{"episode_id": "SQ1_FP_C_0081", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq1\\SQ1_FP_C_0081.json", "metadata": {"sq_type": "SQ1", "sq_name": "设备健康诊断", "variant": "FP", "layout_id": "C", "layout_name": "三室两厅 (3BR)", "profile_id": "family_with_children", "base_date": "2026-06-22T00:00:00", "seed": 20260710, "scenario_id": "DF-06", "total_events": 2464, "anomaly_events_count": 6}, "ground_truth": {"scenario_id": "DF-06-FP", "scenario_name": "DF-06-FP: 窗帘正常移动但速度慢", "category": "device_fault", "is_anomaly": false, "threat_type": "none", "key_difference": "OperationalStatus=closing期间Position在持续变化（5000→5500→7000→10000），最终到达目标位置并停止", "difficulty_score": 9, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 1, "D4_temporal_span": 2, "D5_fp_similarity": 2}, "target_room": "master_bedroom", "injection_time": "2026-06-22T15:24:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": false,\n  \"confidence\": \"high\",\n  \"threat_type\": \"none\",\n  \"threat_description\": \"The master_bedroom occupancy sensor is functioning normally with no detected data loss or state anomalies.\",\n  \"reasoning\": [\"Analyzed contiguous time windows (C00, C01, C28) surrounding the kitchen anomaly at 18:24:00 to verify continuous operation of the master bedroom sensor.\", \"Confirmed that master_bedroom_occupancy consistently reported '1' during the fault window and adjacent periods, indicating robustness against the network transient affecting other sensors.\", \"Verified that temperature readings for master_bedroom_temp_sensor remained within plausible ranges and showed normal diurnal variation, ruling out sensor drift or hardware failure.\"],\n  \"key_evidence\": [\"master_bedroom_occupancy reported '1' consistently in chunks C00, C01, C22, C28, and C29 without interruption.\", \"No null values or missing timestamps were observed for master_bedroom_occupancy logs during the critical event at 18:24:00.\"],\n  \"recommended_actions\": []\n}", "model_response": {"is_anomaly": false, "confidence": "high", "threat_type": "none", "threat_description": "The master_bedroom occupancy sensor is functioning normally with no detected data loss or state anomalies.", "reasoning": ["Analyzed contiguous time windows (C00, C01, C28) surrounding the kitchen anomaly at 18:24:00 to verify continuous operation of the master bedroom sensor.", "Confirmed that master_bedroom_occupancy consistently reported '1' during the fault window and adjacent periods, indicating robustness against the network transient affecting other sensors.", "Verified that temperature readings for master_bedroom_temp_sensor remained within plausible ranges and showed normal diurnal variation, ruling out sensor drift or hardware failure."], "key_evidence": ["master_bedroom_occupancy reported '1' consistently in chunks C00, C01, C22, C28, and C29 without interruption.", "No null values or missing timestamps were observed for master_bedroom_occupancy logs during the critical event at 18:24:00."], "recommended_actions": []}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "CORRECT_REJECT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": false, "confidence": "high"}, "latency": 42.948840856552124, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 2464, "chunk_count": 31, "signals": {"room_activity": {"living_room": 403, "master_bedroom": 526, "kids_room": 517, "kitchen": 303, "dining_room": 219, "second_bedroom": 48, "master_bathroom": 222, "entrance": 225, "second_bathroom": 1}, "attribute_frequency": {"Occupancy": 1254, "MeasuredValue": 1156, "OnOff": 26, "StateValue": 7, "CurrentPositionLiftPercent100ths": 6, "LockState": 5, "OperationalStatus": 2, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 5, "occupancy_events": 1254, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"device-health | single-event-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"master_bedroom_occupancy\", \"kids_room_occupancy\", \"entrance_occupancy\"],\n  \"focus_chunk_ids\": [\"C22\", \"C29\"],\n  \"suspected_patterns\": [\n    \"Sensor data loss (Null value)\",\n    \"Potential false negative occupancy due to sensor failure\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C22 contains a critical anomaly: 'kitchen_temp_sensor' returns 'None' at 18:24:00, indicating a hardware or communication failure.\",\n    \"Chunk C29 shows 'master_bedroom_window' reporting fully closed (100%) while the house is occupied and lights are off, which might indicate a stuck actuator or sensor misalignment if manual intervention wasn't performed, though less critical than the null sensor reading.\",\n    \"Verifying master_bedroom/kids_room occupancy in these chunks helps determine if the temperature drop in C22 was real (house empty) or if the sensor failed to report while people were present.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "device-health | single-event-safety", "focus_rooms": ["kitchen"], "focus_devices": ["kitchen_temp_sensor", "master_bedroom_occupancy", "kids_room_occupancy", "entrance_occupancy"], "focus_chunk_ids": ["C22", "C29"], "suspected_patterns": ["Sensor data loss (Null value)", "Potential false negative occupancy due to sensor failure"], "why_these_chunks": ["Chunk C22 contains a critical anomaly: 'kitchen_temp_sensor' returns 'None' at 18:24:00, indicating a hardware or communication failure.", "Chunk C29 shows 'master_bedroom_window' reporting fully closed (100%) while the house is occupied and lights are off, which might indicate a stuck actuator or sensor misalignment if manual intervention wasn't performed, though less critical than the null sensor reading.", "Verifying master_bedroom/kids_room occupancy in these chunks helps determine if the temperature drop in C22 was real (house empty) or if the sensor failed to report while people were present."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Master bedroom occupancy sensor is functioning normally, correctly detecting continuous presence.\",\n      \"evidence\": [\"Occupancy reported as 1 consistently throughout C22 (18:20-18:55) and C29 (22:46-23:25).\", \"No false negatives or erratic state flips observed in the master_bedroom_occupancy logs.\"],\n      \"weaknesses\": [\"Does not account for potential data loss masked by other sensors' activity; relies on the assumption that a single '1' reading implies valid operation despite system-wide noise.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Intermittent communication failure or sensor glitch in the master bedroom ecosystem, though not explicitly logged as an error code.\",\n      \"threat_type\": \"Data Integrity / False Negative Risk\",\n      \"evidence\": [\n        \"At 18:24:00, the kitchen_temp_sensor returns None while the system is active (lights/cookers on), indicating a transient network or hardware fault affecting the local gateway cluster.\",\n        \"While master_bedroom_temp_sensor does not return None at 18:24:00, its value (2316) deviates slightly from neighbors, suggesting potential synchronization issues or environmental variance during the same fault window.\",\n        \"The 'attribute_frequency' shows low counts for 'OperationalStatus' (2) and 'LockState' (5), suggesting these specific diagnostic attributes are rarely polled, masking underlying device health status.\"\n      ],\n      \"weaknesses\": [\n        \"The master_bedroom_occupancy sensor itself never reported a null value or failure code in the provided chunks; it continued reporting '1'.\",\n        \"Temperature values for master_bedroom remain within plausible ranges and show normal diurnal variation, lacking the erratic jumps often seen in failing thermal sensors.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The simultaneous occurrence of 'kitchen_temp_sensor' returning None at 18:24:00 while house occupancy remains high indicates a systemic transient issue (power blip, gateway reset, or bus collision) rather than isolated master_bedroom hardware failure.\",\n    \"Contrast between 'master_bedroom_occupancy' (consistent 1s) and 'kitchen_temp_sensor' (null spike) suggests the occupancy sensor may be more robust but operates in the same vulnerable network segment.\"\n  ],\n  \"missing_information\": [\n    \"Raw log entries for 'master_bedroom_temp_sensor' OperationalStatus or BatteryLevel to rule out power-induced silent failures.\",\n    \"Timestamped network latency or packet loss metrics around 18:24:00 to confirm if the kitchen null was a local event or a network partition affecting the zone.\",\n    \"History of 'lock_state_flips' specifically tied to the master bedroom door vs. front door to assess actuator stability.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Master bedroom occupancy sensor is functioning normally, correctly detecting continuous presence.", "evidence": ["Occupancy reported as 1 consistently throughout C22 (18:20-18:55) and C29 (22:46-23:25).", "No false negatives or erratic state flips observed in the master_bedroom_occupancy logs."], "weaknesses": ["Does not account for potential data loss masked by other sensors' activity; relies on the assumption that a single '1' reading implies valid operation despite system-wide noise."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Intermittent communication failure or sensor glitch in the master bedroom ecosystem, though not explicitly logged as an error code.", "threat_type": "Data Integrity / False Negative Risk", "evidence": ["At 18:24:00, the kitchen_temp_sensor returns None while the system is active (lights/cookers on), indicating a transient network or hardware fault affecting the local gateway cluster.", "While master_bedroom_temp_sensor does not return None at 18:24:00, its value (2316) deviates slightly from neighbors, suggesting potential synchronization issues or environmental variance during the same fault window.", "The 'attribute_frequency' shows low counts for 'OperationalStatus' (2) and 'LockState' (5), suggesting these specific diagnostic attributes are rarely polled, masking underlying device health status."], "weaknesses": ["The master_bedroom_occupancy sensor itself never reported a null value or failure code in the provided chunks; it continued reporting '1'.", "Temperature values for master_bedroom remain within plausible ranges and show normal diurnal variation, lacking the erratic jumps often seen in failing thermal sensors."]}], "most_discriminative_evidence": ["The simultaneous occurrence of 'kitchen_temp_sensor' returning None at 18:24:00 while house occupancy remains high indicates a systemic transient issue (power blip, gateway reset, or bus collision) rather than isolated master_bedroom hardware failure.", "Contrast between 'master_bedroom_occupancy' (consistent 1s) and 'kitchen_temp_sensor' (null spike) suggests the occupancy sensor may be more robust but operates in the same vulnerable network segment."], "missing_information": ["Raw log entries for 'master_bedroom_temp_sensor' OperationalStatus or BatteryLevel to rule out power-induced silent failures.", "Timestamped network latency or packet loss metrics around 18:24:00 to confirm if the kitchen null was a local event or a network partition affecting the zone.", "History of 'lock_state_flips' specifically tied to the master bedroom door vs. front door to assess actuator stability."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C00\", \"C01\", \"C28\"],\n  \"missing_checks\": [\n    \"Verify 'master_bedroom_occupancy' status immediately before (C00/C01) and after (C28) the anomaly window to confirm continuous operation.\",\n    \"Check for correlated network latency spikes or gateway resets in chunks surrounding C22 to distinguish local sensor failure from systemic outage.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identified that the master_bedroom_occupancy sensor did not report null values during the anomaly, suggesting it may be functioning. However, the evidence is insufficient because the current focus is heavily skewed towards the kitchen anomaly and specific chunks (C22, C29). To definitively rule out intermittent failures or data masking, we need to check contiguous timestamps (C00, C01, C28) around the fault event to ensure no silent gaps occurred.\",\n    \"The investigator's hypothesis relies on the absence of errors in the provided logs; without checking adjacent time windows, a brief communication drop that didn't trigger an error code but caused a data gap cannot be ruled out.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C00", "C01", "C28"], "missing_checks": ["Verify 'master_bedroom_occupancy' status immediately before (C00/C01) and after (C28) the anomaly window to confirm continuous operation.", "Check for correlated network latency spikes or gateway resets in chunks surrounding C22 to distinguish local sensor failure from systemic outage."], "supervisor_notes": ["The analysis correctly identified that the master_bedroom_occupancy sensor did not report null values during the anomaly, suggesting it may be functioning. However, the evidence is insufficient because the current focus is heavily skewed towards the kitchen anomaly and specific chunks (C22, C29). To definitively rule out intermittent failures or data masking, we need to check contiguous timestamps (C00, C01, C28) around the fault event to ensure no silent gaps occurred.", "The investigator's hypothesis relies on the absence of errors in the provided logs; without checking adjacent time windows, a brief communication drop that didn't trigger an error code but caused a data gap cannot be ruled out."]}, "preview_triage_prompt": "## Query\n请检查以下设备状态历史，判断 master_bedroom 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Layout\nLayout: 三室两厅 (3BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kids_room: 儿童房温度传感器<temperature_sensor>, 儿童房灯<dimmable_light>, 儿童房窗帘<window_covering>, 儿童房窗户传感器<contact_sensor>, 儿童房运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅副灯<dimmable_light>, 客厅氛围灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘1<window_covering>, 客厅窗户传感器1<contact_sensor>, 客厅窗户传感器2<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n- master_bathroom: 主卫漏水传感器<water_leak_detector>, 主卫灯<onoff_light>, 主卫运动传感器<occupancy_sensor>\n- master_bedroom: 主卧床头灯<onoff_light>, 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>\n- second_bedroom: 次卧灯<dimmable_light>, 次卧空调<air_conditioner>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 403,\n    \"master_bedroom\": 526,\n    \"kids_room\": 517,\n    \"kitchen\": 303,\n    \"dining_room\": 219,\n    \"second_bedroom\": 48,\n    \"master_bathroom\": 222,\n    \"entrance\": 225,\n    \"second_bathroom\": 1\n  },\n  \"attribute_frequency\": {\n    \"Occupancy\": 1254,\n    \"MeasuredValue\": 1156,\n    \"OnOff\": 26,\n    \"StateValue\": 7,\n    \"CurrentPositionLiftPercent100ths\": 6,\n    \"LockState\": 5,\n    \"OperationalStatus\": 2,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 5,\n  \"occupancy_events\": 1254,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-22T00:00:00\",\n    \"end_ts\": \"2026-06-22T01:10:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 18,\n      \"master_bedroom\": 18,\n      \"kids_room\": 18,\n      \"kitchen\": 14,\n      \"dining_room\": 3,\n      \"second_bedroom\": 3,\n      \"master_bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"kids_room_temp_sensor\",\n      \"kitchen_tem", "preview_verifier_prompt": "## Query\n请检查以下设备状态历史，判断 master_bedroom 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Triage\n{\n  \"latent_task_profile\": \"device-health | single-event-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"master_bedroom_occupancy\", \"kids_room_occupancy\", \"entrance_occupancy\"],\n  \"focus_chunk_ids\": [\"C22\", \"C29\"],\n  \"suspected_patterns\": [\n    \"Sensor data loss (Null value)\",\n    \"Potential false negative occupancy due to sensor failure\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C22 contains a critical anomaly: 'kitchen_temp_sensor' returns 'None' at 18:24:00, indicating a hardware or communication failure.\",\n    \"Chunk C29 shows 'master_bedroom_window' reporting fully closed (100%) while the house is occupied and lights are off, which might indicate a stuck actuator or sensor misalignment if manual intervention wasn't performed, though less critical than the null sensor reading.\",\n    \"Verifying master_bedroom/kids_room occupancy in these chunks helps determine if the temperature drop in C22 was real (house empty) or if the sensor failed to report while people were present.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Master bedroom occupancy sensor is functioning normally, correctly detecting continuous presence.\",\n      \"evidence\": [\"Occupancy reported as 1 consistently throughout C22 (18:20-18:55) and C29 (22:46-23:25).\", \"No false negatives or erratic state flips observed in the master_bedroom_occupancy logs.\"],\n      \"weaknesses\": [\"Does not account for potential data loss masked by other sensors' activity; relies on the assumption that a single '1' reading implies valid operation despite system-wide noise.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Intermittent communication failure or sensor glitch in the master bedroom ecosystem, though not explicitly logged as an error code.\",\n      \"threat_type\": \"Data Integrity / False Negative Risk\",\n      \"evidence\": [\n        \"At 18:24:00, the kitchen_temp_sensor returns None while the system is active (lights/cookers on), indicating a transient network or hardware fault affecting the local gateway cluster.\",\n        \"While master_bedroom_temp_sensor does not return None at 18:24:00, its value (2316) deviates slightly from neighbors, suggesting potential synchronization issues or environmental variance during the same fault window.\",\n        \"The 'attribute_frequency' shows low counts for 'OperationalSt"}}
{"episode_id": "SQ1_FP_B_0088", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq1\\SQ1_FP_B_0088.json", "metadata": {"sq_type": "SQ1", "sq_name": "设备健康诊断", "variant": "FP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "young_professional", "base_date": "2026-06-10T00:00:00", "seed": 20260717, "scenario_id": "DF-03", "total_events": 1830, "anomaly_events_count": 4}, "ground_truth": {"scenario_id": "DF-03-FP", "scenario_name": "DF-03-FP: 宠物活动", "category": "device_fault", "is_anomaly": false, "threat_type": "none", "key_difference": "触发间隔不规律（不是周期性的），且频率较低（几分钟一次不是几十秒一次）", "difficulty_score": 9, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 3, "D2_signal_directness": 2, "D3_cross_device": 1, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "second_bedroom", "injection_time": "2026-06-10T15:11:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": false,\n  \"confidence\": \"high\",\n  \"threat_type\": \"none\",\n  \"threat_description\": \"The second_bedroom sensor is functioning normally with consistent temperature readings, despite a separate anomaly detected in the kitchen sensor.\",\n  \"reasoning\": [\n    \"Analyzed data for 'second_bedroom_temp_sensor' across both provided chunks (C17 and C18).\",\n    \"Observed that the second_bedroom sensor consistently returns valid integer values (ranging from ~2260 to ~2300) at every timestamp where it was recorded.\",\n    \"Confirmed that occupancy events were successfully recorded for the second_bedroom, indicating the device is actively communicating with the system.\"\n  ],\n  \"key_evidence\": [\n    \"In Chunk C17, at timestamps like 19:00:00 and 19:55:00, second_bedroom_temp_sensor reports valid values (2288, 2297) while the kitchen sensor reports None or anomalous values.\",\n    \"In Chunk C18, at timestamps like 19:42:00 (when kitchen sensor is None) and 20:00:00, the second_bedroom sensor continues to report valid integers (2271, 2268).\"\n  ],\n  \"recommended_actions\": [\n    \"Investigate and replace/maintain the kitchen_temp_sensor which is showing data loss and null values.\",\n    \"No immediate action required for the second_bedroom sensor as it appears healthy.\"\n  ]\n}", "model_response": {"is_anomaly": false, "confidence": "high", "threat_type": "none", "threat_description": "The second_bedroom sensor is functioning normally with consistent temperature readings, despite a separate anomaly detected in the kitchen sensor.", "reasoning": ["Analyzed data for 'second_bedroom_temp_sensor' across both provided chunks (C17 and C18).", "Observed that the second_bedroom sensor consistently returns valid integer values (ranging from ~2260 to ~2300) at every timestamp where it was recorded.", "Confirmed that occupancy events were successfully recorded for the second_bedroom, indicating the device is actively communicating with the system."], "key_evidence": ["In Chunk C17, at timestamps like 19:00:00 and 19:55:00, second_bedroom_temp_sensor reports valid values (2288, 2297) while the kitchen sensor reports None or anomalous values.", "In Chunk C18, at timestamps like 19:42:00 (when kitchen sensor is None) and 20:00:00, the second_bedroom sensor continues to report valid integers (2271, 2268)."], "recommended_actions": ["Investigate and replace/maintain the kitchen_temp_sensor which is showing data loss and null values.", "No immediate action required for the second_bedroom sensor as it appears healthy."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "CORRECT_REJECT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 48.86887812614441, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1830, "chunk_count": 23, "signals": {"room_activity": {"living_room": 401, "master_bedroom": 336, "second_bedroom": 340, "kitchen": 298, "bathroom": 222, "entrance": 233}, "attribute_frequency": {"MeasuredValue": 1154, "Occupancy": 647, "OnOff": 14, "StateValue": 5, "LockState": 4, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 4, "occupancy_events": 647, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"device-health\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C17\", \"C18\"],\n  \"suspected_patterns\": [\n    \"Temperature sensor returning null/None values during active heating events\",\n    \"High temperature readings followed by data loss indicating sensor failure or battery drain\"\n  ],\n  \"why_these_chunks\": \"Chunks C17 and C18 contain the critical failure evidence. In C17, the kitchen temperature spikes to ~2665 (anomalous high) just before the cook surface is turned on, and at the end of the chunk, the sensor explicitly returns 'None'. In C18, despite the cook surface being off and temperatures dropping to normal ranges (~2270), the sensor continues to return 'None', confirming a persistent hardware fault rather than a transient glitch.\"\n}", "triage_parsed": {"latent_task_profile": "device-health", "focus_rooms": ["kitchen"], "focus_devices": ["kitchen_temp_sensor"], "focus_chunk_ids": ["C17", "C18"], "suspected_patterns": ["Temperature sensor returning null/None values during active heating events", "High temperature readings followed by data loss indicating sensor failure or battery drain"], "why_these_chunks": "Chunks C17 and C18 contain the critical failure evidence. In C17, the kitchen temperature spikes to ~2665 (anomalous high) just before the cook surface is turned on, and at the end of the chunk, the sensor explicitly returns 'None'. In C18, despite the cook surface being off and temperatures dropping to normal ranges (~2270), the sensor continues to return 'None', confirming a persistent hardware fault rather than a transient glitch."}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The second_bedroom sensor is functioning normally, reporting consistent temperature values (~2270-2300) while the kitchen sensor experiences a transient glitch or communication error specific to that device.\",\n      \"evidence\": [\n        \"second_bedroom_temp_sensor consistently returns valid MeasuredValue integers (e.g., 2297, 2288, 2275) throughout both C17 and C18 chunks.\",\n        \"Occupancy events for second_bedroom are recorded (e.g., at 19:00:00 and 20:00:00), indicating the room's IoT gateway is actively polling devices in this zone.\"\n      ],\n      \"weaknesses\": [\n        \"Fails to explain why the 'kitchen' chunk was selected as the primary focus by the Triage Output if the anomaly were isolated to the kitchen. However, this hypothesis assumes the triage logic might be overly broad or that the kitchen failure triggered a system-wide alert.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"The investigation scope has been misdirected; the actual anomaly lies with the kitchen sensor, not the second bedroom. The second bedroom sensor is normal, but the system health check flagged a critical failure elsewhere.\",\n      \"threat_type\": \"Hardware Failure / Sensor Data Loss\",\n      \"evidence\": [\n        \"Triage Output explicitly identifies focus_room as 'kitchen' and suspected_patterns involve 'Temperature sensor returning null/None values'.\",\n        \"In Chunk C17, kitchen_temp_sensor returns 'None' at 18:52:00 after cooking starts, while second_bedroom continues reporting valid data (2299).\",\n        \"In Chunk C18, kitchen_temp_sensor returns 'None' again at 19:42:00 despite temperatures dropping, while second_bedroom reports valid data (2271).\",\n        \"Structured Signals show 'temperature_patterns': [] (empty), suggesting no aggregate pattern analysis succeeded likely due to the missing kitchen data.\"\n      ],\n      \"weaknesses\": [\n        \"Relies on the assumption that the Triage Output correctly identified the root cause. If the user query strictly demands an evaluation of the *second_bedroom* only based on raw logs, this hypothesis argues the premise of the question contains a false positive regarding the target device.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"Comparison of timestamps 18:52:00 and 19:42:00 shows kitchen_temp_sensor = None while second_bedroom_temp_sensor holds valid integer values, proving the fault is localized to the kitchen sensor.\",\n    \"Triage Output selection of 'kitchen' as focus_room and 'kitchen_temp_sensor' as focus_device contradicts the user's request to check 'second_bedroom', implying the second_bedroom data is actually healthy.\"\n  ],\n  \"missing_information\": [\n    \"Device firmware version and battery status for all sensors involved.\",\n    \"Historical data prior to 2026-06-10 to determine if the kitchen sensor failure is intermittent or permanent.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The second_bedroom sensor is functioning normally, reporting consistent temperature values (~2270-2300) while the kitchen sensor experiences a transient glitch or communication error specific to that device.", "evidence": ["second_bedroom_temp_sensor consistently returns valid MeasuredValue integers (e.g., 2297, 2288, 2275) throughout both C17 and C18 chunks.", "Occupancy events for second_bedroom are recorded (e.g., at 19:00:00 and 20:00:00), indicating the room's IoT gateway is actively polling devices in this zone."], "weaknesses": ["Fails to explain why the 'kitchen' chunk was selected as the primary focus by the Triage Output if the anomaly were isolated to the kitchen. However, this hypothesis assumes the triage logic might be overly broad or that the kitchen failure triggered a system-wide alert."]}], "anomaly_hypotheses": [{"id": "A1", "description": "The investigation scope has been misdirected; the actual anomaly lies with the kitchen sensor, not the second bedroom. The second bedroom sensor is normal, but the system health check flagged a critical failure elsewhere.", "threat_type": "Hardware Failure / Sensor Data Loss", "evidence": ["Triage Output explicitly identifies focus_room as 'kitchen' and suspected_patterns involve 'Temperature sensor returning null/None values'.", "In Chunk C17, kitchen_temp_sensor returns 'None' at 18:52:00 after cooking starts, while second_bedroom continues reporting valid data (2299).", "In Chunk C18, kitchen_temp_sensor returns 'None' again at 19:42:00 despite temperatures dropping, while second_bedroom reports valid data (2271).", "Structured Signals show 'temperature_patterns': [] (empty), suggesting no aggregate pattern analysis succeeded likely due to the missing kitchen data."], "weaknesses": ["Relies on the assumption that the Triage Output correctly identified the root cause. If the user query strictly demands an evaluation of the *second_bedroom* only based on raw logs, this hypothesis argues the premise of the question contains a false positive regarding the target device."]}], "most_discriminative_evidence": ["Comparison of timestamps 18:52:00 and 19:42:00 shows kitchen_temp_sensor = None while second_bedroom_temp_sensor holds valid integer values, proving the fault is localized to the kitchen sensor.", "Triage Output selection of 'kitchen' as focus_room and 'kitchen_temp_sensor' as focus_device contradicts the user's request to check 'second_bedroom', implying the second_bedroom data is actually healthy."], "missing_information": ["Device firmware version and battery status for all sensors involved.", "Historical data prior to 2026-06-10 to determine if the kitchen sensor failure is intermittent or permanent."]}, "supervisor_raw": "{\n  \"on_topic\": false,\n  \"evidence_sufficient\": true,\n  \"needs_more_chunks\": [],\n  \"missing_checks\": [\n    \"Verify if 'second_bedroom' is explicitly mentioned in the Triage Output's focus_rooms or focus_devices fields to confirm scope drift.\",\n    \"Re-evaluate the Investigator's conclusion that the user query premise might be flawed due to the mismatch between the requested device ('second_bedroom') and the triaged anomaly ('kitchen').\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis has drifted significantly from the user's specific query. The user asked to check the 'second_bedroom' sensor status, but the Triage Output explicitly focused on the 'kitchen' sensor (focus_room: 'kitchen', focus_devices: 'kitchen_temp_sensor').\",\n    \"While the Investigator correctly identified that the second_bedroom data appears healthy based on the provided chunks, their reasoning relies heavily on assuming the Triage Output was misdirected rather than directly answering the prompt by confirming the health of the requested room.\",\n    \"The evidence regarding 'second_bedroom' validity is sufficient for the current chunks, but the investigation should have started by explicitly validating the 'second_bedroom' sensors across all relevant timeframes before dismissing the query in favor of the 'kitchen' anomaly.\"\n  ]\n}", "supervisor_parsed": {"on_topic": false, "evidence_sufficient": true, "needs_more_chunks": [], "missing_checks": ["Verify if 'second_bedroom' is explicitly mentioned in the Triage Output's focus_rooms or focus_devices fields to confirm scope drift.", "Re-evaluate the Investigator's conclusion that the user query premise might be flawed due to the mismatch between the requested device ('second_bedroom') and the triaged anomaly ('kitchen')."], "supervisor_notes": ["The analysis has drifted significantly from the user's specific query. The user asked to check the 'second_bedroom' sensor status, but the Triage Output explicitly focused on the 'kitchen' sensor (focus_room: 'kitchen', focus_devices: 'kitchen_temp_sensor').", "While the Investigator correctly identified that the second_bedroom data appears healthy based on the provided chunks, their reasoning relies heavily on assuming the Triage Output was misdirected rather than directly answering the prompt by confirming the health of the requested room.", "The evidence regarding 'second_bedroom' validity is sufficient for the current chunks, but the investigation should have started by explicitly validating the 'second_bedroom' sensors across all relevant timeframes before dismissing the query in favor of the 'kitchen' anomaly."]}, "preview_triage_prompt": "## Query\n请检查以下设备状态历史，判断 second_bedroom 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 401,\n    \"master_bedroom\": 336,\n    \"second_bedroom\": 340,\n    \"kitchen\": 298,\n    \"bathroom\": 222,\n    \"entrance\": 233\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1154,\n    \"Occupancy\": 647,\n    \"OnOff\": 14,\n    \"StateValue\": 5,\n    \"LockState\": 4,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 647,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-10T00:00:00\",\n    \"end_ts\": \"2026-06-10T01:20:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 20,\n      \"master_bedroom\": 19,\n      \"second_bedroom\": 19,\n      \"kitchen\": 16,\n      \"bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"master_bedroom_occupancy\"\n    ],\n    \"alarmish_count\": 15,\n    \"preview_lines\": [\n      \"[2026-06-10T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2276\",\n      \"[2026-06-10T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2267\",\n      \"[2026-06-10T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2272\",\n      \"[2026-06-10T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2279\",\n      \"[2026-06-10T00:00:00] living_room_occupancy | Oc", "preview_verifier_prompt": "## Query\n请检查以下设备状态历史，判断 second_bedroom 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Triage\n{\n  \"latent_task_profile\": \"device-health\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C17\", \"C18\"],\n  \"suspected_patterns\": [\n    \"Temperature sensor returning null/None values during active heating events\",\n    \"High temperature readings followed by data loss indicating sensor failure or battery drain\"\n  ],\n  \"why_these_chunks\": \"Chunks C17 and C18 contain the critical failure evidence. In C17, the kitchen temperature spikes to ~2665 (anomalous high) just before the cook surface is turned on, and at the end of the chunk, the sensor explicitly returns 'None'. In C18, despite the cook surface being off and temperatures dropping to normal ranges (~2270), the sensor continues to return 'None', confirming a persistent hardware fault rather than a transient glitch.\"\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The second_bedroom sensor is functioning normally, reporting consistent temperature values (~2270-2300) while the kitchen sensor experiences a transient glitch or communication error specific to that device.\",\n      \"evidence\": [\n        \"second_bedroom_temp_sensor consistently returns valid MeasuredValue integers (e.g., 2297, 2288, 2275) throughout both C17 and C18 chunks.\",\n        \"Occupancy events for second_bedroom are recorded (e.g., at 19:00:00 and 20:00:00), indicating the room's IoT gateway is actively polling devices in this zone.\"\n      ],\n      \"weaknesses\": [\n        \"Fails to explain why the 'kitchen' chunk was selected as the primary focus by the Triage Output if the anomaly were isolated to the kitchen. However, this hypothesis assumes the triage logic might be overly broad or that the kitchen failure triggered a system-wide alert.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"The investigation scope has been misdirected; the actual anomaly lies with the kitchen sensor, not the second bedroom. The second bedroom sensor is normal, but the system health check flagged a critical failure elsewhere.\",\n      \"threat_type\": \"Hardware Failure / Sensor Data Loss\",\n      \"evidence\": [\n        \"Triage Output explicitly identifies focus_room as 'kitchen' and suspected_patterns involve 'Temperature sensor returning null/None values'.\",\n        \"In Chunk C17, kitchen_temp_sensor returns 'None' at 18:52:00 after cooking starts, w"}}
{"episode_id": "SQ1_FP_A_0080", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq1\\SQ1_FP_A_0080.json", "metadata": {"sq_type": "SQ1", "sq_name": "设备健康诊断", "variant": "FP", "layout_id": "A", "layout_name": "一室一厅 (Studio/1BR)", "profile_id": "young_professional", "base_date": "2026-06-12T00:00:00", "seed": 20260709, "scenario_id": "DF-04", "total_events": 1117, "anomaly_events_count": 3}, "ground_truth": {"scenario_id": "DF-04-FP", "scenario_name": "DF-04-FP: 门锁响应延迟但最终成功锁定", "category": "device_fault", "is_anomaly": false, "threat_type": "none", "key_difference": "虽然响应延迟了几秒，但最终LockState变为Locked(1)，没有触发DoorLockAlarm", "difficulty_score": 8, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 1, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "entrance", "injection_time": "2026-06-12T17:51:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"The door contact sensor malfunctioned by reporting the door as closed immediately after it was opened, triggering an erroneous automatic lock command.\",\n  \"reasoning\": [\n      \"At 07:15:20, the front_door_contact sensor reported StateValue = False (Open).\",\n      \"Only 3 seconds later at 07:15:22, the sensor reported StateValue = True (Closed), indicating a rapid closure or sensor glitch.\",\n      \"Critically, at 07:15:23, the system executed a LockOperation (Auto) while the sensor had only just flipped to 'Closed', and no human occupancy was recorded during this transition window.\",\n      \"This sequence suggests the automation logic locked the door based on a potentially false-positive 'closed' signal appearing too quickly after the door was physically opened, or the door remained open the entire time and the sensor failed to report the open state correctly until the lock attempt occurred.\"\n    ],\n  \"key_evidence\": [\n      \"Sequence: Open Report (07:15:20) -> Closed Report (07:15:22) -> Auto Lock (07:15:23)\",\n      \"Absence of Occupancy events in Entrance/Living Room between 07:15:18 and 07:15:23\"\n    ],\n  \"recommended_actions\": [\n      \"Physically verify if the door was actually closed when the lock command was issued.\",\n      \"Inspect and recalibrate the front_door_contact sensor for intermittent failures or misalignment.\",\n      \"Review automation rules to add a hysteresis delay before auto-locking after a state change from Open to Closed.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "The door contact sensor malfunctioned by reporting the door as closed immediately after it was opened, triggering an erroneous automatic lock command.", "reasoning": ["At 07:15:20, the front_door_contact sensor reported StateValue = False (Open).", "Only 3 seconds later at 07:15:22, the sensor reported StateValue = True (Closed), indicating a rapid closure or sensor glitch.", "Critically, at 07:15:23, the system executed a LockOperation (Auto) while the sensor had only just flipped to 'Closed', and no human occupancy was recorded during this transition window.", "This sequence suggests the automation logic locked the door based on a potentially false-positive 'closed' signal appearing too quickly after the door was physically opened, or the door remained open the entire time and the sensor failed to report the open state correctly until the lock attempt occurred."], "key_evidence": ["Sequence: Open Report (07:15:20) -> Closed Report (07:15:22) -> Auto Lock (07:15:23)", "Absence of Occupancy events in Entrance/Living Room between 07:15:18 and 07:15:23"], "recommended_actions": ["Physically verify if the door was actually closed when the lock command was issued.", "Inspect and recalibrate the front_door_contact sensor for intermittent failures or misalignment.", "Review automation rules to add a hysteresis delay before auto-locking after a state change from Open to Closed."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 50.635998249053955, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1117, "chunk_count": 14, "signals": {"room_activity": {"living_room": 397, "bedroom": 353, "kitchen": 298, "bathroom": 52, "entrance": 17}, "attribute_frequency": {"MeasuredValue": 866, "Occupancy": 212, "OnOff": 18, "LockState": 6, "StateValue": 5, "CurrentPositionLiftPercent100ths": 2, "SystemMode": 1, "OperationalState": 1, "CurrentLevel": 1}, "lock_state_flips": 6, "occupancy_events": 212, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"single-event-safety\",\n  \"focus_rooms\": [\"entrance\"],\n  \"focus_devices\": [\"front_door_contact\", \"front_door_lock\"],\n  \"focus_chunk_ids\": [\"C04\"],\n  \"suspected_patterns\": [\n    \"Door open immediately followed by lock operation without clear occupancy correlation\",\n    \"Potential sensor lag or false negative on door contact state relative to lock state change\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C04 is the only segment containing explicit events for 'front_door_contact' and 'front_door_lock'.\",\n    \"The sequence shows the door contact flipping to False (open) at 07:15:20, then immediately locking at 07:15:23 while the door was reportedly open.\",\n    \"This specific temporal proximity suggests a potential fault in the contact sensor reporting the door as closed when it was actually open, or a logic error in the automation routine triggered by the faulty signal.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "single-event-safety", "focus_rooms": ["entrance"], "focus_devices": ["front_door_contact", "front_door_lock"], "focus_chunk_ids": ["C04"], "suspected_patterns": ["Door open immediately followed by lock operation without clear occupancy correlation", "Potential sensor lag or false negative on door contact state relative to lock state change"], "why_these_chunks": ["Chunk C04 is the only segment containing explicit events for 'front_door_contact' and 'front_door_lock'.", "The sequence shows the door contact flipping to False (open) at 07:15:20, then immediately locking at 07:15:23 while the door was reportedly open.", "This specific temporal proximity suggests a potential fault in the contact sensor reporting the door as closed when it was actually open, or a logic error in the automation routine triggered by the faulty signal."]}, "investigator_raw": "```json\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The door contact sensor is functioning correctly, and the locking event was a standard automation routine triggered by an external signal or timer, not necessarily linked to the immediate physical state of the door at that exact second.\",\n      \"evidence\": [\n        \"Standard lock operation events (LockOperationType=0) often occur automatically based on schedules or external triggers independent of real-time contact verification.\",\n        \"The system successfully reported the LockState as 'Locked' (1) immediately after the operation.\"\n      ],\n      \"weaknesses\": [\n        \"Fails to explain why the automation triggered while the contact sensor explicitly reported the door was open ('False') just moments prior.\",\n        \"Does not account for the lack of occupancy data in the entrance area to justify an auto-lock if the door was physically open.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"The front_door_contact sensor is experiencing a false negative or intermittent failure, reporting the door as closed when it was actually left open, triggering an erroneous auto-lock command.\",\n      \"threat_type\": \"Sensor Fault / Logic Error\",\n      \"evidence\": [\n        \"At 07:15:20, the sensor reports StateValue = False (Open).\",\n        \"At 07:15:23 (3 seconds later), the system executes LockOperation despite the door being reported as Open.\",\n        \"Logical inconsistency: A standard safety protocol would prevent locking an open door; doing so implies the system believes the door is closed based on the faulty sensor reading.\",\n        \"No subsequent occupancy events or door closure confirmations are visible in the provided chunk to correct this state before the lock attempt.\"\n      ],\n      \"weaknesses\": [\n        \"Cannot definitively prove the physical state of the door without video confirmation; the door could have been opened, then quickly closed by an unseen agent (though no occupancy spike is recorded).\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Data synchronization lag between the contact sensor and the lock controller caused a race condition where the lock command executed before the final 'closed' state was registered.\",\n      \"threat_type\": \"System Latency\",\n      \"evidence\": [\n        \"Short temporal gap (3 seconds) between the 'Open' report and the 'Lock' command.\",\n        \"Potential network latency in transmitting the final 'Closed' state update.\"\n      ],\n      \"weaknesses\": [\n        \"Highly unlikely that a 3-second lag would cause a security vulnerability unless the door remained open the entire time, which contradicts the eventual locked state assumption.\",\n        \"Less severe than a hard sensor failure but still indicates system inefficiency.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The specific sequence: 07:15:20 (Contact=False/Open) -> 07:15:23 (LockOperation/Auto). The execution of a lock command while the primary sensor indicates the path is open is the strongest indicator of sensor failure or flawed logic.\",\n    \"The absence of any 'Occupancy' events for the entrance room during this critical window suggests no human presence to manually verify the door state or override the automated action.\"\n  ],\n  \"missing_information\": [\n    \"Physical verification log or camera footage of the entrance area around 07:15:20-07:15:25 to confirm if the door was actually open.\",\n    \"Configuration details of the 'Auto' lock source to determine if it ignores contact status or requires a specific condition that might be misinterpreted.\",\n    \"History of similar events (lock operations with open doors) to distinguish between a one-time glitch and a systemic pattern.\"\n  ]\n}\n```", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The door contact sensor is functioning correctly, and the locking event was a standard automation routine triggered by an external signal or timer, not necessarily linked to the immediate physical state of the door at that exact second.", "evidence": ["Standard lock operation events (LockOperationType=0) often occur automatically based on schedules or external triggers independent of real-time contact verification.", "The system successfully reported the LockState as 'Locked' (1) immediately after the operation."], "weaknesses": ["Fails to explain why the automation triggered while the contact sensor explicitly reported the door was open ('False') just moments prior.", "Does not account for the lack of occupancy data in the entrance area to justify an auto-lock if the door was physically open."]}], "anomaly_hypotheses": [{"id": "A1", "description": "The front_door_contact sensor is experiencing a false negative or intermittent failure, reporting the door as closed when it was actually left open, triggering an erroneous auto-lock command.", "threat_type": "Sensor Fault / Logic Error", "evidence": ["At 07:15:20, the sensor reports StateValue = False (Open).", "At 07:15:23 (3 seconds later), the system executes LockOperation despite the door being reported as Open.", "Logical inconsistency: A standard safety protocol would prevent locking an open door; doing so implies the system believes the door is closed based on the faulty sensor reading.", "No subsequent occupancy events or door closure confirmations are visible in the provided chunk to correct this state before the lock attempt."], "weaknesses": ["Cannot definitively prove the physical state of the door without video confirmation; the door could have been opened, then quickly closed by an unseen agent (though no occupancy spike is recorded)."]}, {"id": "A2", "description": "Data synchronization lag between the contact sensor and the lock controller caused a race condition where the lock command executed before the final 'closed' state was registered.", "threat_type": "System Latency", "evidence": ["Short temporal gap (3 seconds) between the 'Open' report and the 'Lock' command.", "Potential network latency in transmitting the final 'Closed' state update."], "weaknesses": ["Highly unlikely that a 3-second lag would cause a security vulnerability unless the door remained open the entire time, which contradicts the eventual locked state assumption.", "Less severe than a hard sensor failure but still indicates system inefficiency."]}], "most_discriminative_evidence": ["The specific sequence: 07:15:20 (Contact=False/Open) -> 07:15:23 (LockOperation/Auto). The execution of a lock command while the primary sensor indicates the path is open is the strongest indicator of sensor failure or flawed logic.", "The absence of any 'Occupancy' events for the entrance room during this critical window suggests no human presence to manually verify the door state or override the automated action."], "missing_information": ["Physical verification log or camera footage of the entrance area around 07:15:20-07:15:25 to confirm if the door was actually open.", "Configuration details of the 'Auto' lock source to determine if it ignores contact status or requires a specific condition that might be misinterpreted.", "History of similar events (lock operations with open doors) to distinguish between a one-time glitch and a systemic pattern."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C03\", \"C05\"],\n  \"missing_checks\": [\n    \"Verify if the door physically closed between 07:15:20 and 07:15:23 in chunks C03 (pre-event) or C05 (post-event) to rule out rapid closure.\",\n    \"Check for occupancy events in surrounding chunks to determine if a user was present to manually override or close the door.\",\n    \"Review configuration logs to see if the lock automation logic explicitly ignores contact sensor status.\"\n  ],\n  \"supervisor_notes\": [\n    \"The investigation correctly identified the anomaly in C04 (locking while sensor reports open).\",\n    \"However, the evidence is currently insufficient to distinguish between 'Sensor Fault' and 'Rapid Closure followed by Latency'.\",\n    \"Chunk C03 is needed to see if the door was closing/opening just before the event, which might explain the state flip at 07:15:20.\",\n    \"Chunk C05 is needed to verify if the door remained open or closed immediately after the lock command, confirming the final physical state.\",\n    \"Without checking these adjacent time windows, the conclusion remains speculative regarding the root cause.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C03", "C05"], "missing_checks": ["Verify if the door physically closed between 07:15:20 and 07:15:23 in chunks C03 (pre-event) or C05 (post-event) to rule out rapid closure.", "Check for occupancy events in surrounding chunks to determine if a user was present to manually override or close the door.", "Review configuration logs to see if the lock automation logic explicitly ignores contact sensor status."], "supervisor_notes": ["The investigation correctly identified the anomaly in C04 (locking while sensor reports open).", "However, the evidence is currently insufficient to distinguish between 'Sensor Fault' and 'Rapid Closure followed by Latency'.", "Chunk C03 is needed to see if the door was closing/opening just before the event, which might explain the state flip at 07:15:20.", "Chunk C05 is needed to verify if the door remained open or closed immediately after the lock command, confirming the final physical state.", "Without checking these adjacent time windows, the conclusion remains speculative regarding the root cause."]}, "preview_triage_prompt": "## Query\n请检查以下设备状态历史，判断 entrance 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Layout\nLayout: 一室一厅 (Studio/1BR)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅台灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 397,\n    \"bedroom\": 353,\n    \"kitchen\": 298,\n    \"bathroom\": 52,\n    \"entrance\": 17\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 866,\n    \"Occupancy\": 212,\n    \"OnOff\": 18,\n    \"LockState\": 6,\n    \"StateValue\": 5,\n    \"CurrentPositionLiftPercent100ths\": 2,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 6,\n  \"occupancy_events\": 212,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-12T00:00:00\",\n    \"end_ts\": \"2026-06-12T01:50:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 27,\n      \"bedroom\": 27,\n      \"kitchen\": 22,\n      \"bathroom\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"bathroom_occupancy\"\n    ],\n    \"alarmish_count\": 12,\n    \"preview_lines\": [\n      \"[2026-06-12T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2275\",\n      \"[2026-06-12T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2169\",\n      \"[2026-06-12T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2279\",\n      \"[2026-06-12T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-12T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-12T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-12T00:05:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2271\",\n      \"[2026-06-12T00:05:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2165\",\n      \"[2026-06-12T00:05:00] kitchen_t", "preview_verifier_prompt": "## Query\n请检查以下设备状态历史，判断 entrance 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Triage\n{\n  \"latent_task_profile\": \"single-event-safety\",\n  \"focus_rooms\": [\"entrance\"],\n  \"focus_devices\": [\"front_door_contact\", \"front_door_lock\"],\n  \"focus_chunk_ids\": [\"C04\"],\n  \"suspected_patterns\": [\n    \"Door open immediately followed by lock operation without clear occupancy correlation\",\n    \"Potential sensor lag or false negative on door contact state relative to lock state change\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C04 is the only segment containing explicit events for 'front_door_contact' and 'front_door_lock'.\",\n    \"The sequence shows the door contact flipping to False (open) at 07:15:20, then immediately locking at 07:15:23 while the door was reportedly open.\",\n    \"This specific temporal proximity suggests a potential fault in the contact sensor reporting the door as closed when it was actually open, or a logic error in the automation routine triggered by the faulty signal.\"\n  ]\n}\n\n## Investigator\n```json\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The door contact sensor is functioning correctly, and the locking event was a standard automation routine triggered by an external signal or timer, not necessarily linked to the immediate physical state of the door at that exact second.\",\n      \"evidence\": [\n        \"Standard lock operation events (LockOperationType=0) often occur automatically based on schedules or external triggers independent of real-time contact verification.\",\n        \"The system successfully reported the LockState as 'Locked' (1) immediately after the operation.\"\n      ],\n      \"weaknesses\": [\n        \"Fails to explain why the automation triggered while the contact sensor explicitly reported the door was open ('False') just moments prior.\",\n        \"Does not account for the lack of occupancy data in the entrance area to justify an auto-lock if the door was physically open.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"The front_door_contact sensor is experiencing a false negative or intermittent failure, reporting the door as closed when it was actually left open, triggering an erroneous auto-lock command.\",\n      \"threat_type\": \"Sensor Fault / Logic Error\",\n      \"evidence\": [\n        \"At 07:15:20, the sensor reports StateValue = False (Open).\",\n        \"At 07:15:23 (3 seconds later), the system executes LockOperation despite the door being reported as Open.\",\n        \"Logical "}}
{"episode_id": "SQ1_FP_B_0092", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq1\\SQ1_FP_B_0092.json", "metadata": {"sq_type": "SQ1", "sq_name": "设备健康诊断", "variant": "FP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "family_with_children", "base_date": "2026-06-06T00:00:00", "seed": 20260721, "scenario_id": "DF-05", "total_events": 1397, "anomaly_events_count": 5}, "ground_truth": {"scenario_id": "DF-05-FP", "scenario_name": "DF-05-FP: 烟雾报警器正常自检", "category": "device_fault", "is_anomaly": false, "threat_type": "none", "key_difference": "有完整的自检流程（TestInProgress=true → SelfTestComplete → TestInProgress=false），不是HardwareFault", "difficulty_score": 6, "difficulty_level": 1, "difficulty_label": "L1_basic_detection", "difficulty_dimensions": {"D1_evidence_count": 1, "D2_signal_directness": 1, "D3_cross_device": 1, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "kitchen", "injection_time": "2026-06-06T18:45:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"medium\",\n  \"threat_type\": \"sensor_drift\",\n  \"threat_description\": \"The kitchen temperature sensor exhibits significant data drift and erratic oscillations compared to stable neighboring sensors, indicating potential hardware degradation or calibration failure.\",\n  \"reasoning\": [\n    \"Analysis of C12 shows the kitchen temperature sensor tracking closely with other rooms (e.g., dropping from 2391 to 2337) with smooth, consistent intervals.\",\n    \"In C13, the kitchen sensor displays abnormal behavior: values oscillate rapidly between 2315, 2310, 2308, and back up, unlike the smooth trends in living_room and bedroom sensors.\",\n    \"At 18:45:00, the kitchen sensor drops precipitously from 2310 to 2295 immediately before the smoke alarm self-test, while other rooms show much smaller relative shifts, suggesting a malfunction rather than environmental noise.\",\n    \"Following the test in C13/C14, the readings remain unstable (fluctuating between 2290-2288), failing to settle into the steady cooling trend observed in adjacent rooms.\"\n  ],\n  \"key_evidence\": [\n    \"Kitchen sensor oscillation pattern in C13 (2315->2310->2308->2315) contrasts sharply with linear cooling in other rooms.\",\n    \"Abnormal sharp drop from 2310 to 2295 at 18:45:00 coinciding with the start of the smoke alarm self-test.\",\n    \"Persistent instability in post-test readings (C14) where kitchen sensor jumps between 2280-2288 while others stabilize around 2260-2270.\"\n  ],\n  \"recommended_actions\": [\n    \"Calibrate the kitchen temperature sensor immediately to correct offset errors.\",\n    \"Inspect the sensor for physical obstructions or interference from nearby cooking appliances.\",\n    \"If calibration fails, replace the sensor as it likely suffers from internal component degradation.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "medium", "threat_type": "sensor_drift", "threat_description": "The kitchen temperature sensor exhibits significant data drift and erratic oscillations compared to stable neighboring sensors, indicating potential hardware degradation or calibration failure.", "reasoning": ["Analysis of C12 shows the kitchen temperature sensor tracking closely with other rooms (e.g., dropping from 2391 to 2337) with smooth, consistent intervals.", "In C13, the kitchen sensor displays abnormal behavior: values oscillate rapidly between 2315, 2310, 2308, and back up, unlike the smooth trends in living_room and bedroom sensors.", "At 18:45:00, the kitchen sensor drops precipitously from 2310 to 2295 immediately before the smoke alarm self-test, while other rooms show much smaller relative shifts, suggesting a malfunction rather than environmental noise.", "Following the test in C13/C14, the readings remain unstable (fluctuating between 2290-2288), failing to settle into the steady cooling trend observed in adjacent rooms."], "key_evidence": ["Kitchen sensor oscillation pattern in C13 (2315->2310->2308->2315) contrasts sharply with linear cooling in other rooms.", "Abnormal sharp drop from 2310 to 2295 at 18:45:00 coinciding with the start of the smoke alarm self-test.", "Persistent instability in post-test readings (C14) where kitchen sensor jumps between 2280-2288 while others stabilize around 2260-2270."], "recommended_actions": ["Calibrate the kitchen temperature sensor immediately to correct offset errors.", "Inspect the sensor for physical obstructions or interference from nearby cooking appliances.", "If calibration fails, replace the sensor as it likely suffers from internal component degradation."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "medium"}, "latency": 56.57708430290222, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1397, "chunk_count": 18, "signals": {"room_activity": {"living_room": 336, "master_bedroom": 336, "second_bedroom": 336, "kitchen": 293, "bathroom": 48, "entrance": 48}, "attribute_frequency": {"MeasuredValue": 1152, "Occupancy": 240, "TestInProgress": 2, "ExpressedState": 2}, "lock_state_flips": 0, "occupancy_events": 240, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"device-health | single-event-safety | composite-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"kitchen_smoke_alarm\"],\n  \"focus_chunk_ids\": [\"C13\"],\n  \"suspected_patterns\": [\n    \"Sensor_Data_Drift\",\n    \"Missing_Safety_Alarm_Event\",\n    \"Event_Count_Anomaly\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C13 is the only chunk where 'kitchen_smoke_alarm' appears in top devices and has an elevated 'alarmish_count' (19), yet no explicit alarm event is visible in the preview lines, suggesting a potential false positive or sensor malfunction.\",\n    \"The kitchen temperature sensor shows significant fluctuations in C13 compared to other chunks, which could trigger safety alerts if the threshold is low.\",\n    \"The 'event_count' for kitchen in C13 (20) is notably higher than the typical ~16-17 seen in other chunks, indicating unusual activity or stuck reporting.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "device-health | single-event-safety | composite-safety", "focus_rooms": ["kitchen"], "focus_devices": ["kitchen_temp_sensor", "kitchen_smoke_alarm"], "focus_chunk_ids": ["C13"], "suspected_patterns": ["Sensor_Data_Drift", "Missing_Safety_Alarm_Event", "Event_Count_Anomaly"], "why_these_chunks": ["Chunk C13 is the only chunk where 'kitchen_smoke_alarm' appears in top devices and has an elevated 'alarmish_count' (19), yet no explicit alarm event is visible in the preview lines, suggesting a potential false positive or sensor malfunction.", "The kitchen temperature sensor shows significant fluctuations in C13 compared to other chunks, which could trigger safety alerts if the threshold is low.", "The 'event_count' for kitchen in C13 (20) is notably higher than the typical ~16-17 seen in other chunks, indicating unusual activity or stuck reporting."]}, "investigator_raw": "```json\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Kitchen sensors are functioning normally, reporting stable temperature readings consistent with the rest of the house during a cooling trend.\",\n      \"evidence\": [\n        \"kitchen_temp_sensor reports values decreasing from 2331 to 2295 over time, similar to other rooms (e.g., living_room dropping from 2325 to 2297).\",\n        \"No explicit alarm triggers or 'TestInProgress' flags appear for the kitchen smoke alarm until a scheduled self-test at 18:45:00.\"\n      ],\n      \"weaknesses\": [\n        \"The magnitude of temperature fluctuation in the kitchen sensor appears slightly higher than neighbors at certain intervals (e.g., 2315 -> 2295 drop vs others), though this could be normal variance.\",\n        \"Does not account for the specific spike in event count noted in the triage output if that metric is derived from raw log frequency rather than just visible lines.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Kitchen temperature sensor exhibits data drift or instability, potentially indicating hardware degradation or calibration failure.\",\n      \"threat_type\": \"Sensor_Data_Drift\",\n      \"evidence\": [\n        \"Between 18:10 and 18:45, the kitchen sensor shows erratic jumps: 2315 -> 2310 -> 2308 -> 2315 -> 2310 -> 2295. While other sensors show smooth trends, the kitchen sensor oscillates more frequently within short windows.\",\n        \"At 18:45, immediately before the smoke alarm self-test, the kitchen temperature reads 2295, which is significantly lower than the previous reading of 2310 (a ~1.5 degree drop in 5 mins) while other rooms showed less dramatic shifts relative to their own baselines.\",\n        \"The 'Event_Count_Anomaly' suspected by triage suggests a higher frequency of state changes or retries not fully explained by simple cooling.\"\n      ],\n      \"weaknesses\": [\n        \"Temperature fluctuations can occur due to environmental factors (opening doors, cooking residual heat) even if the sensor itself is healthy; without external context, it's hard to rule out environmental noise.\",\n        \"The absolute difference between sensors (e.g., Kitchen 2295 vs Living Room 2307) is small enough to be within normal device tolerance ranges.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Kitchen smoke alarm behavior indicates a potential false positive trigger or sensitivity issue during its self-test cycle.\",\n      \"threat_type\": \"Missing_Safety_Alarm_Event | False Positive Risk\",\n      \"evidence\": [\n        \"Triage output notes an 'elevated alarmish_count (19)' for C13, yet the provided logs only show one clear event sequence: TestInProgress=True followed by SelfTestComplete(). The discrepancy between the high internal count and low visible events suggests hidden transient alarms.\",\n        \"At 18:45:00, the sensor enters TestInProgress mode with ExpressedState=4, then completes at 18:45:30. If 'alarmish_count' includes near-misses or threshold crossings during this test, the sensor might be overly sensitive.\",\n        \"The presence of 'TestInProgress' and 'ExpressedState' flags confirms the device is active, but the gap between the expected number of safety events and observed ones raises questions about filtering logic or sensor stability.\"\n      ],\n      \"weaknesses\": [\n        \"The logs explicitly show a successful completion of the self-test ('SelfTestComplete'), which usually validates the sensor's health. An anomaly might only exist in metadata not present in these specific text lines.\",\n        \"Without access to the full definition of 'alarmish_count', we cannot confirm if those 19 counts represent actual fire hazards, false positives, or internal diagnostic pings.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"Discrepancy between Triaged 'alarmish_count' of 19 and the visible single self-test event sequence in Chunk C13.\",\n    \"Higher frequency of temperature value changes in the kitchen sensor compared to the smoother trajectories of living_room and bedroom sensors in the same timestamp window.\",\n    \"Sudden temperature drop in kitchen sensor (2310 to 2295) coinciding with the start of the smoke alarm self-test, suggesting potential cross-sensitivity or timing correlation.\"\n  ],\n  \"missing_information\": [\n    \"Definition of 'alarmish_count': Does it include near-threshold readings, retries, or only confirmed alarms?\",\n    \"Historical baseline data for kitchen temperature variance to determine if the current fluctuations are abnormal.\",\n    \"Full event log for the smoke alarm prior to 18:45:00 to verify the source of the reported 19 'alarmish' events.\",\n    \"Environmental context (e.g., was cooking occurring?) to explain rapid temperature shifts.\"\n  ]\n}\n```", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Kitchen sensors are functioning normally, reporting stable temperature readings consistent with the rest of the house during a cooling trend.", "evidence": ["kitchen_temp_sensor reports values decreasing from 2331 to 2295 over time, similar to other rooms (e.g., living_room dropping from 2325 to 2297).", "No explicit alarm triggers or 'TestInProgress' flags appear for the kitchen smoke alarm until a scheduled self-test at 18:45:00."], "weaknesses": ["The magnitude of temperature fluctuation in the kitchen sensor appears slightly higher than neighbors at certain intervals (e.g., 2315 -> 2295 drop vs others), though this could be normal variance.", "Does not account for the specific spike in event count noted in the triage output if that metric is derived from raw log frequency rather than just visible lines."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Kitchen temperature sensor exhibits data drift or instability, potentially indicating hardware degradation or calibration failure.", "threat_type": "Sensor_Data_Drift", "evidence": ["Between 18:10 and 18:45, the kitchen sensor shows erratic jumps: 2315 -> 2310 -> 2308 -> 2315 -> 2310 -> 2295. While other sensors show smooth trends, the kitchen sensor oscillates more frequently within short windows.", "At 18:45, immediately before the smoke alarm self-test, the kitchen temperature reads 2295, which is significantly lower than the previous reading of 2310 (a ~1.5 degree drop in 5 mins) while other rooms showed less dramatic shifts relative to their own baselines.", "The 'Event_Count_Anomaly' suspected by triage suggests a higher frequency of state changes or retries not fully explained by simple cooling."], "weaknesses": ["Temperature fluctuations can occur due to environmental factors (opening doors, cooking residual heat) even if the sensor itself is healthy; without external context, it's hard to rule out environmental noise.", "The absolute difference between sensors (e.g., Kitchen 2295 vs Living Room 2307) is small enough to be within normal device tolerance ranges."]}, {"id": "A2", "description": "Kitchen smoke alarm behavior indicates a potential false positive trigger or sensitivity issue during its self-test cycle.", "threat_type": "Missing_Safety_Alarm_Event | False Positive Risk", "evidence": ["Triage output notes an 'elevated alarmish_count (19)' for C13, yet the provided logs only show one clear event sequence: TestInProgress=True followed by SelfTestComplete(). The discrepancy between the high internal count and low visible events suggests hidden transient alarms.", "At 18:45:00, the sensor enters TestInProgress mode with ExpressedState=4, then completes at 18:45:30. If 'alarmish_count' includes near-misses or threshold crossings during this test, the sensor might be overly sensitive.", "The presence of 'TestInProgress' and 'ExpressedState' flags confirms the device is active, but the gap between the expected number of safety events and observed ones raises questions about filtering logic or sensor stability."], "weaknesses": ["The logs explicitly show a successful completion of the self-test ('SelfTestComplete'), which usually validates the sensor's health. An anomaly might only exist in metadata not present in these specific text lines.", "Without access to the full definition of 'alarmish_count', we cannot confirm if those 19 counts represent actual fire hazards, false positives, or internal diagnostic pings."]}], "most_discriminative_evidence": ["Discrepancy between Triaged 'alarmish_count' of 19 and the visible single self-test event sequence in Chunk C13.", "Higher frequency of temperature value changes in the kitchen sensor compared to the smoother trajectories of living_room and bedroom sensors in the same timestamp window.", "Sudden temperature drop in kitchen sensor (2310 to 2295) coinciding with the start of the smoke alarm self-test, suggesting potential cross-sensitivity or timing correlation."], "missing_information": ["Definition of 'alarmish_count': Does it include near-threshold readings, retries, or only confirmed alarms?", "Historical baseline data for kitchen temperature variance to determine if the current fluctuations are abnormal.", "Full event log for the smoke alarm prior to 18:45:00 to verify the source of the reported 19 'alarmish' events.", "Environmental context (e.g., was cooking occurring?) to explain rapid temperature shifts."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C12\", \"C14\"],\n  \"missing_checks\": [\n    \"Retrieve full event logs for C13 to verify the source of the 19 'alarmish_count' entries.\",\n    \"Compare kitchen temperature variance trends in adjacent chunks (C12, C14) to establish a baseline for normal fluctuation.\"\n  ],\n  \"supervisor_notes\": [\n    \"The current analysis correctly identifies potential data drift and alarm count discrepancies but relies heavily on limited visibility within Chunk C13.\",\n    \"To confirm if the temperature oscillations are anomalies or environmental noise, direct comparison with the immediate preceding (C12) and succeeding (C14) time windows is required to establish a temporal baseline.\",\n    \"The definition of 'alarmish_count' remains unknown; without retrieving the full log for C13, we cannot distinguish between hardware faults and benign near-misses.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C12", "C14"], "missing_checks": ["Retrieve full event logs for C13 to verify the source of the 19 'alarmish_count' entries.", "Compare kitchen temperature variance trends in adjacent chunks (C12, C14) to establish a baseline for normal fluctuation."], "supervisor_notes": ["The current analysis correctly identifies potential data drift and alarm count discrepancies but relies heavily on limited visibility within Chunk C13.", "To confirm if the temperature oscillations are anomalies or environmental noise, direct comparison with the immediate preceding (C12) and succeeding (C14) time windows is required to establish a temporal baseline.", "The definition of 'alarmish_count' remains unknown; without retrieving the full log for C13, we cannot distinguish between hardware faults and benign near-misses."]}, "preview_triage_prompt": "## Query\n请检查以下设备状态历史，判断 kitchen 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 336,\n    \"master_bedroom\": 336,\n    \"second_bedroom\": 336,\n    \"kitchen\": 293,\n    \"bathroom\": 48,\n    \"entrance\": 48\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1152,\n    \"Occupancy\": 240,\n    \"TestInProgress\": 2,\n    \"ExpressedState\": 2\n  },\n  \"lock_state_flips\": 0,\n  \"occupancy_events\": 240,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-06T00:00:00\",\n    \"end_ts\": \"2026-06-06T01:20:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 20,\n      \"master_bedroom\": 19,\n      \"second_bedroom\": 19,\n      \"kitchen\": 16,\n      \"bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"master_bedroom_occupancy\"\n    ],\n    \"alarmish_count\": 15,\n    \"preview_lines\": [\n      \"[2026-06-06T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2280\",\n      \"[2026-06-06T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2266\",\n      \"[2026-06-06T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2281\",\n      \"[2026-06-06T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2268\",\n      \"[2026-06-06T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-06T00:00:00] maste", "preview_verifier_prompt": "## Query\n请检查以下设备状态历史，判断 kitchen 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Triage\n{\n  \"latent_task_profile\": \"device-health | single-event-safety | composite-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"kitchen_smoke_alarm\"],\n  \"focus_chunk_ids\": [\"C13\"],\n  \"suspected_patterns\": [\n    \"Sensor_Data_Drift\",\n    \"Missing_Safety_Alarm_Event\",\n    \"Event_Count_Anomaly\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C13 is the only chunk where 'kitchen_smoke_alarm' appears in top devices and has an elevated 'alarmish_count' (19), yet no explicit alarm event is visible in the preview lines, suggesting a potential false positive or sensor malfunction.\",\n    \"The kitchen temperature sensor shows significant fluctuations in C13 compared to other chunks, which could trigger safety alerts if the threshold is low.\",\n    \"The 'event_count' for kitchen in C13 (20) is notably higher than the typical ~16-17 seen in other chunks, indicating unusual activity or stuck reporting.\"\n  ]\n}\n\n## Investigator\n```json\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Kitchen sensors are functioning normally, reporting stable temperature readings consistent with the rest of the house during a cooling trend.\",\n      \"evidence\": [\n        \"kitchen_temp_sensor reports values decreasing from 2331 to 2295 over time, similar to other rooms (e.g., living_room dropping from 2325 to 2297).\",\n        \"No explicit alarm triggers or 'TestInProgress' flags appear for the kitchen smoke alarm until a scheduled self-test at 18:45:00.\"\n      ],\n      \"weaknesses\": [\n        \"The magnitude of temperature fluctuation in the kitchen sensor appears slightly higher than neighbors at certain intervals (e.g., 2315 -> 2295 drop vs others), though this could be normal variance.\",\n        \"Does not account for the specific spike in event count noted in the triage output if that metric is derived from raw log frequency rather than just visible lines.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Kitchen temperature sensor exhibits data drift or instability, potentially indicating hardware degradation or calibration failure.\",\n      \"threat_type\": \"Sensor_Data_Drift\",\n      \"evidence\": [\n        \"Between 18:10 and 18:45, the kitchen sensor shows erratic jumps: 2315 -> 2310 -> 2308 -> 2315 -> 2310 -> 2295. While other sensors show smooth trends, the kitchen sensor oscillates more frequently within short windows.\",\n        \""}}
{"episode_id": "SQ1_FP_C_0085", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq1\\SQ1_FP_C_0085.json", "metadata": {"sq_type": "SQ1", "sq_name": "设备健康诊断", "variant": "FP", "layout_id": "C", "layout_name": "三室两厅 (3BR)", "profile_id": "family_with_children", "base_date": "2026-06-03T00:00:00", "seed": 20260714, "scenario_id": "DF-01", "total_events": 2307, "anomaly_events_count": 5}, "ground_truth": {"scenario_id": "DF-01-FP", "scenario_name": "DF-01-FP: 空调恒温控制导致温度稳定", "category": "device_fault", "is_anomaly": false, "threat_type": "none", "key_difference": "有微小波动（±0.2°C），不是完全固定值；且空调处于开启状态", "difficulty_score": 12, "difficulty_level": 3, "difficulty_label": "L3_composite_reasoning", "difficulty_dimensions": {"D1_evidence_count": 3, "D2_signal_directness": 3, "D3_cross_device": 1, "D4_temporal_span": 3, "D5_fp_similarity": 2}, "target_room": "living_room", "injection_time": "2026-06-03T08:18:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_drift\",\n  \"threat_description\": \"The living_room_temperature_sensor exhibits a continuous, non-physical linear drift from ~22.69°C to ~24.75°C over 6 hours despite the room being unoccupied and no external heat sources being active.\",\n  \"reasoning\": [\n    \"Data analysis reveals a deterministic upward trend in `living_room_temp_sensor` readings (e.g., 2269 at 00:00 to 2475 at 05:45), increasing by approximately 1 unit every 5-10 minutes.\",\n    \"This rate of change (~0.8°C per hour) is inconsistent with natural thermal inertia or ambient temperature fluctuations for a residential environment without an active heater.\",\n    \"The anomaly persists regardless of occupancy status (Occupancy=0 throughout the window) and diverges significantly from other room sensors which show erratic but non-linear patterns, isolating the fault to this specific device's firmware or calibration logic.\",\n    \"No 'OutOfRange' flags or error bits are present in the logs, suggesting the sensor is not detecting its own failure but rather misreporting values due to software drift.\"\n  ],\n  \"key_evidence\": [\n    \"[2026-06-03T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2269 vs [2026-06-03T05:45:00] ... = 2475\",\n    \"Continuous increase observed even when [2026-06-03T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0\"\n  ],\n  \"recommended_actions\": [\n    \"Re-calibrate or replace the living_room_temperature_sensor hardware immediately.\",\n    \"Inspect the sensor's firmware version and update if a known bug causes linear drift has been reported.\",\n    \"Cross-reference physical thermometer readings at the sensor location to confirm the data integrity issue.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_drift", "threat_description": "The living_room_temperature_sensor exhibits a continuous, non-physical linear drift from ~22.69°C to ~24.75°C over 6 hours despite the room being unoccupied and no external heat sources being active.", "reasoning": ["Data analysis reveals a deterministic upward trend in `living_room_temp_sensor` readings (e.g., 2269 at 00:00 to 2475 at 05:45), increasing by approximately 1 unit every 5-10 minutes.", "This rate of change (~0.8°C per hour) is inconsistent with natural thermal inertia or ambient temperature fluctuations for a residential environment without an active heater.", "The anomaly persists regardless of occupancy status (Occupancy=0 throughout the window) and diverges significantly from other room sensors which show erratic but non-linear patterns, isolating the fault to this specific device's firmware or calibration logic.", "No 'OutOfRange' flags or error bits are present in the logs, suggesting the sensor is not detecting its own failure but rather misreporting values due to software drift."], "key_evidence": ["[2026-06-03T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2269 vs [2026-06-03T05:45:00] ... = 2475", "Continuous increase observed even when [2026-06-03T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0"], "recommended_actions": ["Re-calibrate or replace the living_room_temperature_sensor hardware immediately.", "Inspect the sensor's firmware version and update if a known bug causes linear drift has been reported.", "Cross-reference physical thermometer readings at the sensor location to confirm the data integrity issue."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 56.646777391433716, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 2307, "chunk_count": 29, "signals": {"room_activity": {"living_room": 403, "master_bedroom": 520, "kids_room": 521, "kitchen": 303, "dining_room": 224, "second_bedroom": 48, "master_bathroom": 60, "entrance": 227, "second_bathroom": 1}, "attribute_frequency": {"MeasuredValue": 1160, "Occupancy": 1098, "OnOff": 27, "StateValue": 7, "LockState": 5, "CurrentPositionLiftPercent100ths": 3, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 5, "occupancy_events": 1098, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"device-health\",\n  \"focus_rooms\": [\"living_room\"],\n  \"focus_devices\": [\n    \"living_room_temperature_sensor\",\n    \"living_room_occupancy_sensor\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C00\",\n    \"C01\",\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C06\",\n    \"C07\",\n    \"C08\",\n    \"C09\",\n    \"C10\",\n    \"C11\",\n    \"C12\",\n    \"C13\",\n    \"C14\",\n    \"C15\",\n    \"C16\",\n    \"C17\",\n    \"C18\",\n    \"C19\",\n    \"C20\",\n    \"C21\",\n    \"C22\",\n    \"C23\",\n    \"C24\",\n    \"C25\",\n    \"C26\",\n    \"C27\",\n    \"C28\"\n  ],\n  \"suspected_patterns\": [\n    \"Temperature drift anomaly: Sensor readings start at ~22°C and linearly increase to >25°C over time, deviating from expected ambient stability.\",\n    \"Occupancy-temperature correlation failure: Temperature continues to rise even when occupancy sensor reports '0' (e.g., C00, C08, C15), suggesting the temperature reading may be erroneous or influenced by non-occupant factors not captured by the logic.\"\n  ],\n  \"why_these_chunks\": [\n    \"All chunks contain the target room's data.\",\n    \"Chunks C00-C04 show the initial baseline and the onset of significant temperature deviation.\",\n    \"Chunks C05-C12 illustrate the sustained drift despite varying occupancy states.\",\n    \"Chunks C13-C28 confirm the persistence of the anomaly throughout the observation window.\",\n    \"No specific event logs (alarms, lock flips) are visible in previews that would indicate an emergency; the primary signal is the deterministic trend in sensor values.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "device-health", "focus_rooms": ["living_room"], "focus_devices": ["living_room_temperature_sensor", "living_room_occupancy_sensor"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04", "C05", "C06", "C07", "C08", "C09", "C10", "C11", "C12", "C13", "C14", "C15", "C16", "C17", "C18", "C19", "C20", "C21", "C22", "C23", "C24", "C25", "C26", "C27", "C28"], "suspected_patterns": ["Temperature drift anomaly: Sensor readings start at ~22°C and linearly increase to >25°C over time, deviating from expected ambient stability.", "Occupancy-temperature correlation failure: Temperature continues to rise even when occupancy sensor reports '0' (e.g., C00, C08, C15), suggesting the temperature reading may be erroneous or influenced by non-occupant factors not captured by the logic."], "why_these_chunks": ["All chunks contain the target room's data.", "Chunks C00-C04 show the initial baseline and the onset of significant temperature deviation.", "Chunks C05-C12 illustrate the sustained drift despite varying occupancy states.", "Chunks C13-C28 confirm the persistence of the anomaly throughout the observation window.", "No specific event logs (alarms, lock flips) are visible in previews that would indicate an emergency; the primary signal is the deterministic trend in sensor values."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The living_room_temp_sensor is functioning correctly, reporting a gradual increase in ambient temperature due to external factors (e.g., sunrise heating the house) or internal heat gain before occupancy.\",\n      \"evidence\": [\"All sensors across all rooms show a consistent upward trend from ~22.7°C to ~24.8°C over the observation window.\", \"The reading at 00:00 (22.69) aligns with typical overnight indoor temperatures.\"],\n      \"weaknesses\": [\"The rate of increase (~2.0°C per hour) is significantly faster than typical passive thermal diffusion for a standard home without active heating.\", \"Other room sensors do not exhibit this exact synchronized drift pattern; some fluctuate differently, suggesting localized sensor issues rather than global environmental changes.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Hardware failure or calibration drift in the living_room_temp_sensor causing non-physical temperature readings.\",\n      \"threat_type\": \"Sensor Failure / Calibration Drift\",\n      \"evidence\": [\"Deterministic linear drift: Temperature rises steadily from 2269 to >2470 despite no occupancy events ('Occupancy = 0' for the entire duration).\", \"Magnitude anomaly: A rise of ~2 degrees Celsius in one hour is physically improbable for a static environment without an active heater.\", \"Correlation failure: The sensor continues to report rising values even when the occupancy sensor confirms the room is empty, ruling out human body heat as the cause.\", \"Inconsistency: Kitchen and other room sensors show different fluctuation patterns, isolating the anomaly to specific sensors rather than a network-wide issue.\"]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Data logging corruption or unit conversion error in the living_room_temp_sensor data stream.\",\n      \"threat_type\": \"Data Integrity Issue\",\n      \"evidence\": [\"The raw values (e.g., 2269, 2355) are integers that lack decimal precision often found in real-world temperature logs, though they could represent milli-degrees.\", \"If these were milli-degrees, the range would be 22.69°C to 24.70°C, which is plausible. However, if the system interprets them as whole degrees (or if the log format implies a fault), the jump is anomalous.\", \"No alarm flags or 'OutOfRange' states are triggered in the logs despite values exceeding typical comfort ranges if interpreted as single digits.\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The strict correlation between 'Occupancy = 0' and the continuous, rapid rise in temperature suggests the source of the heat signal is not biological but instrumental or erroneous.\",\n    \"The divergence between the living_room sensor trend and the more erratic trends of master_bedroom and kitchen sensors indicates a localized device fault rather than a global HVAC event.\"\n  ],\n  \"missing_information\": [\n    \"Raw binary logs or manufacturer-specific diagnostic status bits to confirm if the sensor reports 'calibration error' or 'battery low'.\",\n    \"Historical baseline data from previous days to determine if this linear drift is a recurring pattern or a new onset.\",\n    \"Physical location of the sensor relative to potential external heat sources (windows, exterior walls) to rule out solar gain during the observed hours.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The living_room_temp_sensor is functioning correctly, reporting a gradual increase in ambient temperature due to external factors (e.g., sunrise heating the house) or internal heat gain before occupancy.", "evidence": ["All sensors across all rooms show a consistent upward trend from ~22.7°C to ~24.8°C over the observation window.", "The reading at 00:00 (22.69) aligns with typical overnight indoor temperatures."], "weaknesses": ["The rate of increase (~2.0°C per hour) is significantly faster than typical passive thermal diffusion for a standard home without active heating.", "Other room sensors do not exhibit this exact synchronized drift pattern; some fluctuate differently, suggesting localized sensor issues rather than global environmental changes."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Hardware failure or calibration drift in the living_room_temp_sensor causing non-physical temperature readings.", "threat_type": "Sensor Failure / Calibration Drift", "evidence": ["Deterministic linear drift: Temperature rises steadily from 2269 to >2470 despite no occupancy events ('Occupancy = 0' for the entire duration).", "Magnitude anomaly: A rise of ~2 degrees Celsius in one hour is physically improbable for a static environment without an active heater.", "Correlation failure: The sensor continues to report rising values even when the occupancy sensor confirms the room is empty, ruling out human body heat as the cause.", "Inconsistency: Kitchen and other room sensors show different fluctuation patterns, isolating the anomaly to specific sensors rather than a network-wide issue."]}, {"id": "A2", "description": "Data logging corruption or unit conversion error in the living_room_temp_sensor data stream.", "threat_type": "Data Integrity Issue", "evidence": ["The raw values (e.g., 2269, 2355) are integers that lack decimal precision often found in real-world temperature logs, though they could represent milli-degrees.", "If these were milli-degrees, the range would be 22.69°C to 24.70°C, which is plausible. However, if the system interprets them as whole degrees (or if the log format implies a fault), the jump is anomalous.", "No alarm flags or 'OutOfRange' states are triggered in the logs despite values exceeding typical comfort ranges if interpreted as single digits."]}], "most_discriminative_evidence": ["The strict correlation between 'Occupancy = 0' and the continuous, rapid rise in temperature suggests the source of the heat signal is not biological but instrumental or erroneous.", "The divergence between the living_room sensor trend and the more erratic trends of master_bedroom and kitchen sensors indicates a localized device fault rather than a global HVAC event."], "missing_information": ["Raw binary logs or manufacturer-specific diagnostic status bits to confirm if the sensor reports 'calibration error' or 'battery low'.", "Historical baseline data from previous days to determine if this linear drift is a recurring pattern or a new onset.", "Physical location of the sensor relative to potential external heat sources (windows, exterior walls) to rule out solar gain during the observed hours."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [],\n  \"missing_checks\": [\n    \"Verify raw data units (check if values like 2269 represent milli-degrees or actual degrees) across all chunks.\",\n    \"Check for 'OutOfRange' flags or calibration error bits in the metadata of C00-C28.\",\n    \"Cross-reference with historical baseline data from previous days to distinguish between recurring drift and new failure.\"\n  ],\n  \"supervisor_notes\": [\n    \"The investigation is currently on-topic and has correctly identified a potential sensor anomaly based on the provided chunks.\",\n    \"However, the evidence regarding the 'Data logging corruption or unit conversion error' hypothesis (A2) remains theoretical. The Investigator Output notes that raw values lack decimal precision, but without examining specific chunks to confirm the log format interpretation, this cannot be ruled out as the primary cause.\",\n    \"The current chunk selection covers the full observation window, so no additional time-series chunks are needed. Instead, deeper inspection of the existing chunks' metadata and cross-referencing with external historical data is required.\",\n    \"Before finalizing the diagnosis, it is crucial to rule out the data integrity issue before concluding hardware failure.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": [], "missing_checks": ["Verify raw data units (check if values like 2269 represent milli-degrees or actual degrees) across all chunks.", "Check for 'OutOfRange' flags or calibration error bits in the metadata of C00-C28.", "Cross-reference with historical baseline data from previous days to distinguish between recurring drift and new failure."], "supervisor_notes": ["The investigation is currently on-topic and has correctly identified a potential sensor anomaly based on the provided chunks.", "However, the evidence regarding the 'Data logging corruption or unit conversion error' hypothesis (A2) remains theoretical. The Investigator Output notes that raw values lack decimal precision, but without examining specific chunks to confirm the log format interpretation, this cannot be ruled out as the primary cause.", "The current chunk selection covers the full observation window, so no additional time-series chunks are needed. Instead, deeper inspection of the existing chunks' metadata and cross-referencing with external historical data is required.", "Before finalizing the diagnosis, it is crucial to rule out the data integrity issue before concluding hardware failure."]}, "preview_triage_prompt": "## Query\n请检查以下设备状态历史，判断 living_room 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Layout\nLayout: 三室两厅 (3BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kids_room: 儿童房温度传感器<temperature_sensor>, 儿童房灯<dimmable_light>, 儿童房窗帘<window_covering>, 儿童房窗户传感器<contact_sensor>, 儿童房运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅副灯<dimmable_light>, 客厅氛围灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘1<window_covering>, 客厅窗户传感器1<contact_sensor>, 客厅窗户传感器2<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n- master_bathroom: 主卫漏水传感器<water_leak_detector>, 主卫灯<onoff_light>, 主卫运动传感器<occupancy_sensor>\n- master_bedroom: 主卧床头灯<onoff_light>, 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>\n- second_bedroom: 次卧灯<dimmable_light>, 次卧空调<air_conditioner>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 403,\n    \"master_bedroom\": 520,\n    \"kids_room\": 521,\n    \"kitchen\": 303,\n    \"dining_room\": 224,\n    \"second_bedroom\": 48,\n    \"master_bathroom\": 60,\n    \"entrance\": 227,\n    \"second_bathroom\": 1\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1160,\n    \"Occupancy\": 1098,\n    \"OnOff\": 27,\n    \"StateValue\": 7,\n    \"LockState\": 5,\n    \"CurrentPositionLiftPercent100ths\": 3,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 5,\n  \"occupancy_events\": 1098,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-03T00:00:00\",\n    \"end_ts\": \"2026-06-03T01:10:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 18,\n      \"master_bedroom\": 18,\n      \"kids_room\": 18,\n      \"kitchen\": 14,\n      \"dining_room\": 3,\n      \"second_bedroom\": 3,\n      \"master_bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"kids_room_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_oc", "preview_verifier_prompt": "## Query\n请检查以下设备状态历史，判断 living_room 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Triage\n{\n  \"latent_task_profile\": \"device-health\",\n  \"focus_rooms\": [\"living_room\"],\n  \"focus_devices\": [\n    \"living_room_temperature_sensor\",\n    \"living_room_occupancy_sensor\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C00\",\n    \"C01\",\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C06\",\n    \"C07\",\n    \"C08\",\n    \"C09\",\n    \"C10\",\n    \"C11\",\n    \"C12\",\n    \"C13\",\n    \"C14\",\n    \"C15\",\n    \"C16\",\n    \"C17\",\n    \"C18\",\n    \"C19\",\n    \"C20\",\n    \"C21\",\n    \"C22\",\n    \"C23\",\n    \"C24\",\n    \"C25\",\n    \"C26\",\n    \"C27\",\n    \"C28\"\n  ],\n  \"suspected_patterns\": [\n    \"Temperature drift anomaly: Sensor readings start at ~22°C and linearly increase to >25°C over time, deviating from expected ambient stability.\",\n    \"Occupancy-temperature correlation failure: Temperature continues to rise even when occupancy sensor reports '0' (e.g., C00, C08, C15), suggesting the temperature reading may be erroneous or influenced by non-occupant factors not captured by the logic.\"\n  ],\n  \"why_these_chunks\": [\n    \"All chunks contain the target room's data.\",\n    \"Chunks C00-C04 show the initial baseline and the onset of significant temperature deviation.\",\n    \"Chunks C05-C12 illustrate the sustained drift despite varying occupancy states.\",\n    \"Chunks C13-C28 confirm the persistence of the anomaly throughout the observation window.\",\n    \"No specific event logs (alarms, lock flips) are visible in previews that would indicate an emergency; the primary signal is the deterministic trend in sensor values.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The living_room_temp_sensor is functioning correctly, reporting a gradual increase in ambient temperature due to external factors (e.g., sunrise heating the house) or internal heat gain before occupancy.\",\n      \"evidence\": [\"All sensors across all rooms show a consistent upward trend from ~22.7°C to ~24.8°C over the observation window.\", \"The reading at 00:00 (22.69) aligns with typical overnight indoor temperatures.\"],\n      \"weaknesses\": [\"The rate of increase (~2.0°C per hour) is significantly faster than typical passive thermal diffusion for a standard home without active heating.\", \"Other room sensors do not exhibit this exact synchronized drift pattern; some fluctuate differently, suggesting localized sensor issues rather than global environmental changes.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\""}}
{"episode_id": "SQ1_FP_A_0083", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq1\\SQ1_FP_A_0083.json", "metadata": {"sq_type": "SQ1", "sq_name": "设备健康诊断", "variant": "FP", "layout_id": "A", "layout_name": "一室一厅 (Studio/1BR)", "profile_id": "young_professional", "base_date": "2026-06-09T00:00:00", "seed": 20260712, "scenario_id": "DF-02", "total_events": 1131, "anomaly_events_count": 5}, "ground_truth": {"scenario_id": "DF-02-FP", "scenario_name": "DF-02-FP: 夏季午后持续升温（正常日照效应）", "category": "device_fault", "is_anomaly": false, "threat_type": "none", "key_difference": "温度上升后在午后到达峰值并回落，符合日间正弦曲线；而真正的漂移是不回落的单向偏移", "difficulty_score": 13, "difficulty_level": 3, "difficulty_label": "L3_composite_reasoning", "difficulty_dimensions": {"D1_evidence_count": 3, "D2_signal_directness": 3, "D3_cross_device": 1, "D4_temporal_span": 3, "D5_fp_similarity": 3}, "target_room": "living_room", "injection_time": "2026-06-09T14:24:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"The living room occupancy sensor is malfunctioning and stuck reporting '0' (empty) despite the house being active, while temperature data shows a likely unit/formatting discrepancy but remains physically plausible when corrected.\",\n  \"reasoning\": [\n      \"The living_room_occupancy sensor consistently reports a value of 0 across all provided chunks (C00-C06), spanning over 12 hours of continuous monitoring.\",\n      \"This reading contradicts observed activity in other rooms (e.g., bedroom lights turning on, bathroom occupancy changing to 1, door locks operating), indicating the living room was not actually empty or the sensor failed to detect presence.\",\n      \"The temperature readings (e.g., 2267) are significantly higher than typical Celsius values, suggesting a unit mismatch (likely millidegrees) or missing decimal point, but the trend relative to other rooms remains stable, making this a data formatting issue rather than a critical hardware failure compared to the stuck occupancy sensor.\"\n    ],\n  \"key_evidence\": [\n      \"Timestamped logs from C03 show bedroom_occupancy switching to 1 at 06:19:00 and 06:24:00, while living_room_occupancy remains 0 simultaneously.\",\n      \"Every single occupancy log entry for living_room_temp_sensor's companion device (living_room_occupancy) in chunks C00 through C06 reads exactly 'OccupancySensing.Occupancy = 0'.\"\n    ],\n  \"recommended_actions\": [\n      \"Inspect the living room occupancy sensor hardware and its power supply/circuit connection immediately.\",\n      \"Verify sensor placement to ensure it is not obstructed by furniture or positioned in a dead zone, though the persistent '0' suggests a hard fault.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "The living room occupancy sensor is malfunctioning and stuck reporting '0' (empty) despite the house being active, while temperature data shows a likely unit/formatting discrepancy but remains physically plausible when corrected.", "reasoning": ["The living_room_occupancy sensor consistently reports a value of 0 across all provided chunks (C00-C06), spanning over 12 hours of continuous monitoring.", "This reading contradicts observed activity in other rooms (e.g., bedroom lights turning on, bathroom occupancy changing to 1, door locks operating), indicating the living room was not actually empty or the sensor failed to detect presence.", "The temperature readings (e.g., 2267) are significantly higher than typical Celsius values, suggesting a unit mismatch (likely millidegrees) or missing decimal point, but the trend relative to other rooms remains stable, making this a data formatting issue rather than a critical hardware failure compared to the stuck occupancy sensor."], "key_evidence": ["Timestamped logs from C03 show bedroom_occupancy switching to 1 at 06:19:00 and 06:24:00, while living_room_occupancy remains 0 simultaneously.", "Every single occupancy log entry for living_room_temp_sensor's companion device (living_room_occupancy) in chunks C00 through C06 reads exactly 'OccupancySensing.Occupancy = 0'."], "recommended_actions": ["Inspect the living room occupancy sensor hardware and its power supply/circuit connection immediately.", "Verify sensor placement to ensure it is not obstructed by furniture or positioned in a dead zone, though the persistent '0' suggests a hard fault."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 58.67842173576355, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1131, "chunk_count": 15, "signals": {"room_activity": {"living_room": 404, "bedroom": 357, "kitchen": 298, "bathroom": 58, "entrance": 14}, "attribute_frequency": {"MeasuredValue": 871, "Occupancy": 224, "OnOff": 18, "StateValue": 5, "LockState": 4, "CurrentPositionLiftPercent100ths": 2, "SystemMode": 1, "OperationalState": 1, "CurrentLevel": 1}, "lock_state_flips": 4, "occupancy_events": 224, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"device-health\",\n  \"focus_rooms\": [\"living_room\"],\n  \"focus_devices\": [\n    \"living_room_temp_sensor\",\n    \"living_room_occupancy\"\n  ],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\", \"C05\", \"C06\", \"C07\", \"C08\", \"C09\", \"C10\", \"C11\", \"C12\", \"C13\", \"C14\"],\n  \"suspected_patterns\": [\n    \"TemperatureOffsetAnomaly\",\n    \"SensorCalibrationDrift\",\n    \"OccupancyReportingGap\"\n  ],\n  \"why_these_chunks\": [\n    \"All chunks contain temperature readings for the living room that are scaled by a factor of 10 (e.g., 2267 vs expected ~22.6°C), indicating a potential firmware scaling error or unit mismatch.\",\n    \"The 'alarmish_count' is consistently high (12-29) per chunk despite no explicit alarm logs in previews, suggesting the system flags these anomalies automatically.\",\n    \"Occupancy events show frequent gaps where the sensor reports '0' even when other devices (lights/AC) are active, potentially indicating a dead zone or calibration issue.\",\n    \"Every single chunk must be inspected to determine if this is a global data transmission artifact or specific to the living room sensor hardware.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "device-health", "focus_rooms": ["living_room"], "focus_devices": ["living_room_temp_sensor", "living_room_occupancy"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04", "C05", "C06", "C07", "C08", "C09", "C10", "C11", "C12", "C13", "C14"], "suspected_patterns": ["TemperatureOffsetAnomaly", "SensorCalibrationDrift", "OccupancyReportingGap"], "why_these_chunks": ["All chunks contain temperature readings for the living room that are scaled by a factor of 10 (e.g., 2267 vs expected ~22.6°C), indicating a potential firmware scaling error or unit mismatch.", "The 'alarmish_count' is consistently high (12-29) per chunk despite no explicit alarm logs in previews, suggesting the system flags these anomalies automatically.", "Occupancy events show frequent gaps where the sensor reports '0' even when other devices (lights/AC) are active, potentially indicating a dead zone or calibration issue.", "Every single chunk must be inspected to determine if this is a global data transmission artifact or specific to the living room sensor hardware."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"All temperature sensors are functioning correctly, reporting raw integer values in millidegrees Celsius (°C * 1000) or a similar high-resolution internal unit.\",\n      \"evidence\": [\n        \"All room sensors report values in the range of 2100-2500, which is consistent across Living Room (~22-23°C), Bedroom (~21-24°C), and Kitchen (~22-25°C).\",\n        \"The relative temperature differences between rooms remain stable over time (e.g., Living Room consistently ~80 units higher than Bedroom), suggesting valid thermal gradients rather than sensor failure.\"\n      ],\n      \"weaknesses\": [\n        \"Standard HVAC and environmental sensors typically output decimals (e.g., 22.67), not integers ending in 00. A reading of '2267' is statistically unlikely for a standard °C*10 scale unless it represents millidegrees, which would be an unusually high resolution display format.\",\n        \"If the system expects degrees Celsius directly, every reported value is physically impossible (2267°C).\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Firmware scaling error or data transmission artifact: The living_room_temp_sensor (and others) are reporting temperature values scaled by a factor of 10 or 100 incorrectly, likely due to a configuration mismatch or firmware bug.\",\n      \"threat_type\": \"SensorCalibrationDrift / DataIntegrityError\",\n      \"evidence\": [\n        \"Raw values start at ~2267 and trend upwards to ~2543 over 8 hours. If interpreted as °C, this implies heating from 22.67°C to 25.43°C, which is physically plausible.\",\n        \"However, the Triage Output explicitly notes: 'All chunks contain temperature readings... scaled by a factor of 10 (e.g., 2267 vs expected ~22.6°C)' - wait, 2267/100 = 22.67. The triage suggests a factor of 10, but 2267/10 = 226.7°C which is fire. The most logical anomaly is that the value **2267** is actually meant to be **22.67**, implying a missing decimal point in the logging layer or a specific encoding where the last two digits are tenths/hundredths.\",\n        \"Crucially, the Living Room occupancy sensor reports `Occupancy = 0` continuously throughout all chunks (C00-C04), despite significant activity events occurring in other rooms (Bedroom light on, Door lock flipped, Bathroom occupancy active). This indicates a 'Dead Zone' or power/circuit issue specific to the living room occupancy detector.\"\n      ],\n      \"weaknesses\": [\n        \"Temperature trends are smooth and realistic if divided by 100, making the 'scaling error' less severe than a hard failure; it might just be a display/formatting issue.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Living Room Occupancy Sensor Failure / Dead Zone: The sensor is stuck at '0' (Empty) despite being in a highly active area during morning routines.\",\n      \"threat_type\": \"SensorMalfunction / FalseNegative\",\n      \"evidence\": [\n        \"Structured Signals show 'living_room': 404 (high activity count) while bedroom is 357, yet the log shows `living_room_occupancy | OccupancySensing.Occupancy = 0` at almost every timestamp.\",\n        \"Activity evidence in C03/C04: Bedroom lights turn on, bathroom occupancy fluctuates, door locks operate, yet the living room occupancy remains stubbornly 0.\",\n        \"In C03, timestamps like `06:19`, `06:24`, `06:29` show bedroom/bathroom activity, but no corresponding living room event triggers a state change to '1'.\"\n      ],\n      \"weaknesses\": [\n        \"It is possible the living room was genuinely empty while other parts of the house were used (e.g., everyone went to bed/lights off in LR while using kitchen/bath), though the high 'room_activity' score contradicts this slightly.\"\n      ]\n    }\n  ],\n  \"most_discinimative_evidence\": [\n    \"Discrepancy between high 'room_activity' metric (404) for living_room and continuous 'Occupancy=0' logs, indicating a sensor blind spot or failure.\",\n    \"Temperature values (e.g., 2267) appearing as integers with no decimal separator, requiring assumption of a hidden decimal point (22.67) or a unit multiplier to be physically sensible.\"\n  ],\n  \"missing_information\": [\n    \"Definition of the raw data unit: Is 2267 millidegrees Celsius, or is it a floating-point number truncated in the log?\",\n    \"History of the living_room_occupancy sensor prior to 2026-06-09T00:00:00 to determine if it has always been stuck at 0 or failed recently.\",\n    \"Location of living_room occupants if known via other systems (e.g., mobile phone GPS, wearable tags) to confirm if the sensor is truly failing to detect presence.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "All temperature sensors are functioning correctly, reporting raw integer values in millidegrees Celsius (°C * 1000) or a similar high-resolution internal unit.", "evidence": ["All room sensors report values in the range of 2100-2500, which is consistent across Living Room (~22-23°C), Bedroom (~21-24°C), and Kitchen (~22-25°C).", "The relative temperature differences between rooms remain stable over time (e.g., Living Room consistently ~80 units higher than Bedroom), suggesting valid thermal gradients rather than sensor failure."], "weaknesses": ["Standard HVAC and environmental sensors typically output decimals (e.g., 22.67), not integers ending in 00. A reading of '2267' is statistically unlikely for a standard °C*10 scale unless it represents millidegrees, which would be an unusually high resolution display format.", "If the system expects degrees Celsius directly, every reported value is physically impossible (2267°C)."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Firmware scaling error or data transmission artifact: The living_room_temp_sensor (and others) are reporting temperature values scaled by a factor of 10 or 100 incorrectly, likely due to a configuration mismatch or firmware bug.", "threat_type": "SensorCalibrationDrift / DataIntegrityError", "evidence": ["Raw values start at ~2267 and trend upwards to ~2543 over 8 hours. If interpreted as °C, this implies heating from 22.67°C to 25.43°C, which is physically plausible.", "However, the Triage Output explicitly notes: 'All chunks contain temperature readings... scaled by a factor of 10 (e.g., 2267 vs expected ~22.6°C)' - wait, 2267/100 = 22.67. The triage suggests a factor of 10, but 2267/10 = 226.7°C which is fire. The most logical anomaly is that the value **2267** is actually meant to be **22.67**, implying a missing decimal point in the logging layer or a specific encoding where the last two digits are tenths/hundredths.", "Crucially, the Living Room occupancy sensor reports `Occupancy = 0` continuously throughout all chunks (C00-C04), despite significant activity events occurring in other rooms (Bedroom light on, Door lock flipped, Bathroom occupancy active). This indicates a 'Dead Zone' or power/circuit issue specific to the living room occupancy detector."], "weaknesses": ["Temperature trends are smooth and realistic if divided by 100, making the 'scaling error' less severe than a hard failure; it might just be a display/formatting issue."]}, {"id": "A2", "description": "Living Room Occupancy Sensor Failure / Dead Zone: The sensor is stuck at '0' (Empty) despite being in a highly active area during morning routines.", "threat_type": "SensorMalfunction / FalseNegative", "evidence": ["Structured Signals show 'living_room': 404 (high activity count) while bedroom is 357, yet the log shows `living_room_occupancy | OccupancySensing.Occupancy = 0` at almost every timestamp.", "Activity evidence in C03/C04: Bedroom lights turn on, bathroom occupancy fluctuates, door locks operate, yet the living room occupancy remains stubbornly 0.", "In C03, timestamps like `06:19`, `06:24`, `06:29` show bedroom/bathroom activity, but no corresponding living room event triggers a state change to '1'."], "weaknesses": ["It is possible the living room was genuinely empty while other parts of the house were used (e.g., everyone went to bed/lights off in LR while using kitchen/bath), though the high 'room_activity' score contradicts this slightly."]}], "most_discinimative_evidence": ["Discrepancy between high 'room_activity' metric (404) for living_room and continuous 'Occupancy=0' logs, indicating a sensor blind spot or failure.", "Temperature values (e.g., 2267) appearing as integers with no decimal separator, requiring assumption of a hidden decimal point (22.67) or a unit multiplier to be physically sensible."], "missing_information": ["Definition of the raw data unit: Is 2267 millidegrees Celsius, or is it a floating-point number truncated in the log?", "History of the living_room_occupancy sensor prior to 2026-06-09T00:00:00 to determine if it has always been stuck at 0 or failed recently.", "Location of living_room occupants if known via other systems (e.g., mobile phone GPS, wearable tags) to confirm if the sensor is truly failing to detect presence."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C05\", \"C14\"],\n  \"missing_checks\": [\n    \"Verify if the temperature scaling issue (2267) is consistent across ALL chunks or specific to early/late periods.\",\n    \"Check C05 and C14 to confirm if the 'Occupancy=0' anomaly persists at the end of the monitoring window (to rule out intermittent failure vs permanent stuck state).\",\n    \"Cross-reference with alarm logs in missing chunks to verify the 'high alarmish_count' mentioned in Triage.\"\n  ],\n  \"supervisor_notes\": [\n    \"The Investigator correctly identified the two main anomalies: potential data formatting/scaling for temperature and a dead sensor for occupancy.\",\n    \"However, the analysis relies heavily on chunks C00-C04. We need to inspect the tail of the dataset (C14) and middle sections (C05+) to determine if these are transient glitches or systemic hardware failures.\",\n    \"Specifically, checking C14 is crucial to see if the occupancy sensor ever recovers or if it remains stuck at 0 until the very end of the log period.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C05", "C14"], "missing_checks": ["Verify if the temperature scaling issue (2267) is consistent across ALL chunks or specific to early/late periods.", "Check C05 and C14 to confirm if the 'Occupancy=0' anomaly persists at the end of the monitoring window (to rule out intermittent failure vs permanent stuck state).", "Cross-reference with alarm logs in missing chunks to verify the 'high alarmish_count' mentioned in Triage."], "supervisor_notes": ["The Investigator correctly identified the two main anomalies: potential data formatting/scaling for temperature and a dead sensor for occupancy.", "However, the analysis relies heavily on chunks C00-C04. We need to inspect the tail of the dataset (C14) and middle sections (C05+) to determine if these are transient glitches or systemic hardware failures.", "Specifically, checking C14 is crucial to see if the occupancy sensor ever recovers or if it remains stuck at 0 until the very end of the log period."]}, "preview_triage_prompt": "## Query\n请检查以下设备状态历史，判断 living_room 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Layout\nLayout: 一室一厅 (Studio/1BR)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅台灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 404,\n    \"bedroom\": 357,\n    \"kitchen\": 298,\n    \"bathroom\": 58,\n    \"entrance\": 14\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 871,\n    \"Occupancy\": 224,\n    \"OnOff\": 18,\n    \"StateValue\": 5,\n    \"LockState\": 4,\n    \"CurrentPositionLiftPercent100ths\": 2,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 224,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-09T00:00:00\",\n    \"end_ts\": \"2026-06-09T01:50:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 27,\n      \"bedroom\": 27,\n      \"kitchen\": 22,\n      \"bathroom\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"bathroom_occupancy\"\n    ],\n    \"alarmish_count\": 12,\n    \"preview_lines\": [\n      \"[2026-06-09T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2267\",\n      \"[2026-06-09T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2177\",\n      \"[2026-06-09T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2280\",\n      \"[2026-06-09T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-09T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-09T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-09T00:05:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2262\",\n      \"[2026-06-09T00:05:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2168\",\n      \"[2026-06-09T00:05:00] kitche", "preview_verifier_prompt": "## Query\n请检查以下设备状态历史，判断 living_room 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Triage\n{\n  \"latent_task_profile\": \"device-health\",\n  \"focus_rooms\": [\"living_room\"],\n  \"focus_devices\": [\n    \"living_room_temp_sensor\",\n    \"living_room_occupancy\"\n  ],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\", \"C05\", \"C06\", \"C07\", \"C08\", \"C09\", \"C10\", \"C11\", \"C12\", \"C13\", \"C14\"],\n  \"suspected_patterns\": [\n    \"TemperatureOffsetAnomaly\",\n    \"SensorCalibrationDrift\",\n    \"OccupancyReportingGap\"\n  ],\n  \"why_these_chunks\": [\n    \"All chunks contain temperature readings for the living room that are scaled by a factor of 10 (e.g., 2267 vs expected ~22.6°C), indicating a potential firmware scaling error or unit mismatch.\",\n    \"The 'alarmish_count' is consistently high (12-29) per chunk despite no explicit alarm logs in previews, suggesting the system flags these anomalies automatically.\",\n    \"Occupancy events show frequent gaps where the sensor reports '0' even when other devices (lights/AC) are active, potentially indicating a dead zone or calibration issue.\",\n    \"Every single chunk must be inspected to determine if this is a global data transmission artifact or specific to the living room sensor hardware.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"All temperature sensors are functioning correctly, reporting raw integer values in millidegrees Celsius (°C * 1000) or a similar high-resolution internal unit.\",\n      \"evidence\": [\n        \"All room sensors report values in the range of 2100-2500, which is consistent across Living Room (~22-23°C), Bedroom (~21-24°C), and Kitchen (~22-25°C).\",\n        \"The relative temperature differences between rooms remain stable over time (e.g., Living Room consistently ~80 units higher than Bedroom), suggesting valid thermal gradients rather than sensor failure.\"\n      ],\n      \"weaknesses\": [\n        \"Standard HVAC and environmental sensors typically output decimals (e.g., 22.67), not integers ending in 00. A reading of '2267' is statistically unlikely for a standard °C*10 scale unless it represents millidegrees, which would be an unusually high resolution display format.\",\n        \"If the system expects degrees Celsius directly, every reported value is physically impossible (2267°C).\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Firmware scaling error or data transmission artifact: The living_room_temp_sensor (and others) are reporting tem"}}
{"episode_id": "SQ1_TP_A_0004", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq1\\SQ1_TP_A_0004.json", "metadata": {"sq_type": "SQ1", "sq_name": "设备健康诊断", "variant": "TP", "layout_id": "A", "layout_name": "一室一厅 (Studio/1BR)", "profile_id": "young_professional", "base_date": "2026-06-19T00:00:00", "seed": 20260633, "scenario_id": "DF-06", "total_events": 1129, "anomaly_events_count": 5}, "ground_truth": {"scenario_id": "DF-06", "scenario_name": "窗帘电机卡住", "category": "device_fault", "is_anomaly": true, "threat_type": "actuator_stuck", "key_evidence": ["OperationalStatus 显示正在移动（closing）", "但 CurrentPositionLiftPercent100ths 数值长时间不变", "状态 vs 实际位置不一致"], "expected_response": "", "difficulty_score": 9, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 1, "D4_temporal_span": 2, "D5_fp_similarity": 2}, "target_room": "bedroom", "injection_time": "2026-06-19T18:00:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_drift\",\n  \"threat_description\": \"The bedroom temperature sensor exhibits a persistent and significant calibration offset (~10°C) compared to adjacent rooms, indicating measurement inaccuracy rather than environmental factors.\",\n  \"reasoning\": [\n    \"Analysis of C00 through C06 reveals that while all rooms are unoccupied for extended periods (e.g., C00-C02), the living room and kitchen temperatures rise from ~2265 to ~2460 (an increase of ~195 units), whereas the bedroom temperature only rises from ~2172 to ~2360 (an increase of ~188 units).\",\n    \"The absolute difference between the bedroom sensor and the living room/kitchen sensors remains remarkably constant at approximately 100-110 units throughout the entire monitoring period, regardless of occupancy changes or thermal dynamics.\",\n    \"This consistent delta strongly suggests a hardware calibration error or scale factor mismatch in the bedroom sensor's firmware or hardware, as natural thermal gradients would not maintain such a precise, static offset over 12+ hours of varying ambient conditions.\"\n  ],\n  \"key_evidence\": [\n    \"At 00:00:00 (C00): Living Room=2265, Bedroom=2172 (Delta=93)\",\n    \"At 05:35:00 (C02): Living Room=2464, Bedroom=2363 (Delta=101)\",\n    \"At 08:55:00 (C05): Living Room=2547, Bedroom=2440 (Delta=107)\"\n  ],\n  \"recommended_actions\": [\n    \"Calibrate the bedroom temperature sensor against a known reference or the readings from the living room/kitchen sensors.\",\n    \"Check the sensor installation location to ensure it is not affected by localized heat sources or drafts that could cause a permanent bias, though the consistency points to calibration.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_drift", "threat_description": "The bedroom temperature sensor exhibits a persistent and significant calibration offset (~10°C) compared to adjacent rooms, indicating measurement inaccuracy rather than environmental factors.", "reasoning": ["Analysis of C00 through C06 reveals that while all rooms are unoccupied for extended periods (e.g., C00-C02), the living room and kitchen temperatures rise from ~2265 to ~2460 (an increase of ~195 units), whereas the bedroom temperature only rises from ~2172 to ~2360 (an increase of ~188 units).", "The absolute difference between the bedroom sensor and the living room/kitchen sensors remains remarkably constant at approximately 100-110 units throughout the entire monitoring period, regardless of occupancy changes or thermal dynamics.", "This consistent delta strongly suggests a hardware calibration error or scale factor mismatch in the bedroom sensor's firmware or hardware, as natural thermal gradients would not maintain such a precise, static offset over 12+ hours of varying ambient conditions."], "key_evidence": ["At 00:00:00 (C00): Living Room=2265, Bedroom=2172 (Delta=93)", "At 05:35:00 (C02): Living Room=2464, Bedroom=2363 (Delta=101)", "At 08:55:00 (C05): Living Room=2547, Bedroom=2440 (Delta=107)"], "recommended_actions": ["Calibrate the bedroom temperature sensor against a known reference or the readings from the living room/kitchen sensors.", "Check the sensor installation location to ensure it is not affected by localized heat sources or drafts that could cause a permanent bias, though the consistency points to calibration."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": true, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 70.05538535118103, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1129, "chunk_count": 15, "signals": {"room_activity": {"living_room": 401, "bedroom": 357, "kitchen": 298, "bathroom": 59, "entrance": 14}, "attribute_frequency": {"MeasuredValue": 866, "Occupancy": 222, "OnOff": 18, "StateValue": 5, "LockState": 4, "CurrentPositionLiftPercent100ths": 3, "OperationalStatus": 3, "SystemMode": 1, "OperationalState": 1, "CurrentLevel": 1}, "lock_state_flips": 4, "occupancy_events": 222, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"device-health\",\n  \"focus_rooms\": [\"bedroom\"],\n  \"focus_devices\": [\"bedroom_temp_sensor\", \"bedroom_occupancy\", \"bedroom_window\"],\n  \"focus_chunk_ids\": [\"C09\", \"C10\", \"C11\", \"C12\", \"C13\"],\n  \"suspected_patterns\": [\n    \"Temperature drift or calibration offset in bedroom sensor compared to other rooms\",\n    \"Occupancy sensor false negatives (reported empty while activity occurs)\",\n    \"Window contact sensor reporting open when likely closed\"\n  ],\n  \"why_these_chunks\": [\n    \"C09: First appearance of 'bedroom_window' events, potential correlation with temperature drops.\",\n    \"C10-C13: Contains critical anomalies including a 'None' value for kitchen sensor (system health indicator), specific window contact state changes, and occupancy reports that may conflict with room activity levels observed in layout analysis.\",\n    \"C12-C13: High alarm counts correlate with the suspected sensor issues in the bedroom context.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "device-health", "focus_rooms": ["bedroom"], "focus_devices": ["bedroom_temp_sensor", "bedroom_occupancy", "bedroom_window"], "focus_chunk_ids": ["C09", "C10", "C11", "C12", "C13"], "suspected_patterns": ["Temperature drift or calibration offset in bedroom sensor compared to other rooms", "Occupancy sensor false negatives (reported empty while activity occurs)", "Window contact sensor reporting open when likely closed"], "why_these_chunks": ["C09: First appearance of 'bedroom_window' events, potential correlation with temperature drops.", "C10-C13: Contains critical anomalies including a 'None' value for kitchen sensor (system health indicator), specific window contact state changes, and occupancy reports that may conflict with room activity levels observed in layout analysis.", "C12-C13: High alarm counts correlate with the suspected sensor issues in the bedroom context."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Bedroom sensors are functioning correctly, reporting a stable low temperature due to the room being unoccupied and insulated from external heat sources compared to the kitchen.\",\n      \"evidence\": [\n        \"Temperature values in bedroom (2142-2284) are consistently lower than living room (2245-2383) and kitchen (2247-2715), which is physically plausible for an unoccupied secondary room.\",\n        \"Bedroom occupancy sensor alternates between 0 and 1, matching events like lights turning on/off (C12: 'bedroom_light | OnOff.OnOff = True' at 21:59:26 coincides with occupancy=1).\",\n        \"No missing values ('None') reported for bedroom_temp_sensor or bedroom_occupancy throughout the entire log.\"\n      ],\n      \"weaknesses\": [\n        \"The absolute temperature difference (~6-10 degrees Celsius) between bedroom and living room is unusually large for typical residential insulation without active cooling/heating differences, suggesting potential calibration drift rather than just environmental isolation.\",\n        \"The window coverings were opened (position 10000) while occupancy was 1, yet no significant temperature rise relative to other rooms occurred, making the thermal dynamics slightly ambiguous.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Bedroom temperature sensor suffers from significant calibration offset or scale error, reading values ~6-10°C lower than adjacent living areas despite similar ambient conditions when occupied.\",\n      \"threat_type\": \"Measurement Inaccuracy / Calibration Drift\",\n      \"evidence\": [\n        \"Persistent Delta: Throughout C10-C13, when both living_room and bedroom are occupied (Occupancy=1), the bedroom temp remains ~2150-2170 while living room is ~2260-2280. Example C13 (22:25): BR=2150 vs LR=2258.\",\n        \"Scale Discrepancy: Bedroom readings (e.g., 2142 in C12) are suspiciously low for a standard Celsius reading; if these are raw millidegrees or scaled integers, they map to ~21.4°C, but the gap persists even when accounting for conversion factors if applied uniformly.\",\n        \"Lack of Convergence: When bedroom occupants enter (C12: 21:59:21 -> Occupancy=1), the temperature does not rise towards the living room baseline as expected from body heat, remaining flat at ~2150 while living room stabilizes higher.\"\n      ],\n      \"weaknesses\": [\n        \"If the house has distinct zones with HVAC setpoints (e.g., bedroom kept cool at night), the delta could be intentional. However, the AC in living room was turned OFF at 21:59:16, same time bedroom light turned ON, weakening the 'cooling zone' theory.\",\n        \"Without historical baseline data, it is difficult to confirm this is a new drift versus a permanent installation setting.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Bedroom occupancy sensor exhibits false negatives (stuck-at-zero behavior) during periods of confirmed human activity.\",\n      \"threat_type\": \"Sensor Failure / Logic Error\",\n      \"evidence\": [\n        \"Contradictory State in C12: At 21:59:26, 'bedroom_light' turns ON, and shortly after at 22:04:21 and 22:09:21, 'bedroom_occupancy' reports 1. However, immediately prior to lights turning on (21:59:21), occupancy jumped to 1, suggesting the sensor detected entry. But note C11->C12 transition: At 21:31:42 occupancy=0, then at 21:59:21 it becomes 1. This sequence seems consistent.\",\n        \"Re-evaluating A2 based on full log: The occupancy sensor actually behaves reasonably well in C12/C13 where it flips 0->1 upon light activation. The primary anomaly remains the temperature discrepancy. False negatives are less supported by the specific timestamps provided where light/occupancy correlate.\"\n      ],\n      \"weaknesses\": [\n        \"Upon closer inspection of C12/C13, the occupancy sensor accurately reflects the state change when lights turn on (21:59:26). The hypothesis that it is stuck at zero is weak because it does report 1s frequently. The primary issue is likely the temperature sensor accuracy.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"C12 & C13 Thermal Divergence: At timestamp 22:25:00, Living Room Temp = 2258°C (approx), Bedroom Temp = 2150°C (approx). Both rooms have Occupancy=1. If the home is heated/cooled centrally, the bedroom should track the living room much closer unless there is a massive HVAC failure or intentional override, which contradicts the simultaneous AC OFF event in the living room.\",\n    \"Missing Kitchen Data Context: While kitchen sensor goes 'None' at 18:51:00 and 19:41:00, the bedroom sensor never fails. This isolates the anomaly specifically to the measurement *value* range of the bedroom sensor rather than a complete communication drop.\"\n  ],\n  \"missing_information\": [\n    \"HVAC System Configuration: What are the target setpoints for the bedroom vs. living room? Is there a dedicated thermostat?\",\n    \"Historical Baseline: What were the bedroom temperatures at the start of the day or previous days to determine if the offset is new or chronic?\",\n    \"Unit Definition: Are the 'MeasuredValue' integers representing raw ADC counts, millidegrees Celsius, or actual degrees Celsius?\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Bedroom sensors are functioning correctly, reporting a stable low temperature due to the room being unoccupied and insulated from external heat sources compared to the kitchen.", "evidence": ["Temperature values in bedroom (2142-2284) are consistently lower than living room (2245-2383) and kitchen (2247-2715), which is physically plausible for an unoccupied secondary room.", "Bedroom occupancy sensor alternates between 0 and 1, matching events like lights turning on/off (C12: 'bedroom_light | OnOff.OnOff = True' at 21:59:26 coincides with occupancy=1).", "No missing values ('None') reported for bedroom_temp_sensor or bedroom_occupancy throughout the entire log."], "weaknesses": ["The absolute temperature difference (~6-10 degrees Celsius) between bedroom and living room is unusually large for typical residential insulation without active cooling/heating differences, suggesting potential calibration drift rather than just environmental isolation.", "The window coverings were opened (position 10000) while occupancy was 1, yet no significant temperature rise relative to other rooms occurred, making the thermal dynamics slightly ambiguous."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Bedroom temperature sensor suffers from significant calibration offset or scale error, reading values ~6-10°C lower than adjacent living areas despite similar ambient conditions when occupied.", "threat_type": "Measurement Inaccuracy / Calibration Drift", "evidence": ["Persistent Delta: Throughout C10-C13, when both living_room and bedroom are occupied (Occupancy=1), the bedroom temp remains ~2150-2170 while living room is ~2260-2280. Example C13 (22:25): BR=2150 vs LR=2258.", "Scale Discrepancy: Bedroom readings (e.g., 2142 in C12) are suspiciously low for a standard Celsius reading; if these are raw millidegrees or scaled integers, they map to ~21.4°C, but the gap persists even when accounting for conversion factors if applied uniformly.", "Lack of Convergence: When bedroom occupants enter (C12: 21:59:21 -> Occupancy=1), the temperature does not rise towards the living room baseline as expected from body heat, remaining flat at ~2150 while living room stabilizes higher."], "weaknesses": ["If the house has distinct zones with HVAC setpoints (e.g., bedroom kept cool at night), the delta could be intentional. However, the AC in living room was turned OFF at 21:59:16, same time bedroom light turned ON, weakening the 'cooling zone' theory.", "Without historical baseline data, it is difficult to confirm this is a new drift versus a permanent installation setting."]}, {"id": "A2", "description": "Bedroom occupancy sensor exhibits false negatives (stuck-at-zero behavior) during periods of confirmed human activity.", "threat_type": "Sensor Failure / Logic Error", "evidence": ["Contradictory State in C12: At 21:59:26, 'bedroom_light' turns ON, and shortly after at 22:04:21 and 22:09:21, 'bedroom_occupancy' reports 1. However, immediately prior to lights turning on (21:59:21), occupancy jumped to 1, suggesting the sensor detected entry. But note C11->C12 transition: At 21:31:42 occupancy=0, then at 21:59:21 it becomes 1. This sequence seems consistent.", "Re-evaluating A2 based on full log: The occupancy sensor actually behaves reasonably well in C12/C13 where it flips 0->1 upon light activation. The primary anomaly remains the temperature discrepancy. False negatives are less supported by the specific timestamps provided where light/occupancy correlate."], "weaknesses": ["Upon closer inspection of C12/C13, the occupancy sensor accurately reflects the state change when lights turn on (21:59:26). The hypothesis that it is stuck at zero is weak because it does report 1s frequently. The primary issue is likely the temperature sensor accuracy."]}], "most_discriminative_evidence": ["C12 & C13 Thermal Divergence: At timestamp 22:25:00, Living Room Temp = 2258°C (approx), Bedroom Temp = 2150°C (approx). Both rooms have Occupancy=1. If the home is heated/cooled centrally, the bedroom should track the living room much closer unless there is a massive HVAC failure or intentional override, which contradicts the simultaneous AC OFF event in the living room.", "Missing Kitchen Data Context: While kitchen sensor goes 'None' at 18:51:00 and 19:41:00, the bedroom sensor never fails. This isolates the anomaly specifically to the measurement *value* range of the bedroom sensor rather than a complete communication drop."], "missing_information": ["HVAC System Configuration: What are the target setpoints for the bedroom vs. living room? Is there a dedicated thermostat?", "Historical Baseline: What were the bedroom temperatures at the start of the day or previous days to determine if the offset is new or chronic?", "Unit Definition: Are the 'MeasuredValue' integers representing raw ADC counts, millidegrees Celsius, or actual degrees Celsius?"]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\", \"C05\", \"C06\", \"C07\", \"C08\", \"C14\"],\n  \"missing_checks\": [\n    \"Verify if the large temperature delta (~10°C) persists in unoccupied periods to rule out passive cooling/heating effects.\",\n    \"Check historical baseline data (earlier than C10) to determine if this is a new calibration drift or a chronic installation error.\",\n    \"Confirm sensor unit definitions (raw counts vs. scaled degrees) as mentioned in 'missing_information'.\",\n    \"Investigate HVAC zone settings and setpoints for the bedroom specifically.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identified the primary anomaly: a persistent ~10°C offset between the bedroom and living room sensors when both are occupied.\",\n    \"However, the evidence collection is insufficient because it relies heavily on chunks C10-C13. Without earlier chunks (C00-C09 excluding C09's window context), we cannot establish if this offset is new (drift) or chronic (installation error).\",\n    \"We also lack data from later chunks (C14) to see if the pattern continues or resolves.\",\n    \"Crucially, there is no evidence regarding the bedroom's HVAC status or setpoints in the selected chunks, which is necessary to validate the hypothesis that the low reading is intentional climate control rather than sensor failure.\",\n    \"The investigation of the occupancy sensor was premature; without full temporal coverage across the entire day, confirming false negatives requires more robust correlation with activity logs outside the specific C12/C13 window.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C00", "C01", "C02", "C03", "C04", "C05", "C06", "C07", "C08", "C14"], "missing_checks": ["Verify if the large temperature delta (~10°C) persists in unoccupied periods to rule out passive cooling/heating effects.", "Check historical baseline data (earlier than C10) to determine if this is a new calibration drift or a chronic installation error.", "Confirm sensor unit definitions (raw counts vs. scaled degrees) as mentioned in 'missing_information'.", "Investigate HVAC zone settings and setpoints for the bedroom specifically."], "supervisor_notes": ["The analysis correctly identified the primary anomaly: a persistent ~10°C offset between the bedroom and living room sensors when both are occupied.", "However, the evidence collection is insufficient because it relies heavily on chunks C10-C13. Without earlier chunks (C00-C09 excluding C09's window context), we cannot establish if this offset is new (drift) or chronic (installation error).", "We also lack data from later chunks (C14) to see if the pattern continues or resolves.", "Crucially, there is no evidence regarding the bedroom's HVAC status or setpoints in the selected chunks, which is necessary to validate the hypothesis that the low reading is intentional climate control rather than sensor failure.", "The investigation of the occupancy sensor was premature; without full temporal coverage across the entire day, confirming false negatives requires more robust correlation with activity logs outside the specific C12/C13 window."]}, "preview_triage_prompt": "## Query\n请检查以下设备状态历史，判断 bedroom 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Layout\nLayout: 一室一厅 (Studio/1BR)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅台灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 401,\n    \"bedroom\": 357,\n    \"kitchen\": 298,\n    \"bathroom\": 59,\n    \"entrance\": 14\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 866,\n    \"Occupancy\": 222,\n    \"OnOff\": 18,\n    \"StateValue\": 5,\n    \"LockState\": 4,\n    \"CurrentPositionLiftPercent100ths\": 3,\n    \"OperationalStatus\": 3,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 222,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-19T00:00:00\",\n    \"end_ts\": \"2026-06-19T01:50:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 27,\n      \"bedroom\": 27,\n      \"kitchen\": 22,\n      \"bathroom\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"bathroom_occupancy\"\n    ],\n    \"alarmish_count\": 12,\n    \"preview_lines\": [\n      \"[2026-06-19T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2265\",\n      \"[2026-06-19T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2172\",\n      \"[2026-06-19T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2264\",\n      \"[2026-06-19T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-19T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-19T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-19T00:05:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2265\",\n      \"[2026-06-19T00:05:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2169\",\n      \"[202", "preview_verifier_prompt": "## Query\n请检查以下设备状态历史，判断 bedroom 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Triage\n{\n  \"latent_task_profile\": \"device-health\",\n  \"focus_rooms\": [\"bedroom\"],\n  \"focus_devices\": [\"bedroom_temp_sensor\", \"bedroom_occupancy\", \"bedroom_window\"],\n  \"focus_chunk_ids\": [\"C09\", \"C10\", \"C11\", \"C12\", \"C13\"],\n  \"suspected_patterns\": [\n    \"Temperature drift or calibration offset in bedroom sensor compared to other rooms\",\n    \"Occupancy sensor false negatives (reported empty while activity occurs)\",\n    \"Window contact sensor reporting open when likely closed\"\n  ],\n  \"why_these_chunks\": [\n    \"C09: First appearance of 'bedroom_window' events, potential correlation with temperature drops.\",\n    \"C10-C13: Contains critical anomalies including a 'None' value for kitchen sensor (system health indicator), specific window contact state changes, and occupancy reports that may conflict with room activity levels observed in layout analysis.\",\n    \"C12-C13: High alarm counts correlate with the suspected sensor issues in the bedroom context.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Bedroom sensors are functioning correctly, reporting a stable low temperature due to the room being unoccupied and insulated from external heat sources compared to the kitchen.\",\n      \"evidence\": [\n        \"Temperature values in bedroom (2142-2284) are consistently lower than living room (2245-2383) and kitchen (2247-2715), which is physically plausible for an unoccupied secondary room.\",\n        \"Bedroom occupancy sensor alternates between 0 and 1, matching events like lights turning on/off (C12: 'bedroom_light | OnOff.OnOff = True' at 21:59:26 coincides with occupancy=1).\",\n        \"No missing values ('None') reported for bedroom_temp_sensor or bedroom_occupancy throughout the entire log.\"\n      ],\n      \"weaknesses\": [\n        \"The absolute temperature difference (~6-10 degrees Celsius) between bedroom and living room is unusually large for typical residential insulation without active cooling/heating differences, suggesting potential calibration drift rather than just environmental isolation.\",\n        \"The window coverings were opened (position 10000) while occupancy was 1, yet no significant temperature rise relative to other rooms occurred, making the thermal dynamics slightly ambiguous.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Bedroom temperature sensor suffers from significant calibration offset "}}
{"episode_id": "SQ1_TN_A_0135", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq1\\SQ1_TN_A_0135.json", "metadata": {"sq_type": "SQ1", "sq_name": "设备健康诊断", "variant": "TN", "layout_id": "A", "layout_name": "一室一厅 (Studio/1BR)", "profile_id": "young_professional", "base_date": "2026-06-07T00:00:00", "seed": 20260764, "scenario_id": null, "total_events": 1341, "anomaly_events_count": 0}, "ground_truth": {"scenario_id": "TN", "scenario_name": "Normal — no anomaly", "category": "none", "is_anomaly": false, "threat_type": "none", "variant": "TN", "difficulty_score": 0, "difficulty_level": 0, "difficulty_label": "TN_baseline", "difficulty_dimensions": {"D1_evidence_count": 0, "D2_signal_directness": 0, "D3_cross_device": 0, "D4_temporal_span": 0, "D5_fp_similarity": 0}}, "raw_response": "{\n  \"is_anomaly\": false,\n  \"confidence\": \"high\",\n  \"threat_type\": \"none\",\n  \"threat_description\": \"The bathroom occupancy sensor is functioning normally; the absence of 'Occupancy=1' events in later logs corresponds to periods when no one was using the bathroom, confirmed by normal activity patterns in C00-C04.\",\n  \"reasoning\": [\"Analysis of chunks C00 through C04 confirms the sensor reported 'Occupancy=0' consistently during hours of inactivity (00:00-09:10) and correctly transitioned to 'Occupancy=1' at 08:55 and 09:00 when users were active.\", \"In chunk C05, the sensor correctly detected presence ('Occupancy=1') from 08:55 until 09:22, after which it switched to '0'. This switch coincides with the light turning off at 09:18 and subsequent user movement out of the room's detection range, indicating proper state management rather than failure.\", \"Chunks C12 and C16 show the sensor reporting 'Occupancy=0', which aligns with the timeline suggesting the household had left or the bathroom was unused. The Triage hypothesis regarding system-wide data loss is refuted because the raw logs for `bathroom_occupancy` contain valid values throughout the entire period, unlike the `kitchen_temp_sensor` which shows multiple 'None' errors.\", \"The initial investigator concern about 'missing' Occupancy=1 events is resolved by recognizing that a lack of positive detections simply indicates an empty room, not a malfunctioning sensor.\"],\n  \"key_evidence\": [\"C05 Log: '2026-06-07T09:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 1' followed by '2026-06-07T09:22:00] bathroom_occupancy | OccupancySensing.Occupancy = 0', showing correct state transitions.\", \"C05 Log: Presence of '2026-06-07T09:19:10] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = None' proves sensor failures exist in the system but are isolated to the temperature sensor, not the occupancy sensor.\", \"C00-C04 Logs: Consistent pattern of 'Occupancy=0' during morning hours prior to 08:55, demonstrating the sensor successfully reports emptiness without generating false positives.\"],\n  \"recommended_actions\": [\"No immediate action required as the device is operating within expected parameters.\", \"Monitor the kitchen_temp_sensor separately due to its recurring 'None' readings which may indicate power or connectivity issues.\"]\n}", "model_response": {"is_anomaly": false, "confidence": "high", "threat_type": "none", "threat_description": "The bathroom occupancy sensor is functioning normally; the absence of 'Occupancy=1' events in later logs corresponds to periods when no one was using the bathroom, confirmed by normal activity patterns in C00-C04.", "reasoning": ["Analysis of chunks C00 through C04 confirms the sensor reported 'Occupancy=0' consistently during hours of inactivity (00:00-09:10) and correctly transitioned to 'Occupancy=1' at 08:55 and 09:00 when users were active.", "In chunk C05, the sensor correctly detected presence ('Occupancy=1') from 08:55 until 09:22, after which it switched to '0'. This switch coincides with the light turning off at 09:18 and subsequent user movement out of the room's detection range, indicating proper state management rather than failure.", "Chunks C12 and C16 show the sensor reporting 'Occupancy=0', which aligns with the timeline suggesting the household had left or the bathroom was unused. The Triage hypothesis regarding system-wide data loss is refuted because the raw logs for `bathroom_occupancy` contain valid values throughout the entire period, unlike the `kitchen_temp_sensor` which shows multiple 'None' errors.", "The initial investigator concern about 'missing' Occupancy=1 events is resolved by recognizing that a lack of positive detections simply indicates an empty room, not a malfunctioning sensor."], "key_evidence": ["C05 Log: '2026-06-07T09:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 1' followed by '2026-06-07T09:22:00] bathroom_occupancy | OccupancySensing.Occupancy = 0', showing correct state transitions.", "C05 Log: Presence of '2026-06-07T09:19:10] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = None' proves sensor failures exist in the system but are isolated to the temperature sensor, not the occupancy sensor.", "C00-C04 Logs: Consistent pattern of 'Occupancy=0' during morning hours prior to 08:55, demonstrating the sensor successfully reports emptiness without generating false positives."], "recommended_actions": ["No immediate action required as the device is operating within expected parameters.", "Monitor the kitchen_temp_sensor separately due to its recurring 'None' readings which may indicate power or connectivity issues."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "CORRECT_REJECT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": null, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 72.85187840461731, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1341, "chunk_count": 17, "signals": {"room_activity": {"living_room": 482, "bedroom": 493, "kitchen": 308, "bathroom": 55, "entrance": 3}, "attribute_frequency": {"MeasuredValue": 870, "Occupancy": 442, "OnOff": 18, "StateValue": 4, "CurrentPositionLiftPercent100ths": 3, "SystemMode": 1, "OperationalState": 1, "LockState": 1}, "lock_state_flips": 1, "occupancy_events": 442, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"device-health | single-event-safety\",\n  \"focus_rooms\": [\"bathroom\"],\n  \"focus_devices\": [\"bathroom_occupancy\", \"bathroom_light\", \"water_leak_detector\"],\n  \"focus_chunk_ids\": [\"C05\", \"C12\", \"C16\"],\n  \"suspected_patterns\": [\n    \"Sensor data loss (Null/None values)\",\n    \"Occupancy state inconsistency with activity logs\",\n    \"Light state mismatch with occupancy events\"\n  ],\n  \"why_these_chunks\": [\n    \"C05: Contains a critical 'MeasuredValue = None' event for kitchen_temp_sensor, indicating potential sensor communication failures or power issues that may affect the entire system's reliability. Also shows bathroom occupancy toggling to 1 while no other bathroom device activity is recorded.\",\n    \"C12: Shows 'kitchen_temp_sensor' returning 'None' again shortly after an event, reinforcing a pattern of sporadic sensor data loss.\",\n    \"C16: The final chunk has significantly fewer total events and low bathroom event count compared to previous chunks, suggesting possible network disconnection or device dormancy/death at the end of the log period.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "device-health | single-event-safety", "focus_rooms": ["bathroom"], "focus_devices": ["bathroom_occupancy", "bathroom_light", "water_leak_detector"], "focus_chunk_ids": ["C05", "C12", "C16"], "suspected_patterns": ["Sensor data loss (Null/None values)", "Occupancy state inconsistency with activity logs", "Light state mismatch with occupancy events"], "why_these_chunks": ["C05: Contains a critical 'MeasuredValue = None' event for kitchen_temp_sensor, indicating potential sensor communication failures or power issues that may affect the entire system's reliability. Also shows bathroom occupancy toggling to 1 while no other bathroom device activity is recorded.", "C12: Shows 'kitchen_temp_sensor' returning 'None' again shortly after an event, reinforcing a pattern of sporadic sensor data loss.", "C16: The final chunk has significantly fewer total events and low bathroom event count compared to previous chunks, suggesting possible network disconnection or device dormancy/death at the end of the log period."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Bathroom occupancy sensor is functioning correctly, accurately detecting presence and absence based on user activity patterns.\",\n      \"evidence\": [\"C05: Sensor reports Occupancy=1 at 09:10 and 09:15, then switches to 0 at 09:22 and 09:49, consistent with short usage intervals.\", \"C12: Sensor reports Occupancy=0 consistently between 18:19 and 18:49 during evening hours.\", \"C16: Sensor reports Occupancy=0 consistently between 23:19 and 23:49 during night hours.\"],\n      \"weaknesses\": [\"The sensor shows a single event of 'Occupancy=1' in C05 at the very beginning (09:10) without a preceding 'Occupancy=0' or duration data to confirm entry, though this could be a log start artifact.\"],\n      \"status\": \"Plausible but incomplete context\"\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Bathroom occupancy sensor exhibits intermittent communication failure or power loss, indicated by sporadic 'null' values or missing state transitions that contradict expected continuous monitoring.\",\n      \"threat_type\": \"Data Integrity Loss / Device Dormancy\",\n      \"evidence\": [\"Triage Output explicitly flags 'Sensor data loss (Null/None values)' as a suspected pattern. While the provided chunks show kitchen_temp_sensor returning 'None', the Triage system aggregates this as a system-wide reliability indicator affecting the bathroom focus device.\", \"C05: The bathroom occupancy state toggles from 1 to 0 at 09:22 and back to 0 at 09:49. If the sensor were fully functional, one might expect a stable '1' if someone was using the room, or a clear transition. However, the critical evidence lies in the *absence* of any 'Occupancy=1' events for the bathroom after 09:49 in C05, despite other rooms having frequent updates. This suggests the sensor may have stopped reporting (dormant) rather than just changing state.\", \"Comparison with other devices: Temperature sensors report values every ~5 minutes. Bathroom occupancy only reports specific state changes. The lack of 'Occupancy=1' readings in the later parts of C05 and C12/C16 (where activity logs show people in other rooms) suggests the sensor is either offline or dead silent, not just reporting 'empty'.\", \"Note: The raw chunks do not explicitly contain a string 'MeasuredValue = None' for the *bathroom_occupancy* sensor itself, only for kitchen_temp_sensor. The anomaly hypothesis relies on the Triage Output's assertion that these failures are linked or indicative of a broader issue affecting the bathroom device mentioned in the `focus_devices` list.\"],\n      \"weaknesses\": [\"The provided raw chunks (C05, C12, C16) do not explicitly display a 'null' or 'None' value for the `bathroom_occupancy` sensor; they only show it switching to 0. The strong evidence for 'data loss' comes from the `kitchen_temp_sensor` nulls and the Triage summary, requiring an inference that the bathroom sensor shares the same fate or has similar unlogged gaps.\", \"It is possible the bathroom was genuinely empty for long periods, making the lack of '1' events normal behavior, though the frequency of '0' events without corresponding '1' events in active periods suggests otherwise.\"],\n      \"status\": \"High Probability due to system-wide correlation\"\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Lighting control logic mismatch: The bathroom light turned OFF while the occupancy sensor still reported OCCUPIED, indicating a potential sensor-to-actuator lag or false positive occupancy detection.\",\n      \"threat_type\": \"Logic Inconsistency / False Positive\",\n      \"evidence\": [\"C05: At 09:18:00, `bathroom_light` reports `OnOff.OnOff = False`. Shortly before this, at 09:15:00 and 09:18:00 (just prior to the off command), `bathroom_occupancy` reported `OccupancySensing.Occupancy = 1`.\", \"In many smart home systems, lights turn ON when occupied and OFF when unoccupied. If the light turned OFF at 09:18 while occupancy was still 1 (or had just been 1 moments ago), it implies the light controller received a 'leave' signal before the occupancy sensor did, OR the occupancy sensor falsely detected presence causing the light to stay on longer than intended (though here it went off). More critically, if the light goes off, the system expects occupancy to go to 0. The sequence is tight, suggesting a race condition or misalignment.\", \"However, looking closer at C05: Light OFF at 09:18. Occupancy 1 at 09:15 and 09:18. Occupancy 0 at 09:22. This looks like a standard 'person leaves, light turns off manually or via timer, person walks out of range'. It is less definitive than A1.\"],\n      \"weaknesses\": [\"The timing (1 min gap between occupancy=1 and occupancy=0 after light off) is within acceptable human movement tolerance.\", \"No explicit 'Occupancy=1' reading exists *after* the light turns off in the log until 09:49 (which is 0), so we cannot prove a conflict easily.\"],\n      \"status\": \"Low Confidence - likely normal operational sequence\"\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The Triage Output's explicit identification of 'Sensor data loss (Null/None values)' and 'Network disconnection' as key issues, coupled with the high frequency of 'None' values in the kitchen sensor (a common failure mode often systemic) and the total absence of 'Occupancy=1' events for the bathroom in the latter half of the logs despite general household activity.\",\n    \"The discrepancy between the structured signal showing low bathroom activity (55 vs 482 living room) and the complete silence of the bathroom occupancy sensor in the detailed logs after the initial few entries in C05.\"\n  ],\n  \"missing_information\": [\n    \"Raw log data containing explicit 'Occupancy = None' or 'Occupancy = Error' events for the bathroom sensor to definitively confirm hardware failure versus software filtering.\",\n    \"Logs covering the period immediately following the last 'Occupancy=1' read to see if there is a prolonged gap before the next update.\",\n    \"Configuration settings for the bathroom light automation (delay timers, sensitivity) to rule out intentional behavior mimicking faults.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Bathroom occupancy sensor is functioning correctly, accurately detecting presence and absence based on user activity patterns.", "evidence": ["C05: Sensor reports Occupancy=1 at 09:10 and 09:15, then switches to 0 at 09:22 and 09:49, consistent with short usage intervals.", "C12: Sensor reports Occupancy=0 consistently between 18:19 and 18:49 during evening hours.", "C16: Sensor reports Occupancy=0 consistently between 23:19 and 23:49 during night hours."], "weaknesses": ["The sensor shows a single event of 'Occupancy=1' in C05 at the very beginning (09:10) without a preceding 'Occupancy=0' or duration data to confirm entry, though this could be a log start artifact."], "status": "Plausible but incomplete context"}], "anomaly_hypotheses": [{"id": "A1", "description": "Bathroom occupancy sensor exhibits intermittent communication failure or power loss, indicated by sporadic 'null' values or missing state transitions that contradict expected continuous monitoring.", "threat_type": "Data Integrity Loss / Device Dormancy", "evidence": ["Triage Output explicitly flags 'Sensor data loss (Null/None values)' as a suspected pattern. While the provided chunks show kitchen_temp_sensor returning 'None', the Triage system aggregates this as a system-wide reliability indicator affecting the bathroom focus device.", "C05: The bathroom occupancy state toggles from 1 to 0 at 09:22 and back to 0 at 09:49. If the sensor were fully functional, one might expect a stable '1' if someone was using the room, or a clear transition. However, the critical evidence lies in the *absence* of any 'Occupancy=1' events for the bathroom after 09:49 in C05, despite other rooms having frequent updates. This suggests the sensor may have stopped reporting (dormant) rather than just changing state.", "Comparison with other devices: Temperature sensors report values every ~5 minutes. Bathroom occupancy only reports specific state changes. The lack of 'Occupancy=1' readings in the later parts of C05 and C12/C16 (where activity logs show people in other rooms) suggests the sensor is either offline or dead silent, not just reporting 'empty'.", "Note: The raw chunks do not explicitly contain a string 'MeasuredValue = None' for the *bathroom_occupancy* sensor itself, only for kitchen_temp_sensor. The anomaly hypothesis relies on the Triage Output's assertion that these failures are linked or indicative of a broader issue affecting the bathroom device mentioned in the `focus_devices` list."], "weaknesses": ["The provided raw chunks (C05, C12, C16) do not explicitly display a 'null' or 'None' value for the `bathroom_occupancy` sensor; they only show it switching to 0. The strong evidence for 'data loss' comes from the `kitchen_temp_sensor` nulls and the Triage summary, requiring an inference that the bathroom sensor shares the same fate or has similar unlogged gaps.", "It is possible the bathroom was genuinely empty for long periods, making the lack of '1' events normal behavior, though the frequency of '0' events without corresponding '1' events in active periods suggests otherwise."], "status": "High Probability due to system-wide correlation"}, {"id": "A2", "description": "Lighting control logic mismatch: The bathroom light turned OFF while the occupancy sensor still reported OCCUPIED, indicating a potential sensor-to-actuator lag or false positive occupancy detection.", "threat_type": "Logic Inconsistency / False Positive", "evidence": ["C05: At 09:18:00, `bathroom_light` reports `OnOff.OnOff = False`. Shortly before this, at 09:15:00 and 09:18:00 (just prior to the off command), `bathroom_occupancy` reported `OccupancySensing.Occupancy = 1`.", "In many smart home systems, lights turn ON when occupied and OFF when unoccupied. If the light turned OFF at 09:18 while occupancy was still 1 (or had just been 1 moments ago), it implies the light controller received a 'leave' signal before the occupancy sensor did, OR the occupancy sensor falsely detected presence causing the light to stay on longer than intended (though here it went off). More critically, if the light goes off, the system expects occupancy to go to 0. The sequence is tight, suggesting a race condition or misalignment.", "However, looking closer at C05: Light OFF at 09:18. Occupancy 1 at 09:15 and 09:18. Occupancy 0 at 09:22. This looks like a standard 'person leaves, light turns off manually or via timer, person walks out of range'. It is less definitive than A1."], "weaknesses": ["The timing (1 min gap between occupancy=1 and occupancy=0 after light off) is within acceptable human movement tolerance.", "No explicit 'Occupancy=1' reading exists *after* the light turns off in the log until 09:49 (which is 0), so we cannot prove a conflict easily."], "status": "Low Confidence - likely normal operational sequence"}], "most_discriminative_evidence": ["The Triage Output's explicit identification of 'Sensor data loss (Null/None values)' and 'Network disconnection' as key issues, coupled with the high frequency of 'None' values in the kitchen sensor (a common failure mode often systemic) and the total absence of 'Occupancy=1' events for the bathroom in the latter half of the logs despite general household activity.", "The discrepancy between the structured signal showing low bathroom activity (55 vs 482 living room) and the complete silence of the bathroom occupancy sensor in the detailed logs after the initial few entries in C05."], "missing_information": ["Raw log data containing explicit 'Occupancy = None' or 'Occupancy = Error' events for the bathroom sensor to definitively confirm hardware failure versus software filtering.", "Logs covering the period immediately following the last 'Occupancy=1' read to see if there is a prolonged gap before the next update.", "Configuration settings for the bathroom light automation (delay timers, sensitivity) to rule out intentional behavior mimicking faults."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\"],\n  \"missing_checks\": [\n    \"Verify if 'Occupancy=1' events exist in earlier chunks (C00-C04) to establish a baseline of normal activity patterns before the potential failure window.\",\n    \"Check raw logs in all selected chunks for explicit 'MeasuredValue = None' or 'Error' strings specifically associated with 'bathroom_occupancy', not just kitchen_temp_sensor.\",\n    \"Analyze timestamp continuity between chunks C05 and C12 to rule out long gaps caused by log rotation rather than device dormancy.\"\n  ],\n  \"supervisor_notes\": [\n    \"The current investigation relies heavily on Triage output assumptions that kitchen sensor failures affect the bathroom sensor. This is an inference, not direct evidence.\",\n    \"Chunks C05, C12, and C16 are insufficient to determine the *start* or *end* of the anomaly. We need the beginning of the log (C00-C04) to see if the bathroom was working normally before stopping reporting at 09:49 in C05.\",\n    \"The absence of 'Occupancy=1' readings could be due to the room actually being empty for extended periods. Without seeing activity in the first few chunks, we cannot confirm a 'device death' vs 'room usage pattern'.\",\n    \"The investigator correctly identified missing explicit null values for the bathroom sensor; additional chunks must be examined to either find these errors or prove their absence throughout the entire timeline.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C00", "C01", "C02", "C03", "C04"], "missing_checks": ["Verify if 'Occupancy=1' events exist in earlier chunks (C00-C04) to establish a baseline of normal activity patterns before the potential failure window.", "Check raw logs in all selected chunks for explicit 'MeasuredValue = None' or 'Error' strings specifically associated with 'bathroom_occupancy', not just kitchen_temp_sensor.", "Analyze timestamp continuity between chunks C05 and C12 to rule out long gaps caused by log rotation rather than device dormancy."], "supervisor_notes": ["The current investigation relies heavily on Triage output assumptions that kitchen sensor failures affect the bathroom sensor. This is an inference, not direct evidence.", "Chunks C05, C12, and C16 are insufficient to determine the *start* or *end* of the anomaly. We need the beginning of the log (C00-C04) to see if the bathroom was working normally before stopping reporting at 09:49 in C05.", "The absence of 'Occupancy=1' readings could be due to the room actually being empty for extended periods. Without seeing activity in the first few chunks, we cannot confirm a 'device death' vs 'room usage pattern'.", "The investigator correctly identified missing explicit null values for the bathroom sensor; additional chunks must be examined to either find these errors or prove their absence throughout the entire timeline."]}, "preview_triage_prompt": "## Query\n请检查以下设备状态历史，判断 bathroom 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Layout\nLayout: 一室一厅 (Studio/1BR)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅台灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 482,\n    \"bedroom\": 493,\n    \"kitchen\": 308,\n    \"bathroom\": 55,\n    \"entrance\": 3\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 870,\n    \"Occupancy\": 442,\n    \"OnOff\": 18,\n    \"StateValue\": 4,\n    \"CurrentPositionLiftPercent100ths\": 3,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"LockState\": 1\n  },\n  \"lock_state_flips\": 1,\n  \"occupancy_events\": 442,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-07T00:00:00\",\n    \"end_ts\": \"2026-06-07T01:50:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 27,\n      \"bedroom\": 27,\n      \"kitchen\": 22,\n      \"bathroom\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"bathroom_occupancy\"\n    ],\n    \"alarmish_count\": 12,\n    \"preview_lines\": [\n      \"[2026-06-07T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2277\",\n      \"[2026-06-07T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2163\",\n      \"[2026-06-07T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2269\",\n      \"[2026-06-07T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-07T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-07T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-07T00:05:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2266\",\n      \"[2026-06-07T00:05:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2164\",\n      \"[2026-06-07T00:05:00] kitchen_temp_sensor | Temperature", "preview_verifier_prompt": "## Query\n请检查以下设备状态历史，判断 bathroom 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Triage\n{\n  \"latent_task_profile\": \"device-health | single-event-safety\",\n  \"focus_rooms\": [\"bathroom\"],\n  \"focus_devices\": [\"bathroom_occupancy\", \"bathroom_light\", \"water_leak_detector\"],\n  \"focus_chunk_ids\": [\"C05\", \"C12\", \"C16\"],\n  \"suspected_patterns\": [\n    \"Sensor data loss (Null/None values)\",\n    \"Occupancy state inconsistency with activity logs\",\n    \"Light state mismatch with occupancy events\"\n  ],\n  \"why_these_chunks\": [\n    \"C05: Contains a critical 'MeasuredValue = None' event for kitchen_temp_sensor, indicating potential sensor communication failures or power issues that may affect the entire system's reliability. Also shows bathroom occupancy toggling to 1 while no other bathroom device activity is recorded.\",\n    \"C12: Shows 'kitchen_temp_sensor' returning 'None' again shortly after an event, reinforcing a pattern of sporadic sensor data loss.\",\n    \"C16: The final chunk has significantly fewer total events and low bathroom event count compared to previous chunks, suggesting possible network disconnection or device dormancy/death at the end of the log period.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Bathroom occupancy sensor is functioning correctly, accurately detecting presence and absence based on user activity patterns.\",\n      \"evidence\": [\"C05: Sensor reports Occupancy=1 at 09:10 and 09:15, then switches to 0 at 09:22 and 09:49, consistent with short usage intervals.\", \"C12: Sensor reports Occupancy=0 consistently between 18:19 and 18:49 during evening hours.\", \"C16: Sensor reports Occupancy=0 consistently between 23:19 and 23:49 during night hours.\"],\n      \"weaknesses\": [\"The sensor shows a single event of 'Occupancy=1' in C05 at the very beginning (09:10) without a preceding 'Occupancy=0' or duration data to confirm entry, though this could be a log start artifact.\"],\n      \"status\": \"Plausible but incomplete context\"\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Bathroom occupancy sensor exhibits intermittent communication failure or power loss, indicated by sporadic 'null' values or missing state transitions that contradict expected continuous monitoring.\",\n      \"threat_type\": \"Data Integrity Loss / Device Dormancy\",\n      \"evidence\": [\"Triage Output explicitly flags 'Sensor data loss (Null/None values)' as a suspected pattern. While the provided chunks show kitchen_temp_"}}
{"episode_id": "SQ1_TP_A_0006", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq1\\SQ1_TP_A_0006.json", "metadata": {"sq_type": "SQ1", "sq_name": "设备健康诊断", "variant": "TP", "layout_id": "A", "layout_name": "一室一厅 (Studio/1BR)", "profile_id": "young_professional", "base_date": "2026-06-01T00:00:00", "seed": 20260635, "scenario_id": "DF-02", "total_events": 1132, "anomaly_events_count": 5}, "ground_truth": {"scenario_id": "DF-02", "scenario_name": "温度传感器读数漂移（drift）", "category": "device_fault", "is_anomaly": true, "threat_type": "sensor_drift", "key_evidence": ["温度读数持续单向偏移，不符合正常日间温度曲线", "其他传感器或空调自带温度显示不一致（如果可以交叉验证）"], "expected_response": "", "difficulty_score": 13, "difficulty_level": 3, "difficulty_label": "L3_composite_reasoning", "difficulty_dimensions": {"D1_evidence_count": 3, "D2_signal_directness": 3, "D3_cross_device": 1, "D4_temporal_span": 3, "D5_fp_similarity": 3}, "target_room": "living_room", "injection_time": "2026-06-01T00:08:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"The living_room_temp_sensor is experiencing intermittent hardware failure or communication loss, resulting in periodic null data readings at regular intervals while other sensors function normally.\",\n  \"reasoning\": [\n      \"Evidence from Chunk C04 shows the sensor reporting valid values (e.g., 2552) immediately before the anomaly window.\",\n      \"At exactly 09:00:00 and 10:00:00 in Chunk C05, the log entry for living_room_temp_sensor contains no numeric value ('MeasuredValue = '), whereas all other room sensors report valid numbers simultaneously.\",\n      \"This pattern repeats at 20:00:00 in Chunk C11, indicating a systematic fault rather than random noise or network latency.\",\n      \"The consistent recurrence of 'null' events at the same hourly timestamp suggests a firmware crash, power cycle issue, or specific communication timeout inherent to this device.\"\n    ],\n  \"key_evidence\": [\n      \"[2026-06-01T09:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2548 ... [2026-06-01T09:00:00] living_room_temp_sensor | \",\n      \"[2026-06-01T10:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2555 ... [2026-06-01T10:00:00] living_room_temp_sensor | \",\n      \"[2026-06-01T20:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2264 ... [2026-06-01T20:00:00] living_room_temp_sensor | \"\n    ],\n  \"recommended_actions\": [\n      \"Inspect the physical connections and power supply to the living_room_temp_sensor.\",\n      \"Check the device logs on the sensor itself for error codes related to memory overflow, watchdog resets, or bus timeouts.\",\n      \"Consider replacing the sensor if the nulling persists after power cycling and connection checks.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "The living_room_temp_sensor is experiencing intermittent hardware failure or communication loss, resulting in periodic null data readings at regular intervals while other sensors function normally.", "reasoning": ["Evidence from Chunk C04 shows the sensor reporting valid values (e.g., 2552) immediately before the anomaly window.", "At exactly 09:00:00 and 10:00:00 in Chunk C05, the log entry for living_room_temp_sensor contains no numeric value ('MeasuredValue = '), whereas all other room sensors report valid numbers simultaneously.", "This pattern repeats at 20:00:00 in Chunk C11, indicating a systematic fault rather than random noise or network latency.", "The consistent recurrence of 'null' events at the same hourly timestamp suggests a firmware crash, power cycle issue, or specific communication timeout inherent to this device."], "key_evidence": ["[2026-06-01T09:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2548 ... [2026-06-01T09:00:00] living_room_temp_sensor | ", "[2026-06-01T10:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2555 ... [2026-06-01T10:00:00] living_room_temp_sensor | ", "[2026-06-01T20:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2264 ... [2026-06-01T20:00:00] living_room_temp_sensor | "], "recommended_actions": ["Inspect the physical connections and power supply to the living_room_temp_sensor.", "Check the device logs on the sensor itself for error codes related to memory overflow, watchdog resets, or bus timeouts.", "Consider replacing the sensor if the nulling persists after power cycling and connection checks."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": true, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 60.58982467651367, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1132, "chunk_count": 15, "signals": {"room_activity": {"living_room": 407, "bedroom": 357, "kitchen": 298, "bathroom": 56, "entrance": 14}, "attribute_frequency": {"MeasuredValue": 866, "Occupancy": 225, "OnOff": 18, "StateValue": 5, "LockState": 4, "CurrentPositionLiftPercent100ths": 2, "SystemMode": 1, "OperationalState": 1, "CurrentLevel": 1}, "lock_state_flips": 4, "occupancy_events": 225, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"device-health | single-event-safety\",\n  \"focus_rooms\": [\"living_room\"],\n  \"focus_devices\": [\"living_room_temp_sensor\", \"living_room_occupancy\"],\n  \"focus_chunk_ids\": [\"C05\", \"C11\"],\n  \"suspected_patterns\": [\n    \"Temperature sensor reading missing/null (Data Loss)\",\n    \"High frequency alarm events correlated with occupancy changes\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C05 contains a log entry '[2026-06-01T09:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = ' indicating a null or missing value, suggesting sensor failure or communication loss.\",\n    \"Chunk C11 shows multiple alarm counts and potential environmental anomalies (kitchen window open followed by temp sensor null), requiring verification of the living room's correlation during active occupancy periods to rule out systemic issues vs. isolated sensor faults.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "device-health | single-event-safety", "focus_rooms": ["living_room"], "focus_devices": ["living_room_temp_sensor", "living_room_occupancy"], "focus_chunk_ids": ["C05", "C11"], "suspected_patterns": ["Temperature sensor reading missing/null (Data Loss)", "High frequency alarm events correlated with occupancy changes"], "why_these_chunks": ["Chunk C05 contains a log entry '[2026-06-01T09:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = ' indicating a null or missing value, suggesting sensor failure or communication loss.", "Chunk C11 shows multiple alarm counts and potential environmental anomalies (kitchen window open followed by temp sensor null), requiring verification of the living room's correlation during active occupancy periods to rule out systemic issues vs. isolated sensor faults."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The living_room_temp_sensor is functioning correctly, reporting valid temperature data within the expected range (~24-25°C or ~2270-2550 raw units), and gaps in logs are due to temporary network latency or clock synchronization issues.\",\n      \"evidence\": [\n        \"In Chunk C11, readings like 2271, 2281, 2275, 2264, 2273 show a stable, physically plausible progression of temperatures.\",\n        \"In Chunk C05, after a gap at 09:00:00, the sensor resumes reporting values (2536, 2550) that are consistent with neighboring sensors (bedroom/kitchen).\"\n      ],\n      \"weaknesses\": [\n        \"Fails to explain the specific timestamp 2026-06-01T09:00:00 where the log explicitly shows an empty value field instead of a number, which indicates a failure event rather than just missing data.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"The living_room_temp_sensor has a hardware fault causing periodic total readout failures (Data Loss/Nulling).\",\n      \"threat_type\": \"Sensor Failure / Data Integrity Loss\",\n      \"evidence\": [\n        \"Chunk C05 Log Line: '[2026-06-01T09:00:00] living_room_temp_sensor | ' contains no value, whereas adjacent lines for other sensors contain numbers.\",\n        \"Chunk C05 Log Line: '[2026-06-01T10:00:00] living_room_temp_sensor | ' repeats this exact pattern exactly one hour later.\",\n        \"Contrast with other sensors: At both 09:00:00 and 10:00:00, bedroom, kitchen, and bathroom sensors reported valid numeric values, isolating the fault to the living room device.\",\n        \"The anomaly occurs during periods of high activity (living_room occupancy events present in C11 around the time of the C05 gap context).\"\n      ],\n      \"weaknesses\": [\n        \"The exact trigger mechanism (e.g., power cycle vs. firmware crash) is not visible in the provided text logs.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"The living_room_temp_sensor exhibits a calibration drift or offset error, reading significantly higher values than actual temperature compared to other rooms.\",\n      \"threat_type\": \"Calibration Error / Sensor Drift\",\n      \"evidence\": [\n        \"In Chunk C05, Living Room reads ~2550 while Bedroom reads ~2440 (a difference of ~110 raw units).\",\n        \"In Chunk C11, Living Room reads ~2260-2280 while Bedroom reads ~2160-2180 (a difference of ~100 raw units).\",\n        \"This relative difference remains constant across different times and environmental states (day/evening).\"\n      ],\n      \"weaknesses\": [\n        \"A constant offset could be normal if the living room thermostat is set significantly higher than bedrooms. However, combined with the hard 'null' errors in A1, this hypothesis is less likely to be the primary issue.\",\n        \"Cannot rule out that the 'high' reading is actually correct and the bedroom sensor is cold.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The literal absence of a numeric value in the log entry '[2026-06-01T09:00:00] living_room_temp_sensor | ' at two distinct hourly intervals (09:00 and 10:00) while all other room sensors report valid numbers simultaneously.\",\n    \"The recurrence of the empty log line suggests a systematic hardware reset or communication timeout specific to the living room sensor module, rather than random noise.\"\n  ],\n  \"missing_information\": [\n    \"System configuration: What is the expected 'raw unit' conversion factor for temperature? (e.g., are these Kelvin, scaled Celsius, or proprietary units?)\",\n    \"Network topology: Is the living_room sensor on a separate bus or VLAN that might have experienced a periodic outage?\",\n    \"Previous history: Did similar null events occur before 08:57:18 in Chunk C05?\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The living_room_temp_sensor is functioning correctly, reporting valid temperature data within the expected range (~24-25°C or ~2270-2550 raw units), and gaps in logs are due to temporary network latency or clock synchronization issues.", "evidence": ["In Chunk C11, readings like 2271, 2281, 2275, 2264, 2273 show a stable, physically plausible progression of temperatures.", "In Chunk C05, after a gap at 09:00:00, the sensor resumes reporting values (2536, 2550) that are consistent with neighboring sensors (bedroom/kitchen)."], "weaknesses": ["Fails to explain the specific timestamp 2026-06-01T09:00:00 where the log explicitly shows an empty value field instead of a number, which indicates a failure event rather than just missing data."]}], "anomaly_hypotheses": [{"id": "A1", "description": "The living_room_temp_sensor has a hardware fault causing periodic total readout failures (Data Loss/Nulling).", "threat_type": "Sensor Failure / Data Integrity Loss", "evidence": ["Chunk C05 Log Line: '[2026-06-01T09:00:00] living_room_temp_sensor | ' contains no value, whereas adjacent lines for other sensors contain numbers.", "Chunk C05 Log Line: '[2026-06-01T10:00:00] living_room_temp_sensor | ' repeats this exact pattern exactly one hour later.", "Contrast with other sensors: At both 09:00:00 and 10:00:00, bedroom, kitchen, and bathroom sensors reported valid numeric values, isolating the fault to the living room device.", "The anomaly occurs during periods of high activity (living_room occupancy events present in C11 around the time of the C05 gap context)."], "weaknesses": ["The exact trigger mechanism (e.g., power cycle vs. firmware crash) is not visible in the provided text logs."]}, {"id": "A2", "description": "The living_room_temp_sensor exhibits a calibration drift or offset error, reading significantly higher values than actual temperature compared to other rooms.", "threat_type": "Calibration Error / Sensor Drift", "evidence": ["In Chunk C05, Living Room reads ~2550 while Bedroom reads ~2440 (a difference of ~110 raw units).", "In Chunk C11, Living Room reads ~2260-2280 while Bedroom reads ~2160-2180 (a difference of ~100 raw units).", "This relative difference remains constant across different times and environmental states (day/evening)."], "weaknesses": ["A constant offset could be normal if the living room thermostat is set significantly higher than bedrooms. However, combined with the hard 'null' errors in A1, this hypothesis is less likely to be the primary issue.", "Cannot rule out that the 'high' reading is actually correct and the bedroom sensor is cold."]}], "most_discriminative_evidence": ["The literal absence of a numeric value in the log entry '[2026-06-01T09:00:00] living_room_temp_sensor | ' at two distinct hourly intervals (09:00 and 10:00) while all other room sensors report valid numbers simultaneously.", "The recurrence of the empty log line suggests a systematic hardware reset or communication timeout specific to the living room sensor module, rather than random noise."], "missing_information": ["System configuration: What is the expected 'raw unit' conversion factor for temperature? (e.g., are these Kelvin, scaled Celsius, or proprietary units?)", "Network topology: Is the living_room sensor on a separate bus or VLAN that might have experienced a periodic outage?", "Previous history: Did similar null events occur before 08:57:18 in Chunk C05?"]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C04\", \"C06\"],\n  \"missing_checks\": [\n    \"Verify if the null event in C05 was an isolated incident or part of a recurring pattern by checking the immediate preceding chunk (C04) for prior occurrences.\",\n    \"Confirm whether the null event persists or resolves immediately after the timestamp by checking the immediate succeeding chunk (C06).\",\n    \"Cross-reference 'living_room_occupancy' status specifically at the exact timestamps 09:00:00 and 10:00:00 to definitively rule out occupancy-triggered communication drops.\"\n  ],\n  \"supervisor_notes\": [\n    \"The current analysis relies heavily on Chunk C05 and C11. To confirm if the sensor failure is intermittent or permanent, evidence from the chunks immediately surrounding C05 (C04 and C06) is required to establish the temporal boundaries of the fault.\",\n    \"While the investigator noted high activity during the anomaly, explicit confirmation of the occupancy state at the exact moment of the null reading is missing; this requires reviewing the logs in C04/C05/C06 context where occupancy events are logged alongside temperature data.\",\n    \"The hypothesis regarding calibration drift (A2) is plausible but less likely given the hard nulls; however, without seeing the trend before and after the nulls in adjacent chunks, the magnitude of drift cannot be fully quantified.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C04", "C06"], "missing_checks": ["Verify if the null event in C05 was an isolated incident or part of a recurring pattern by checking the immediate preceding chunk (C04) for prior occurrences.", "Confirm whether the null event persists or resolves immediately after the timestamp by checking the immediate succeeding chunk (C06).", "Cross-reference 'living_room_occupancy' status specifically at the exact timestamps 09:00:00 and 10:00:00 to definitively rule out occupancy-triggered communication drops."], "supervisor_notes": ["The current analysis relies heavily on Chunk C05 and C11. To confirm if the sensor failure is intermittent or permanent, evidence from the chunks immediately surrounding C05 (C04 and C06) is required to establish the temporal boundaries of the fault.", "While the investigator noted high activity during the anomaly, explicit confirmation of the occupancy state at the exact moment of the null reading is missing; this requires reviewing the logs in C04/C05/C06 context where occupancy events are logged alongside temperature data.", "The hypothesis regarding calibration drift (A2) is plausible but less likely given the hard nulls; however, without seeing the trend before and after the nulls in adjacent chunks, the magnitude of drift cannot be fully quantified."]}, "preview_triage_prompt": "## Query\n请检查以下设备状态历史，判断 living_room 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Layout\nLayout: 一室一厅 (Studio/1BR)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅台灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 407,\n    \"bedroom\": 357,\n    \"kitchen\": 298,\n    \"bathroom\": 56,\n    \"entrance\": 14\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 866,\n    \"Occupancy\": 225,\n    \"OnOff\": 18,\n    \"StateValue\": 5,\n    \"LockState\": 4,\n    \"CurrentPositionLiftPercent100ths\": 2,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 225,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-01T00:00:00\",\n    \"end_ts\": \"2026-06-01T01:50:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 27,\n      \"bedroom\": 27,\n      \"kitchen\": 22,\n      \"bathroom\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"bathroom_occupancy\"\n    ],\n    \"alarmish_count\": 12,\n    \"preview_lines\": [\n      \"[2026-06-01T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2270\",\n      \"[2026-06-01T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2176\",\n      \"[2026-06-01T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2276\",\n      \"[2026-06-01T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-01T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-01T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-01T00:05:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2265\",\n      \"[2026-06-01T00:05:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2182\",\n      \"[2026-06-01T00:05:00] kitche", "preview_verifier_prompt": "## Query\n请检查以下设备状态历史，判断 living_room 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Triage\n{\n  \"latent_task_profile\": \"device-health | single-event-safety\",\n  \"focus_rooms\": [\"living_room\"],\n  \"focus_devices\": [\"living_room_temp_sensor\", \"living_room_occupancy\"],\n  \"focus_chunk_ids\": [\"C05\", \"C11\"],\n  \"suspected_patterns\": [\n    \"Temperature sensor reading missing/null (Data Loss)\",\n    \"High frequency alarm events correlated with occupancy changes\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C05 contains a log entry '[2026-06-01T09:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = ' indicating a null or missing value, suggesting sensor failure or communication loss.\",\n    \"Chunk C11 shows multiple alarm counts and potential environmental anomalies (kitchen window open followed by temp sensor null), requiring verification of the living room's correlation during active occupancy periods to rule out systemic issues vs. isolated sensor faults.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The living_room_temp_sensor is functioning correctly, reporting valid temperature data within the expected range (~24-25°C or ~2270-2550 raw units), and gaps in logs are due to temporary network latency or clock synchronization issues.\",\n      \"evidence\": [\n        \"In Chunk C11, readings like 2271, 2281, 2275, 2264, 2273 show a stable, physically plausible progression of temperatures.\",\n        \"In Chunk C05, after a gap at 09:00:00, the sensor resumes reporting values (2536, 2550) that are consistent with neighboring sensors (bedroom/kitchen).\"\n      ],\n      \"weaknesses\": [\n        \"Fails to explain the specific timestamp 2026-06-01T09:00:00 where the log explicitly shows an empty value field instead of a number, which indicates a failure event rather than just missing data.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"The living_room_temp_sensor has a hardware fault causing periodic total readout failures (Data Loss/Nulling).\",\n      \"threat_type\": \"Sensor Failure / Data Integrity Loss\",\n      \"evidence\": [\n        \"Chunk C05 Log Line: '[2026-06-01T09:00:00] living_room_temp_sensor | ' contains no value, whereas adjacent lines for other sensors contain numbers.\",\n        \"Chunk C05 Log Line: '[2026-06-01T10:00:00] living_room_temp_sensor | ' repeats this exact pattern exactly one hour later.\",\n        \"Contrast with other sensors: At both 09:00:00 and 10:00:00, bedroom,"}}
{"episode_id": "SQ1_TP_A_0036", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq1\\SQ1_TP_A_0036.json", "metadata": {"sq_type": "SQ1", "sq_name": "设备健康诊断", "variant": "TP", "layout_id": "A", "layout_name": "一室一厅 (Studio/1BR)", "profile_id": "young_professional", "base_date": "2026-06-22T00:00:00", "seed": 20260665, "scenario_id": "DF-04", "total_events": 1127, "anomaly_events_count": 5}, "ground_truth": {"scenario_id": "DF-04", "scenario_name": "门锁响应异常", "category": "device_fault", "is_anomaly": true, "threat_type": "lock_malfunction", "key_evidence": ["LockDoor 命令后 LockState 未变为 Locked", "DoorLockAlarm (LockJammed) 触发", "门锁故障意味着家庭物理安全降级"], "expected_response": "通知住户门锁可能卡住/故障，建议手动检查", "difficulty_score": 8, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 1, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "entrance", "injection_time": "2026-06-22T21:36:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"medium\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"The entrance contact sensor exhibits a delayed state transition following manual locking, suggesting calibration drift or misalignment.\",\n  \"reasoning\": [\n      \"In Chunk C04, a manual lock operation occurred at 07:17:23, immediately followed by the door contact sensor reporting 'False' (open) at 07:17:25 and returning to 'True' (closed) at 07:17:26.\",\n      \"This creates a 2-second gap where the system believes the door is open while it is being locked, which contradicts normal mechanical behavior where the door should be closed immediately upon initiation of the closing mechanism.\",\n      \"Chunks C03 and C05 contain no entry/exit events for the front door during this timeframe, preventing a direct comparison to rule out user error or specific environmental factors on that single day; however, the tight coupling between the lock actuation and the subsequent false negative strongly points to a hardware alignment issue.\"\n    ],\n  \"key_evidence\": [\n      \"Event sequence: LockOperation(Manual) @ 07:17:23 -> ContactSensor(False) @ 07:17:25 -> ContactSensor(True) @ 07:17:26.\",\n      \"The 2-second duration of the 'False' state is abnormally long for a standard door swing, indicating the sensor likely failed to register the initial closure phase.\"\n  ],\n  \"recommended_actions\": [\n      \"Inspect the physical installation of the magnetic reed switch at the entrance to verify gap distance between the lock body and strike plate.\",\n      \"Perform sensor calibration or realignment if physical inspection reveals improper positioning.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "medium", "threat_type": "sensor_malfunction", "threat_description": "The entrance contact sensor exhibits a delayed state transition following manual locking, suggesting calibration drift or misalignment.", "reasoning": ["In Chunk C04, a manual lock operation occurred at 07:17:23, immediately followed by the door contact sensor reporting 'False' (open) at 07:17:25 and returning to 'True' (closed) at 07:17:26.", "This creates a 2-second gap where the system believes the door is open while it is being locked, which contradicts normal mechanical behavior where the door should be closed immediately upon initiation of the closing mechanism.", "Chunks C03 and C05 contain no entry/exit events for the front door during this timeframe, preventing a direct comparison to rule out user error or specific environmental factors on that single day; however, the tight coupling between the lock actuation and the subsequent false negative strongly points to a hardware alignment issue."], "key_evidence": ["Event sequence: LockOperation(Manual) @ 07:17:23 -> ContactSensor(False) @ 07:17:25 -> ContactSensor(True) @ 07:17:26.", "The 2-second duration of the 'False' state is abnormally long for a standard door swing, indicating the sensor likely failed to register the initial closure phase."], "recommended_actions": ["Inspect the physical installation of the magnetic reed switch at the entrance to verify gap distance between the lock body and strike plate.", "Perform sensor calibration or realignment if physical inspection reveals improper positioning."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": true, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "medium"}, "latency": 55.00820231437683, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1127, "chunk_count": 15, "signals": {"room_activity": {"living_room": 400, "bedroom": 353, "kitchen": 298, "bathroom": 57, "entrance": 19}, "attribute_frequency": {"MeasuredValue": 866, "Occupancy": 220, "OnOff": 18, "LockState": 6, "StateValue": 5, "CurrentPositionLiftPercent100ths": 2, "SystemMode": 1, "OperationalState": 1, "CurrentLevel": 1}, "lock_state_flips": 6, "occupancy_events": 220, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"device-health | behavior-sequence\",\n  \"focus_rooms\": [\"entrance\"],\n  \"focus_devices\": [\"front_door_contact\", \"front_door_lock\"],\n  \"focus_chunk_ids\": [\"C04\"],\n  \"suspected_patterns\": [\n    \"Contact sensor state transition mismatch (False -> True) immediately following lock operation\",\n    \"Potential false positive entry event or sensor calibration drift\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C04 is the only segment containing 'entrance' room activity and specific events for 'front_door_contact' and 'front_door_lock'. The preview lines show a rapid sequence: LockState change, followed by ContactSensor StateValue= False, then immediately StateValue= True. This specific temporal correlation between the lock action and the contact state flip suggests a potential fault in the magnetic reed switch alignment or signal interpretation logic that requires inspection.\",\n    \"No other chunks contain entrance-specific data, making C04 the sole source of truth for diagnosing the status of the entrance sensors.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "device-health | behavior-sequence", "focus_rooms": ["entrance"], "focus_devices": ["front_door_contact", "front_door_lock"], "focus_chunk_ids": ["C04"], "suspected_patterns": ["Contact sensor state transition mismatch (False -> True) immediately following lock operation", "Potential false positive entry event or sensor calibration drift"], "why_these_chunks": ["Chunk C04 is the only segment containing 'entrance' room activity and specific events for 'front_door_contact' and 'front_door_lock'. The preview lines show a rapid sequence: LockState change, followed by ContactSensor StateValue= False, then immediately StateValue= True. This specific temporal correlation between the lock action and the contact state flip suggests a potential fault in the magnetic reed switch alignment or signal interpretation logic that requires inspection.", "No other chunks contain entrance-specific data, making C04 the sole source of truth for diagnosing the status of the entrance sensors."]}, "investigator_raw": "```json\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The entrance sensor exhibits normal mechanical behavior during a manual door closure, where the magnetic reed switch is momentarily disengaged (False) as the door swings shut and immediately re-engages (True) once the door stops moving.\",\n      \"evidence\": [\n        \"Event at 07:17:23: Manual LockOperation initiated (Door closing).\",\n        \"Event at 07:17:25: front_door_contact StateValue = False (Gap detected).\",\n        \"Event at 07:17:26: front_door_contact StateValue = True (Gap closed).\"\n      ],\n      \"weaknesses\": [\n        \"The 'False' state persisted for exactly 2 seconds (07:17:23 to 07:17:25), which is unusually long for a standard door swing unless there was significant air resistance or a heavy door mechanism.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Front door contact sensor calibration drift or misalignment causing false negative readings.\",\n      \"threat_type\": \"Sensor Malfunction / Calibration Drift\",\n      \"evidence\": [\n        \"Temporal correlation between LockState change and ContactSensor flip suggests the system might be interpreting the lock actuation as a door breach event.\",\n        \"The sequence Lock->False->True implies the sensor did not register the 'closed' state immediately upon the start of the locking mechanism, potentially missing the initial closure phase.\",\n        \"Low room_activity count (19) for entrance compared to other rooms suggests potential under-reporting of entry/exit events due to sensor unreliability.\"\n      ],\n      \"weaknesses\": [\n        \"No other data points in Chunk C04 show erratic flipping outside of this specific lock event.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Intermittent electrical connection or loose wiring in the entrance contact sensor.\",\n      \"threat_type\": \"Hardware Failure\",\n      \"evidence\": [\n        \"The rapid transition from False back to True within 1 second could indicate a momentary signal dropout before stabilization, typical of loose connections.\"\n      ],\n      \"weaknesses\": [\n        \"The sensor quickly recovered to a stable 'True' state, which argues against a complete hardware failure like an open circuit.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The precise timestamp sequence: LockOperation(Manual) -> LockState=2 -> Contact=False -> Contact=True. This tight coupling suggests the contact sensor state is being triggered by the lock motor's movement rather than independent door motion.\",\n    \"The duration of the 'False' state (2 seconds) relative to the speed of a typical door operation indicates a possible delay in signal propagation or mechanical lag.\"\n  ],\n  \"missing_information\": [\n    \"Historical data for the same time on previous days to compare if this pattern is recurrent or isolated.\",\n    \"Raw voltage/current readings from the contact sensor during the 07:17:23-07:17:26 window to confirm signal integrity.\",\n    \"Physical installation logs to verify the current gap distance between the lock body and the strike plate/reed switch.\"\n  ]\n}\n```", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The entrance sensor exhibits normal mechanical behavior during a manual door closure, where the magnetic reed switch is momentarily disengaged (False) as the door swings shut and immediately re-engages (True) once the door stops moving.", "evidence": ["Event at 07:17:23: Manual LockOperation initiated (Door closing).", "Event at 07:17:25: front_door_contact StateValue = False (Gap detected).", "Event at 07:17:26: front_door_contact StateValue = True (Gap closed)."], "weaknesses": ["The 'False' state persisted for exactly 2 seconds (07:17:23 to 07:17:25), which is unusually long for a standard door swing unless there was significant air resistance or a heavy door mechanism."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Front door contact sensor calibration drift or misalignment causing false negative readings.", "threat_type": "Sensor Malfunction / Calibration Drift", "evidence": ["Temporal correlation between LockState change and ContactSensor flip suggests the system might be interpreting the lock actuation as a door breach event.", "The sequence Lock->False->True implies the sensor did not register the 'closed' state immediately upon the start of the locking mechanism, potentially missing the initial closure phase.", "Low room_activity count (19) for entrance compared to other rooms suggests potential under-reporting of entry/exit events due to sensor unreliability."], "weaknesses": ["No other data points in Chunk C04 show erratic flipping outside of this specific lock event."]}, {"id": "A2", "description": "Intermittent electrical connection or loose wiring in the entrance contact sensor.", "threat_type": "Hardware Failure", "evidence": ["The rapid transition from False back to True within 1 second could indicate a momentary signal dropout before stabilization, typical of loose connections."], "weaknesses": ["The sensor quickly recovered to a stable 'True' state, which argues against a complete hardware failure like an open circuit."]}], "most_discriminative_evidence": ["The precise timestamp sequence: LockOperation(Manual) -> LockState=2 -> Contact=False -> Contact=True. This tight coupling suggests the contact sensor state is being triggered by the lock motor's movement rather than independent door motion.", "The duration of the 'False' state (2 seconds) relative to the speed of a typical door operation indicates a possible delay in signal propagation or mechanical lag."], "missing_information": ["Historical data for the same time on previous days to compare if this pattern is recurrent or isolated.", "Raw voltage/current readings from the contact sensor during the 07:17:23-07:17:26 window to confirm signal integrity.", "Physical installation logs to verify the current gap distance between the lock body and the strike plate/reed switch."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C03\", \"C05\"],\n  \"missing_checks\": [\n    \"Cross-reference with historical data from previous days to determine if the 'Lock->False->True' pattern is a recurring anomaly or an isolated incident.\",\n    \"Verify physical installation logs for gap distance between lock body and reed switch at the entrance.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis is currently focused on a single event (Chunk C04) without sufficient context. To distinguish between a mechanical delay (Normal Hypothesis N1) and sensor drift/misalignment (Anomaly Hypothesis A1), it is necessary to check adjacent chunks (C03, C05) for similar door operations where the sensor behaved normally. If the same 2-second False state occurs during manual locking in other chunks, it likely indicates a systematic issue with that specific door mechanism rather than a sensor fault.\",\n    \"The investigator correctly identified missing raw signal data and historical trends, which are critical for validating the hypothesis of calibration drift versus normal behavior.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C03", "C05"], "missing_checks": ["Cross-reference with historical data from previous days to determine if the 'Lock->False->True' pattern is a recurring anomaly or an isolated incident.", "Verify physical installation logs for gap distance between lock body and reed switch at the entrance."], "supervisor_notes": ["The analysis is currently focused on a single event (Chunk C04) without sufficient context. To distinguish between a mechanical delay (Normal Hypothesis N1) and sensor drift/misalignment (Anomaly Hypothesis A1), it is necessary to check adjacent chunks (C03, C05) for similar door operations where the sensor behaved normally. If the same 2-second False state occurs during manual locking in other chunks, it likely indicates a systematic issue with that specific door mechanism rather than a sensor fault.", "The investigator correctly identified missing raw signal data and historical trends, which are critical for validating the hypothesis of calibration drift versus normal behavior."]}, "preview_triage_prompt": "## Query\n请检查以下设备状态历史，判断 entrance 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Layout\nLayout: 一室一厅 (Studio/1BR)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅台灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 400,\n    \"bedroom\": 353,\n    \"kitchen\": 298,\n    \"bathroom\": 57,\n    \"entrance\": 19\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 866,\n    \"Occupancy\": 220,\n    \"OnOff\": 18,\n    \"LockState\": 6,\n    \"StateValue\": 5,\n    \"CurrentPositionLiftPercent100ths\": 2,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 6,\n  \"occupancy_events\": 220,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-22T00:00:00\",\n    \"end_ts\": \"2026-06-22T01:50:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 27,\n      \"bedroom\": 27,\n      \"kitchen\": 22,\n      \"bathroom\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"bathroom_occupancy\"\n    ],\n    \"alarmish_count\": 12,\n    \"preview_lines\": [\n      \"[2026-06-22T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2270\",\n      \"[2026-06-22T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2176\",\n      \"[2026-06-22T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2274\",\n      \"[2026-06-22T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-22T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-22T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-22T00:05:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2280\",\n      \"[2026-06-22T00:05:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2166\",\n      \"[2026-06-22T00:05:00] kitchen_t", "preview_verifier_prompt": "## Query\n请检查以下设备状态历史，判断 entrance 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Triage\n{\n  \"latent_task_profile\": \"device-health | behavior-sequence\",\n  \"focus_rooms\": [\"entrance\"],\n  \"focus_devices\": [\"front_door_contact\", \"front_door_lock\"],\n  \"focus_chunk_ids\": [\"C04\"],\n  \"suspected_patterns\": [\n    \"Contact sensor state transition mismatch (False -> True) immediately following lock operation\",\n    \"Potential false positive entry event or sensor calibration drift\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C04 is the only segment containing 'entrance' room activity and specific events for 'front_door_contact' and 'front_door_lock'. The preview lines show a rapid sequence: LockState change, followed by ContactSensor StateValue= False, then immediately StateValue= True. This specific temporal correlation between the lock action and the contact state flip suggests a potential fault in the magnetic reed switch alignment or signal interpretation logic that requires inspection.\",\n    \"No other chunks contain entrance-specific data, making C04 the sole source of truth for diagnosing the status of the entrance sensors.\"\n  ]\n}\n\n## Investigator\n```json\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The entrance sensor exhibits normal mechanical behavior during a manual door closure, where the magnetic reed switch is momentarily disengaged (False) as the door swings shut and immediately re-engages (True) once the door stops moving.\",\n      \"evidence\": [\n        \"Event at 07:17:23: Manual LockOperation initiated (Door closing).\",\n        \"Event at 07:17:25: front_door_contact StateValue = False (Gap detected).\",\n        \"Event at 07:17:26: front_door_contact StateValue = True (Gap closed).\"\n      ],\n      \"weaknesses\": [\n        \"The 'False' state persisted for exactly 2 seconds (07:17:23 to 07:17:25), which is unusually long for a standard door swing unless there was significant air resistance or a heavy door mechanism.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Front door contact sensor calibration drift or misalignment causing false negative readings.\",\n      \"threat_type\": \"Sensor Malfunction / Calibration Drift\",\n      \"evidence\": [\n        \"Temporal correlation between LockState change and ContactSensor flip suggests the system might be interpreting the lock actuation as a door breach event.\",\n        \"The sequence Lock->False->True implies the sensor did not register the 'closed' state immediately u"}}
{"episode_id": "SQ1_TP_C_0005", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq1\\SQ1_TP_C_0005.json", "metadata": {"sq_type": "SQ1", "sq_name": "设备健康诊断", "variant": "TP", "layout_id": "C", "layout_name": "三室两厅 (3BR)", "profile_id": "family_with_children", "base_date": "2026-06-09T00:00:00", "seed": 20260634, "scenario_id": "DF-01", "total_events": 2296, "anomaly_events_count": 10}, "ground_truth": {"scenario_id": "DF-01", "scenario_name": "温度传感器读数固定（stuck-at）", "category": "device_fault", "is_anomaly": true, "threat_type": "sensor_stuck", "key_evidence": ["Day1 温度有正常的日间波动（上午偏低、中午偏高、晚间回落）", "Day2 中午开始读数完全固定在 23.50°C", "连续24小时+完全无变化，真实温度不可能如此稳定"], "expected_response": "标记传感器可能故障，建议住户检查/更换", "difficulty_score": 12, "difficulty_level": 3, "difficulty_label": "L3_composite_reasoning", "difficulty_dimensions": {"D1_evidence_count": 3, "D2_signal_directness": 3, "D3_cross_device": 1, "D4_temporal_span": 3, "D5_fp_similarity": 2}, "target_room": "kitchen", "injection_time": "2026-06-09T08:34:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"Kitchen sensors are reporting physically impossible temperatures due to a persistent x10 data scaling error or firmware bug.\",\n  \"reasoning\": [\n      \"All temperature readings across all rooms (including kitchen) consistently exceed 2000, with values reaching up to 2493, which implies an ambient temperature of nearly 250°C if interpreted as Celsius.\",\n      \"The reported values show a logical diurnal pattern consistent with real-world heating (gradual increase from ~227 to ~248), but the magnitude is off by a factor of exactly 10, indicating a systematic unit conversion failure rather than random noise or sensor drift.\",\n      \"While other occupancy sensors function correctly (generating events when people enter rooms like the master bathroom), the specific temperature data format for the kitchen sensor is invalid for any standard residential HVAC logic.\"\n    ],\n  \"key_evidence\": [\n      \"kitchen_temp_sensor reports value 2493 at 2026-06-09T06:15:00, implying 249.3°C in a living space.\",\n      \"Consistent x10 ratio observed between expected residential temps (~22-25°C) and actual raw logs (227-248).\"\n    ],\n  \"recommended_actions\": [\n      \"Reset or reboot the kitchen temperature sensor to clear potential firmware state corruption.\",\n      \"Check the device configuration or aggregator settings to verify if the 'Deci-Celsius' unit multiplier was incorrectly applied globally or locally.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "Kitchen sensors are reporting physically impossible temperatures due to a persistent x10 data scaling error or firmware bug.", "reasoning": ["All temperature readings across all rooms (including kitchen) consistently exceed 2000, with values reaching up to 2493, which implies an ambient temperature of nearly 250°C if interpreted as Celsius.", "The reported values show a logical diurnal pattern consistent with real-world heating (gradual increase from ~227 to ~248), but the magnitude is off by a factor of exactly 10, indicating a systematic unit conversion failure rather than random noise or sensor drift.", "While other occupancy sensors function correctly (generating events when people enter rooms like the master bathroom), the specific temperature data format for the kitchen sensor is invalid for any standard residential HVAC logic."], "key_evidence": ["kitchen_temp_sensor reports value 2493 at 2026-06-09T06:15:00, implying 249.3°C in a living space.", "Consistent x10 ratio observed between expected residential temps (~22-25°C) and actual raw logs (227-248)."], "recommended_actions": ["Reset or reboot the kitchen temperature sensor to clear potential firmware state corruption.", "Check the device configuration or aggregator settings to verify if the 'Deci-Celsius' unit multiplier was incorrectly applied globally or locally."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": true, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 52.94069766998291, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 2296, "chunk_count": 29, "signals": {"room_activity": {"living_room": 398, "master_bedroom": 515, "kids_room": 515, "kitchen": 313, "dining_room": 223, "second_bedroom": 48, "master_bathroom": 56, "entrance": 227, "second_bathroom": 1}, "attribute_frequency": {"MeasuredValue": 1166, "Occupancy": 1082, "OnOff": 26, "StateValue": 7, "LockState": 5, "CurrentPositionLiftPercent100ths": 3, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 5, "occupancy_events": 1082, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"device-health\",\n  \"focus_rooms\": [\n    \"kitchen\"\n  ],\n  \"focus_devices\": [\n    \"kitchen_temp_sensor\",\n    \"kitchen_window_sensor\",\n    \"kitchen_occupancy_sensor\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C00\",\n    \"C01\",\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C06\",\n    \"C07\",\n    \"C08\",\n    \"C09\",\n    \"C10\",\n    \"C11\",\n    \"C12\",\n    \"C13\",\n    \"C14\",\n    \"C15\",\n    \"C16\",\n    \"C17\",\n    \"C18\",\n    \"C19\",\n    \"C20\",\n    \"C21\",\n    \"C22\",\n    \"C23\",\n    \"C24\",\n    \"C25\",\n    \"C26\",\n    \"C27\",\n    \"C28\"\n  ],\n  \"suspected_patterns\": [\n    \"Temperature values are consistently scaled by a factor of ~10 (e.g., 22.7°C reported as 227)\",\n    \"Missing occupancy sensor events in the kitchen despite high activity counts in other rooms\",\n    \"Absence of window/door contact sensor events for the kitchen area throughout the entire log\"\n  ],\n  \"why_these_chunks\": \"All chunks are required to perform a longitudinal health check. The analysis must verify if the temperature scaling is a global system artifact or isolated to the kitchen sensor, and confirm if the lack of specific event types (occupancy/window state) in the kitchen is consistent across all time periods or sporadic.\"\n}", "triage_parsed": {"latent_task_profile": "device-health", "focus_rooms": ["kitchen"], "focus_devices": ["kitchen_temp_sensor", "kitchen_window_sensor", "kitchen_occupancy_sensor"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04", "C05", "C06", "C07", "C08", "C09", "C10", "C11", "C12", "C13", "C14", "C15", "C16", "C17", "C18", "C19", "C20", "C21", "C22", "C23", "C24", "C25", "C26", "C27", "C28"], "suspected_patterns": ["Temperature values are consistently scaled by a factor of ~10 (e.g., 22.7°C reported as 227)", "Missing occupancy sensor events in the kitchen despite high activity counts in other rooms", "Absence of window/door contact sensor events for the kitchen area throughout the entire log"], "why_these_chunks": "All chunks are required to perform a longitudinal health check. The analysis must verify if the temperature scaling is a global system artifact or isolated to the kitchen sensor, and confirm if the lack of specific event types (occupancy/window state) in the kitchen is consistent across all time periods or sporadic."}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The kitchen temperature sensor is functioning correctly, and the high numerical values (e.g., 2400) represent a valid data format where temperature in Celsius is multiplied by 10.\",\n      \"evidence\": [\n        \"All room sensors report consistent scaling factors (~10x), suggesting a global system configuration rather than an isolated hardware fault.\",\n        \"Temperature values show logical diurnal variation patterns (gradual increase over time from ~227 to ~248), consistent with ambient heating or appliance usage.\"\n      ],\n      \"weaknesses\": [\n        \"Standard HVAC systems rarely operate at temperatures exceeding 45°C (450 on this scale); while possible in extreme industrial settings, residential peaks of 24.8°C are typical, making 2480 physically improbable for a standard living space unless it is a specialized server room or sauna, which contradicts the 'kitchen' label.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"The kitchen temperature sensor has a firmware or calibration error causing a persistent x10 multiplication overflow, rendering all readings invalid for standard control logic.\",\n      \"threat_type\": \"Sensor Calibration Error / Firmware Bug\",\n      \"evidence\": [\n        \"Raw values consistently exceed realistic residential thresholds (e.g., 2480 implies 248°C, far above boiling point).\",\n        \"The `attribute_frequency` shows only 7 `StateValue` events but 1166 `MeasuredValue` events, indicating the system relies heavily on these inflated numbers for state determination.\",\n        \"No `temperature_patterns` were detected in the structured signals, likely because the parsing engine failed to normalize the x10 factor automatically.\"\n      ],\n      \"weaknesses\": [\n        \"If this is a global system artifact affecting all rooms, the issue might be in the central aggregator rather than the specific kitchen sensor hardware.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"The kitchen occupancy sensor is completely non-functional or disconnected, resulting in zero event generation despite high activity counts in adjacent rooms.\",\n      \"threat_type\": \"Device Disconnection / Power Loss\",\n      \"evidence\": [\n        \"Structured signal `room_activity` shows 313 events for the kitchen vs 398 for the living room, yet no `OccupancySensing.Occupancy` events appear for the kitchen in any chunk.\",\n        \"In contrast, other rooms like the master bathroom show discrete event logs (e.g., C04: Occupancy=1, Light=OnOff=True).\",\n        \"Suspected pattern explicitly notes: 'Missing occupancy sensor events in the kitchen despite high activity counts in other rooms'.\"\n      ],\n      \"weaknesses\": [\n        \"High activity counts in the kitchen could theoretically stem from window/door sensors if they were active, though the triage output suggests their absence as well.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"Consistent presence of TemperatureMeasurement.MeasuredValue = ~2300-2480 across all chunks, which maps to >23°C only if divided by 10, creating a physical impossibility for normal residential cooking environments without normalization.\",\n    \"Complete absence of `OccupancySensing` log lines for `kitchen_occupancy` throughout the entire 6+ hour timeline, unlike other rooms which log periodic states.\"\n  ],\n  \"missing_information\": [\n    \"The raw unit definition or schema for `TemperatureMeasurement.MeasuredValue` to confirm if 'Celsius' or 'Deci-Celsius' is expected.\",\n    \"Hardware status flags (e.g., battery level, last heartbeat timestamp) for the kitchen sensors to rule out total power failure.\",\n    \"Activity logs specifically for windows/doors in the kitchen to verify if the lack of occupancy data is due to a missing sensor type entirely or a malfunctioning one.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The kitchen temperature sensor is functioning correctly, and the high numerical values (e.g., 2400) represent a valid data format where temperature in Celsius is multiplied by 10.", "evidence": ["All room sensors report consistent scaling factors (~10x), suggesting a global system configuration rather than an isolated hardware fault.", "Temperature values show logical diurnal variation patterns (gradual increase over time from ~227 to ~248), consistent with ambient heating or appliance usage."], "weaknesses": ["Standard HVAC systems rarely operate at temperatures exceeding 45°C (450 on this scale); while possible in extreme industrial settings, residential peaks of 24.8°C are typical, making 2480 physically improbable for a standard living space unless it is a specialized server room or sauna, which contradicts the 'kitchen' label."]}], "anomaly_hypotheses": [{"id": "A1", "description": "The kitchen temperature sensor has a firmware or calibration error causing a persistent x10 multiplication overflow, rendering all readings invalid for standard control logic.", "threat_type": "Sensor Calibration Error / Firmware Bug", "evidence": ["Raw values consistently exceed realistic residential thresholds (e.g., 2480 implies 248°C, far above boiling point).", "The `attribute_frequency` shows only 7 `StateValue` events but 1166 `MeasuredValue` events, indicating the system relies heavily on these inflated numbers for state determination.", "No `temperature_patterns` were detected in the structured signals, likely because the parsing engine failed to normalize the x10 factor automatically."], "weaknesses": ["If this is a global system artifact affecting all rooms, the issue might be in the central aggregator rather than the specific kitchen sensor hardware."]}, {"id": "A2", "description": "The kitchen occupancy sensor is completely non-functional or disconnected, resulting in zero event generation despite high activity counts in adjacent rooms.", "threat_type": "Device Disconnection / Power Loss", "evidence": ["Structured signal `room_activity` shows 313 events for the kitchen vs 398 for the living room, yet no `OccupancySensing.Occupancy` events appear for the kitchen in any chunk.", "In contrast, other rooms like the master bathroom show discrete event logs (e.g., C04: Occupancy=1, Light=OnOff=True).", "Suspected pattern explicitly notes: 'Missing occupancy sensor events in the kitchen despite high activity counts in other rooms'."], "weaknesses": ["High activity counts in the kitchen could theoretically stem from window/door sensors if they were active, though the triage output suggests their absence as well."]}], "most_discriminative_evidence": ["Consistent presence of TemperatureMeasurement.MeasuredValue = ~2300-2480 across all chunks, which maps to >23°C only if divided by 10, creating a physical impossibility for normal residential cooking environments without normalization.", "Complete absence of `OccupancySensing` log lines for `kitchen_occupancy` throughout the entire 6+ hour timeline, unlike other rooms which log periodic states."], "missing_information": ["The raw unit definition or schema for `TemperatureMeasurement.MeasuredValue` to confirm if 'Celsius' or 'Deci-Celsius' is expected.", "Hardware status flags (e.g., battery level, last heartbeat timestamp) for the kitchen sensors to rule out total power failure.", "Activity logs specifically for windows/doors in the kitchen to verify if the lack of occupancy data is due to a missing sensor type entirely or a malfunctioning one."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [],\n  \"missing_checks\": [\n    \"Verify hardware status flags (battery level, last heartbeat) for kitchen sensors to rule out power failure.\",\n    \"Check raw schema/unit definition for TemperatureMeasurement.MeasuredValue to confirm expected units (Celsius vs Deci-Celsius).\",\n    \"Review activity logs specifically for window/door sensors in the kitchen to distinguish between missing sensor type and malfunction.\"\n  ],\n  \"supervisor_notes\": [\n    \"The investigator has correctly identified potential anomalies (temperature scaling x10 and missing occupancy events) based on the provided chunks C00-C28.\",\n    \"However, the evidence is insufficient to definitively diagnose the root cause. The analysis currently relies on correlation with other rooms but lacks direct hardware diagnostics (status flags) and schema definitions required to confirm if the temperature issue is a data format error or a hardware fault.\",\n    \"The current chunk selection covers the entire timeline, so no additional chunks are needed; the gap lies in the specific fields within those chunks that were not analyzed yet.\",\n    \"Proceed to extract metadata and status fields from the existing chunks rather than requesting new time-based chunks.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": [], "missing_checks": ["Verify hardware status flags (battery level, last heartbeat) for kitchen sensors to rule out power failure.", "Check raw schema/unit definition for TemperatureMeasurement.MeasuredValue to confirm expected units (Celsius vs Deci-Celsius).", "Review activity logs specifically for window/door sensors in the kitchen to distinguish between missing sensor type and malfunction."], "supervisor_notes": ["The investigator has correctly identified potential anomalies (temperature scaling x10 and missing occupancy events) based on the provided chunks C00-C28.", "However, the evidence is insufficient to definitively diagnose the root cause. The analysis currently relies on correlation with other rooms but lacks direct hardware diagnostics (status flags) and schema definitions required to confirm if the temperature issue is a data format error or a hardware fault.", "The current chunk selection covers the entire timeline, so no additional chunks are needed; the gap lies in the specific fields within those chunks that were not analyzed yet.", "Proceed to extract metadata and status fields from the existing chunks rather than requesting new time-based chunks."]}, "preview_triage_prompt": "## Query\n请检查以下设备状态历史，判断 kitchen 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Layout\nLayout: 三室两厅 (3BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kids_room: 儿童房温度传感器<temperature_sensor>, 儿童房灯<dimmable_light>, 儿童房窗帘<window_covering>, 儿童房窗户传感器<contact_sensor>, 儿童房运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅副灯<dimmable_light>, 客厅氛围灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘1<window_covering>, 客厅窗户传感器1<contact_sensor>, 客厅窗户传感器2<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n- master_bathroom: 主卫漏水传感器<water_leak_detector>, 主卫灯<onoff_light>, 主卫运动传感器<occupancy_sensor>\n- master_bedroom: 主卧床头灯<onoff_light>, 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>\n- second_bedroom: 次卧灯<dimmable_light>, 次卧空调<air_conditioner>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 398,\n    \"master_bedroom\": 515,\n    \"kids_room\": 515,\n    \"kitchen\": 313,\n    \"dining_room\": 223,\n    \"second_bedroom\": 48,\n    \"master_bathroom\": 56,\n    \"entrance\": 227,\n    \"second_bathroom\": 1\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1166,\n    \"Occupancy\": 1082,\n    \"OnOff\": 26,\n    \"StateValue\": 7,\n    \"LockState\": 5,\n    \"CurrentPositionLiftPercent100ths\": 3,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 5,\n  \"occupancy_events\": 1082,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-09T00:00:00\",\n    \"end_ts\": \"2026-06-09T01:10:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 18,\n      \"master_bedroom\": 18,\n      \"kids_room\": 18,\n      \"kitchen\": 14,\n      \"dining_room\": 3,\n      \"second_bedroom\": 3,\n      \"master_bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"kids_room_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupa", "preview_verifier_prompt": "## Query\n请检查以下设备状态历史，判断 kitchen 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Triage\n{\n  \"latent_task_profile\": \"device-health\",\n  \"focus_rooms\": [\n    \"kitchen\"\n  ],\n  \"focus_devices\": [\n    \"kitchen_temp_sensor\",\n    \"kitchen_window_sensor\",\n    \"kitchen_occupancy_sensor\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C00\",\n    \"C01\",\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C06\",\n    \"C07\",\n    \"C08\",\n    \"C09\",\n    \"C10\",\n    \"C11\",\n    \"C12\",\n    \"C13\",\n    \"C14\",\n    \"C15\",\n    \"C16\",\n    \"C17\",\n    \"C18\",\n    \"C19\",\n    \"C20\",\n    \"C21\",\n    \"C22\",\n    \"C23\",\n    \"C24\",\n    \"C25\",\n    \"C26\",\n    \"C27\",\n    \"C28\"\n  ],\n  \"suspected_patterns\": [\n    \"Temperature values are consistently scaled by a factor of ~10 (e.g., 22.7°C reported as 227)\",\n    \"Missing occupancy sensor events in the kitchen despite high activity counts in other rooms\",\n    \"Absence of window/door contact sensor events for the kitchen area throughout the entire log\"\n  ],\n  \"why_these_chunks\": \"All chunks are required to perform a longitudinal health check. The analysis must verify if the temperature scaling is a global system artifact or isolated to the kitchen sensor, and confirm if the lack of specific event types (occupancy/window state) in the kitchen is consistent across all time periods or sporadic.\"\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The kitchen temperature sensor is functioning correctly, and the high numerical values (e.g., 2400) represent a valid data format where temperature in Celsius is multiplied by 10.\",\n      \"evidence\": [\n        \"All room sensors report consistent scaling factors (~10x), suggesting a global system configuration rather than an isolated hardware fault.\",\n        \"Temperature values show logical diurnal variation patterns (gradual increase over time from ~227 to ~248), consistent with ambient heating or appliance usage.\"\n      ],\n      \"weaknesses\": [\n        \"Standard HVAC systems rarely operate at temperatures exceeding 45°C (450 on this scale); while possible in extreme industrial settings, residential peaks of 24.8°C are typical, making 2480 physically improbable for a standard living space unless it is a specialized server room or sauna, which contradicts the 'kitchen' label.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"The kitchen temperature sensor has a firmware or calibration error causing a persistent x10 multiplication overflow, rendering all readings inv"}}
{"episode_id": "SQ1_TP_B_0000", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq1\\SQ1_TP_B_0000.json", "metadata": {"sq_type": "SQ1", "sq_name": "设备健康诊断", "variant": "TP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "young_professional", "base_date": "2026-06-08T00:00:00", "seed": 20260629, "scenario_id": "DF-03", "total_events": 1656, "anomaly_events_count": 5}, "ground_truth": {"scenario_id": "DF-03", "scenario_name": "运动传感器持续触发", "category": "device_fault", "is_anomaly": true, "threat_type": "sensor_malfunction", "key_evidence": ["运动传感器高频率周期性触发", "该房间无其他活动迹象（灯关、无门窗事件）", "周期性极其规律（不像人类活动的随机性）"], "expected_response": "", "difficulty_score": 9, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 3, "D2_signal_directness": 2, "D3_cross_device": 1, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "second_bedroom", "injection_time": "2026-06-08T07:48:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"The second_bedroom_temp_sensor exhibits severe calibration drift or data integrity failure, reporting physically impossible values that diverge significantly from peer sensors without correlating to environmental changes.\",\n  \"reasoning\": [\n    \"All sensors report values in the range of 2300-2550, which is physically unrealistic for Celsius (indoor temps are typically 18-30°C), suggesting a raw integer scale where ~23.5°C corresponds to 2350. Despite this scaling, the divergence pattern is anomalous.\",\n    \"While all sensors show an upward trend initially (likely due to external heat gain or AC failure), the second_bedroom sensor shows a distinct, steady linear ascent (e.g., 2352 -> 2400 -> 2450) that continues even when other rooms fluctuate or plateau.\",\n    \"At 07:48, occupancy is detected in the second bedroom, yet the high temperature reading was already established hours prior and does not spike further upon human entry, ruling out body heat as the cause.\",\n    \"The gap between the second_bedroom sensor and others widens over time (from ~1 unit difference to ~30+ units), indicating a local fault such as a stuck incrementer, firmware overflow, or specific sensor aging rather than a global ambient shift.\"\n  ],\n  \"key_evidence\": [\n    \"Second bedroom sensor reads 2523 at 07:35 while living_room reads 2530; however, the trajectory of the second bedroom sensor (steady linear climb) contrasts sharply with the noisy fluctuations of others.\",\n    \"Occupancy event at 07:48 in the second bedroom occurs after the anomaly has persisted for hours, confirming the reading is not caused by local thermal sources.\",\n    \"No status flags (battery/signal) are provided to rule out power-induced drift, but the magnitude of divergence (~3% error relative to absolute value, growing larger) points to a hardware/software fault.\"\n  ],\n  \"recommended_actions\": [\n    \"Reset the second_bedroom_temp_sensor node immediately to clear potential temporary state corruption.\",\n    \"Inspect the physical sensor location for obstructions or direct sunlight exposure causing localized heating not seen elsewhere.\",\n    \"Replace the sensor if the reset fails, as the device appears to have suffered irreversible calibration drift or component failure.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "The second_bedroom_temp_sensor exhibits severe calibration drift or data integrity failure, reporting physically impossible values that diverge significantly from peer sensors without correlating to environmental changes.", "reasoning": ["All sensors report values in the range of 2300-2550, which is physically unrealistic for Celsius (indoor temps are typically 18-30°C), suggesting a raw integer scale where ~23.5°C corresponds to 2350. Despite this scaling, the divergence pattern is anomalous.", "While all sensors show an upward trend initially (likely due to external heat gain or AC failure), the second_bedroom sensor shows a distinct, steady linear ascent (e.g., 2352 -> 2400 -> 2450) that continues even when other rooms fluctuate or plateau.", "At 07:48, occupancy is detected in the second bedroom, yet the high temperature reading was already established hours prior and does not spike further upon human entry, ruling out body heat as the cause.", "The gap between the second_bedroom sensor and others widens over time (from ~1 unit difference to ~30+ units), indicating a local fault such as a stuck incrementer, firmware overflow, or specific sensor aging rather than a global ambient shift."], "key_evidence": ["Second bedroom sensor reads 2523 at 07:35 while living_room reads 2530; however, the trajectory of the second bedroom sensor (steady linear climb) contrasts sharply with the noisy fluctuations of others.", "Occupancy event at 07:48 in the second bedroom occurs after the anomaly has persisted for hours, confirming the reading is not caused by local thermal sources.", "No status flags (battery/signal) are provided to rule out power-induced drift, but the magnitude of divergence (~3% error relative to absolute value, growing larger) points to a hardware/software fault."], "recommended_actions": ["Reset the second_bedroom_temp_sensor node immediately to clear potential temporary state corruption.", "Inspect the physical sensor location for obstructions or direct sunlight exposure causing localized heating not seen elsewhere.", "Replace the sensor if the reset fails, as the device appears to have suffered irreversible calibration drift or component failure."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": true, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 68.34636211395264, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1656, "chunk_count": 21, "signals": {"room_activity": {"living_room": 399, "master_bedroom": 336, "second_bedroom": 341, "kitchen": 298, "bathroom": 52, "entrance": 230}, "attribute_frequency": {"MeasuredValue": 1154, "Occupancy": 473, "OnOff": 14, "StateValue": 5, "LockState": 4, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 4, "occupancy_events": 473, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"device-health\",\n  \"focus_rooms\": [\"second_bedroom\", \"kitchen\", \"living_room\"],\n  \"focus_devices\": [\n    \"second_bedroom_temp_sensor\",\n    \"kitchen_temp_sensor\",\n    \"living_room_temp_sensor\"\n  ],\n  \"focus_chunk_ids\": [\"C01\", \"C02\", \"C03\", \"C04\", \"C05\", \"C15\", \"C16\"],\n  \"suspected_patterns\": [\n    \"Temperature drift indicating calibration failure or sensor aging\",\n    \"Discrepancy between reported temperature and occupancy context (e.g., high temp when room is empty)\"\n  ],\n  \"why_these_chunks\": [\n    \"C01-C05: Show a progressive, unrealistic rise in second_bedroom_temp_sensor readings (from ~2270 to ~2530) while other sensors remain relatively stable or follow a different curve, suggesting a specific sensor fault rather than ambient heating.\",\n    \"C15-C06: Kitchen sensor spikes significantly higher than living_room during AC operation, indicating potential sensor saturation or offset issues compared to the main living area.\",\n    \"Cross-validation needed: Comparing these chunks against 'empty' state logs to confirm if the high temperatures persist without heat sources present.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "device-health", "focus_rooms": ["second_bedroom", "kitchen", "living_room"], "focus_devices": ["second_bedroom_temp_sensor", "kitchen_temp_sensor", "living_room_temp_sensor"], "focus_chunk_ids": ["C01", "C02", "C03", "C04", "C05", "C15", "C16"], "suspected_patterns": ["Temperature drift indicating calibration failure or sensor aging", "Discrepancy between reported temperature and occupancy context (e.g., high temp when room is empty)"], "why_these_chunks": ["C01-C05: Show a progressive, unrealistic rise in second_bedroom_temp_sensor readings (from ~2270 to ~2530) while other sensors remain relatively stable or follow a different curve, suggesting a specific sensor fault rather than ambient heating.", "C15-C06: Kitchen sensor spikes significantly higher than living_room during AC operation, indicating potential sensor saturation or offset issues compared to the main living area.", "Cross-validation needed: Comparing these chunks against 'empty' state logs to confirm if the high temperatures persist without heat sources present."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"All sensors are functioning correctly, recording a uniform rise in ambient temperature due to external factors (e.g., HVAC failure or solar gain) affecting the entire house simultaneously.\",\n      \"evidence\": [\"All room sensors show a consistent upward trend from ~23°C (represented as 230x) to ~25.3°C (represented as 253x).\", \"The relative ordering of temperatures between rooms remains stable throughout the log period.\"],\n      \"weaknesses\": [\"The absolute values (e.g., 2530) exceed standard Celsius ranges for indoor environments unless using a specific scaled unit not indicated, suggesting a potential logging artifact rather than physical reality.\", \"Even if scaled, the magnitude of change (~2.3 units over 7 hours) is rapid and synchronized across all zones without any localized heat source activation.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"The second_bedroom_temp_sensor is suffering from severe calibration drift or firmware overflow, reporting values significantly higher than other valid sensors.\",\n      \"threat_type\": \"Sensor Calibration Failure / Data Integrity Error\",\n      \"evidence\": [\"At 01:30, while living_room drops to 2301 and master_bedroom rises to 2316, second_bedroom jumps anomalously to 2317, breaking the initial cluster stability.\", \"From 02:40 onwards, second_bedroom readings consistently diverge upwards, reaching 2523 by 07:35, while kitchen and living_room stabilize around 2520-2529.\", \"The gap widens specifically when occupancy events occur in other rooms (e.g., entrance at 07:24), but not in the second bedroom until 07:48, yet the temperature anomaly persists regardless of local occupancy changes.\", \"The 'MeasuredValue' attribute appears to be scaling incorrectly or hitting a saturation point unique to this sensor node compared to peers.\"],\n      \"weaknesses\": [\"There is no direct evidence that the *other* sensors are wrong; they could also be drifting together if the entire system clock or base offset is corrupted globally.\"],\n      \"additional_note\": \"Given the triage output suggests 'Temperature drift', A1 is the strongest candidate. The evidence shows second_bedroom leading the pack in value increase after the initial synchronization phase, indicating a local fault.\"\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"Divergence in rate of change: After 02:40, second_bedroom continues to climb steadily (e.g., 2352 -> 2523), whereas kitchen and living_room fluctuate more erratically or plateau slightly earlier.\",\n    \"Occupancy Context Mismatch: At 07:48, occupancy detects presence in second_bedroom, yet the temperature spike was already established before this event, ruling out body heat as the primary cause for the anomalous high reading.\",\n    \"Cross-Sensor Discrepancy: At 07:35, second_bedroom reads 2523 while living_room reads 2530. While close, the trajectory of second_bedroom (steady linear ascent) contrasts with the noisy fluctuations of others, pointing to a stuck incrementer or offset error specific to the second bedroom node.\"\n  ],\n  \"missing_information\": [\n    \"The definition of the 'MeasuredValue' unit (Celsius, Fahrenheit, Kelvin, or an internal integer scale?) to determine if 2300-2530 represents a realistic temperature or a raw register value overflow.\",\n    \"Historical baseline data for these specific sensors prior to 2026-06-08 to confirm if the current trajectory is a new deviation or part of a long-term degradation pattern.\",\n    \"Status flags for the second_bedroom sensor (e.g., BatteryLevel, SignalStrength, SelfTestResult) which might indicate power issues causing intermittent calibration loss.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "All sensors are functioning correctly, recording a uniform rise in ambient temperature due to external factors (e.g., HVAC failure or solar gain) affecting the entire house simultaneously.", "evidence": ["All room sensors show a consistent upward trend from ~23°C (represented as 230x) to ~25.3°C (represented as 253x).", "The relative ordering of temperatures between rooms remains stable throughout the log period."], "weaknesses": ["The absolute values (e.g., 2530) exceed standard Celsius ranges for indoor environments unless using a specific scaled unit not indicated, suggesting a potential logging artifact rather than physical reality.", "Even if scaled, the magnitude of change (~2.3 units over 7 hours) is rapid and synchronized across all zones without any localized heat source activation."]}], "anomaly_hypotheses": [{"id": "A1", "description": "The second_bedroom_temp_sensor is suffering from severe calibration drift or firmware overflow, reporting values significantly higher than other valid sensors.", "threat_type": "Sensor Calibration Failure / Data Integrity Error", "evidence": ["At 01:30, while living_room drops to 2301 and master_bedroom rises to 2316, second_bedroom jumps anomalously to 2317, breaking the initial cluster stability.", "From 02:40 onwards, second_bedroom readings consistently diverge upwards, reaching 2523 by 07:35, while kitchen and living_room stabilize around 2520-2529.", "The gap widens specifically when occupancy events occur in other rooms (e.g., entrance at 07:24), but not in the second bedroom until 07:48, yet the temperature anomaly persists regardless of local occupancy changes.", "The 'MeasuredValue' attribute appears to be scaling incorrectly or hitting a saturation point unique to this sensor node compared to peers."], "weaknesses": ["There is no direct evidence that the *other* sensors are wrong; they could also be drifting together if the entire system clock or base offset is corrupted globally."], "additional_note": "Given the triage output suggests 'Temperature drift', A1 is the strongest candidate. The evidence shows second_bedroom leading the pack in value increase after the initial synchronization phase, indicating a local fault."}], "most_discriminative_evidence": ["Divergence in rate of change: After 02:40, second_bedroom continues to climb steadily (e.g., 2352 -> 2523), whereas kitchen and living_room fluctuate more erratically or plateau slightly earlier.", "Occupancy Context Mismatch: At 07:48, occupancy detects presence in second_bedroom, yet the temperature spike was already established before this event, ruling out body heat as the primary cause for the anomalous high reading.", "Cross-Sensor Discrepancy: At 07:35, second_bedroom reads 2523 while living_room reads 2530. While close, the trajectory of second_bedroom (steady linear ascent) contrasts with the noisy fluctuations of others, pointing to a stuck incrementer or offset error specific to the second bedroom node."], "missing_information": ["The definition of the 'MeasuredValue' unit (Celsius, Fahrenheit, Kelvin, or an internal integer scale?) to determine if 2300-2530 represents a realistic temperature or a raw register value overflow.", "Historical baseline data for these specific sensors prior to 2026-06-08 to confirm if the current trajectory is a new deviation or part of a long-term degradation pattern.", "Status flags for the second_bedroom sensor (e.g., BatteryLevel, SignalStrength, SelfTestResult) which might indicate power issues causing intermittent calibration loss."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C06\", \"C07\", \"C08\"],\n  \"missing_checks\": [\"Verify data unit definition for values >2000 (Overflow vs Real Temp)\", \"Check sensor status flags (Battery/Signal) in C06-C08\", \"Cross-reference with 'empty room' logs in later chunks to rule out delayed HVAC response\"],\n  \"supervisor_notes\": [\n    \"The analysis correctly identifies the divergence pattern but relies heavily on early chunks (C01-C05) and Triage suggestions.\",\n    \"Triage output incorrectly included C15-C06 as a chunk range; evidence suggests C06 is critical for observing the stabilization of other sensors mentioned by the investigator.\",\n    \"Missing chunks C06-C08 are necessary to confirm if the anomaly persists after the initial spike or if it resolves, and to check for late-stage occupancy events that might explain the discrepancy.\",\n    \"Crucially, the raw values (~2300-2530) are physically unrealistic for Celsius without knowing the unit scale. This fundamental ambiguity must be resolved before concluding 'calibration drift'; this requires metadata often found in the full log sequence.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C06", "C07", "C08"], "missing_checks": ["Verify data unit definition for values >2000 (Overflow vs Real Temp)", "Check sensor status flags (Battery/Signal) in C06-C08", "Cross-reference with 'empty room' logs in later chunks to rule out delayed HVAC response"], "supervisor_notes": ["The analysis correctly identifies the divergence pattern but relies heavily on early chunks (C01-C05) and Triage suggestions.", "Triage output incorrectly included C15-C06 as a chunk range; evidence suggests C06 is critical for observing the stabilization of other sensors mentioned by the investigator.", "Missing chunks C06-C08 are necessary to confirm if the anomaly persists after the initial spike or if it resolves, and to check for late-stage occupancy events that might explain the discrepancy.", "Crucially, the raw values (~2300-2530) are physically unrealistic for Celsius without knowing the unit scale. This fundamental ambiguity must be resolved before concluding 'calibration drift'; this requires metadata often found in the full log sequence."]}, "preview_triage_prompt": "## Query\n请检查以下设备状态历史，判断 second_bedroom 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 399,\n    \"master_bedroom\": 336,\n    \"second_bedroom\": 341,\n    \"kitchen\": 298,\n    \"bathroom\": 52,\n    \"entrance\": 230\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1154,\n    \"Occupancy\": 473,\n    \"OnOff\": 14,\n    \"StateValue\": 5,\n    \"LockState\": 4,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 473,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-08T00:00:00\",\n    \"end_ts\": \"2026-06-08T01:20:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 20,\n      \"master_bedroom\": 19,\n      \"second_bedroom\": 19,\n      \"kitchen\": 16,\n      \"bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"master_bedroom_occupancy\"\n    ],\n    \"alarmish_count\": 15,\n    \"preview_lines\": [\n      \"[2026-06-08T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2271\",\n      \"[2026-06-08T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2267\",\n      \"[2026-06-08T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2269\",\n      \"[2026-06-08T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2271\",\n      \"[2026-06-08T00:00:00] living_room_occupancy | Occ", "preview_verifier_prompt": "## Query\n请检查以下设备状态历史，判断 second_bedroom 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Triage\n{\n  \"latent_task_profile\": \"device-health\",\n  \"focus_rooms\": [\"second_bedroom\", \"kitchen\", \"living_room\"],\n  \"focus_devices\": [\n    \"second_bedroom_temp_sensor\",\n    \"kitchen_temp_sensor\",\n    \"living_room_temp_sensor\"\n  ],\n  \"focus_chunk_ids\": [\"C01\", \"C02\", \"C03\", \"C04\", \"C05\", \"C15\", \"C16\"],\n  \"suspected_patterns\": [\n    \"Temperature drift indicating calibration failure or sensor aging\",\n    \"Discrepancy between reported temperature and occupancy context (e.g., high temp when room is empty)\"\n  ],\n  \"why_these_chunks\": [\n    \"C01-C05: Show a progressive, unrealistic rise in second_bedroom_temp_sensor readings (from ~2270 to ~2530) while other sensors remain relatively stable or follow a different curve, suggesting a specific sensor fault rather than ambient heating.\",\n    \"C15-C06: Kitchen sensor spikes significantly higher than living_room during AC operation, indicating potential sensor saturation or offset issues compared to the main living area.\",\n    \"Cross-validation needed: Comparing these chunks against 'empty' state logs to confirm if the high temperatures persist without heat sources present.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"All sensors are functioning correctly, recording a uniform rise in ambient temperature due to external factors (e.g., HVAC failure or solar gain) affecting the entire house simultaneously.\",\n      \"evidence\": [\"All room sensors show a consistent upward trend from ~23°C (represented as 230x) to ~25.3°C (represented as 253x).\", \"The relative ordering of temperatures between rooms remains stable throughout the log period.\"],\n      \"weaknesses\": [\"The absolute values (e.g., 2530) exceed standard Celsius ranges for indoor environments unless using a specific scaled unit not indicated, suggesting a potential logging artifact rather than physical reality.\", \"Even if scaled, the magnitude of change (~2.3 units over 7 hours) is rapid and synchronized across all zones without any localized heat source activation.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"The second_bedroom_temp_sensor is suffering from severe calibration drift or firmware overflow, reporting values significantly higher than other valid sensors.\",\n      \"threat_type\": \"Sensor Calibration Failure / Data Integrity Error\",\n      \"evidence\": [\"At 01:30, while living_room drops to 2301 an"}}
{"episode_id": "SQ2_FP_A_0329", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq2\\SQ2_FP_A_0329.json", "metadata": {"sq_type": "SQ2", "sq_name": "单事件安全判断", "variant": "FP", "layout_id": "A", "layout_name": "一室一厅 (Studio/1BR)", "profile_id": "young_professional", "base_date": "2026-06-02T00:00:00", "seed": 20260958, "scenario_id": "INS-02", "total_events": 1127, "anomaly_events_count": 4}, "ground_truth": {"scenario_id": "INS-02-FP", "scenario_name": "INS-02-FP: 住户忘记密码/手指脏", "category": "intrusion", "is_anomaly": false, "threat_type": "none", "key_difference": "只有1-2次错误（非连续多次），最终成功解锁且 UserIndex 是合法用户", "difficulty_score": 8, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 3, "D2_signal_directness": 1, "D3_cross_device": 1, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "living_room", "injection_time": "2026-06-02T07:23:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"The kitchen temperature sensor is reporting physically impossible values (2400K-2700K) for an extended period, indicating a severe hardware malfunction or calibration failure rather than a real environmental hazard.\",\n  \"reasoning\": [\n      \"Analysis of Chunks C10 and C11 reveals sustained readings from the kitchen_temp_sensor ranging between 2578K and 2710K, which equates to temperatures exceeding 2300°C. This is physically impossible for any indoor residential environment or standard cooking appliance.\",\n      \"While living room and bedroom sensors show consistent, plausible readings (~2300K-2500K), the kitchen sensor data shows a clear divergence that persists even after cooking activities ceased and temperatures normalized in other rooms, confirming the anomaly is isolated to this specific device.\",\n      \"The temporal correlation with 'Occupancy=1' creates a safety paradox where the system would attempt to cool a non-existent molten environment, confirming the data integrity failure rather than a genuine fire event.\"\n    ],\n  \"key_evidence\": [\n      \"Kitchen sensor reading of 2710K (approx. 2436°C) at 18:40:00 in Chunk C10.\",\n      \"Consistent normal temperature readings (~2300K) from adjacent living_room_temp_sensor during the same timeframe, isolating the fault to the kitchen sensor.\"\n    ],\n  \"recommended_actions\": [\n      \"Immediately disable the kitchen_temp_sensor in the automation logic to prevent erroneous HVAC commands.\",\n      \"Schedule physical inspection and replacement of the kitchen temperature sensor due to internal component failure.\",\n      \"Verify the integrity of the sensor's wiring and power supply to rule out external electrical noise causing the drift.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "The kitchen temperature sensor is reporting physically impossible values (2400K-2700K) for an extended period, indicating a severe hardware malfunction or calibration failure rather than a real environmental hazard.", "reasoning": ["Analysis of Chunks C10 and C11 reveals sustained readings from the kitchen_temp_sensor ranging between 2578K and 2710K, which equates to temperatures exceeding 2300°C. This is physically impossible for any indoor residential environment or standard cooking appliance.", "While living room and bedroom sensors show consistent, plausible readings (~2300K-2500K), the kitchen sensor data shows a clear divergence that persists even after cooking activities ceased and temperatures normalized in other rooms, confirming the anomaly is isolated to this specific device.", "The temporal correlation with 'Occupancy=1' creates a safety paradox where the system would attempt to cool a non-existent molten environment, confirming the data integrity failure rather than a genuine fire event."], "key_evidence": ["Kitchen sensor reading of 2710K (approx. 2436°C) at 18:40:00 in Chunk C10.", "Consistent normal temperature readings (~2300K) from adjacent living_room_temp_sensor during the same timeframe, isolating the fault to the kitchen sensor."], "recommended_actions": ["Immediately disable the kitchen_temp_sensor in the automation logic to prevent erroneous HVAC commands.", "Schedule physical inspection and replacement of the kitchen temperature sensor due to internal component failure.", "Verify the integrity of the sensor's wiring and power supply to rule out external electrical noise causing the drift."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 60.31420922279358, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1127, "chunk_count": 15, "signals": {"room_activity": {"living_room": 401, "bedroom": 354, "kitchen": 298, "bathroom": 57, "entrance": 17}, "attribute_frequency": {"MeasuredValue": 866, "Occupancy": 222, "OnOff": 18, "StateValue": 6, "LockState": 4, "CurrentPositionLiftPercent100ths": 2, "SystemMode": 1, "OperationalState": 1, "CurrentLevel": 1}, "lock_state_flips": 4, "occupancy_events": 222, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"single-event-safety | composite-safety\",\n  \"focus_rooms\": [\"entrance\", \"kitchen\", \"living_room\"],\n  \"focus_devices\": [\"front_door_lock\", \"front_door_contact\", \"kitchen_temp_sensor\", \"living_room_ac\", \"living_room_occupancy\"],\n  \"focus_chunk_ids\": [\"C04\", \"C10\", \"C11\"],\n  \"suspected_patterns\": [\n    \"lock_operation_failure_preceding_entry\",\n    \"abnormal_temperature_elevation_during_high_activity\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C04 captures a critical sequence: a LockOperationError immediately followed by a successful lock operation and door contact flip, indicating potential tampering or malfunction upon entry.\",\n    \"Chunks C10 and C11 show sustained high temperatures in the kitchen (2578K-2630K) coinciding with living room occupancy and AC activation, suggesting a heating anomaly or sensor calibration drift that requires immediate health verification.\",\n    \"The combination of mechanical failure at the perimeter (entrance) and thermal anomalies inside suggests a multi-vector safety event requiring cross-referencing.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "single-event-safety | composite-safety", "focus_rooms": ["entrance", "kitchen", "living_room"], "focus_devices": ["front_door_lock", "front_door_contact", "kitchen_temp_sensor", "living_room_ac", "living_room_occupancy"], "focus_chunk_ids": ["C04", "C10", "C11"], "suspected_patterns": ["lock_operation_failure_preceding_entry", "abnormal_temperature_elevation_during_high_activity"], "why_these_chunks": ["Chunk C04 captures a critical sequence: a LockOperationError immediately followed by a successful lock operation and door contact flip, indicating potential tampering or malfunction upon entry.", "Chunks C10 and C11 show sustained high temperatures in the kitchen (2578K-2630K) coinciding with living room occupancy and AC activation, suggesting a heating anomaly or sensor calibration drift that requires immediate health verification.", "The combination of mechanical failure at the perimeter (entrance) and thermal anomalies inside suggests a multi-vector safety event requiring cross-referencing."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The event represents a series of benign household activities: a resident returning home, cooking dinner in the kitchen, and normal temperature fluctuations due to appliance usage.\",\n      \"evidence\": [\n        \"C04 shows a standard entry sequence: LockOperationError followed immediately by successful locking and door contact flip, consistent with user interaction or minor sensor noise.\",\n        \"C10 and C11 show typical daily patterns: AC activation upon occupancy (18:12), cooking surface usage (18:49), and dishwasher operation (20:13).\",\n        \"Room activity counts are high in living room and bedroom, suggesting occupied residential use rather than intrusion.\"\n      ],\n      \"weaknesses\": [\n        \"Kitchen temperature values in C10 (e.g., 2709) are physically impossible for ambient air sensors, indicating potential data corruption or mislabeling of device type.\",\n        \"The sequence in C04 involves an error state that, while common, is a deviation from ideal system behavior requiring verification.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Critical Sensor Malfunction or Calibration Drift creating false safety signals; specifically, the kitchen temperature sensor reports values >2500K (approx. 2227°C) which indicates either total sensor failure, exposure to fire, or severe data spoofing.\",\n      \"threat_type\": \"Environmental Hazard / Data Integrity Failure\",\n      \"evidence\": [\n        \"C10 records kitchen_temp_sensor values ranging from 2578K to 2710K between 18:15 and 19:35. These values correspond to temperatures exceeding 2300°C, far beyond any domestic environment or even a gas flame.\",\n        \"This anomaly coincides with reported 'Occupancy=1' and 'AC Activation', creating a logical contradiction where the thermostat attempts to cool an area that is effectively molten.\",\n        \"The sensor returns 'None' intermittently (18:50, 19:54) during these extreme readings, suggesting hardware saturation or communication loss.\"\n      ],\n      \"weaknesses\": [\n        \"No concurrent fire alarms or smoke detector events are explicitly logged in the provided chunks to confirm physical combustion.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Perimeter Security Compromise involving lock manipulation and unauthorized entry simulation.\",\n      \"threat_type\": \"Physical Intrusion / Bypass Attempt\",\n      \"evidence\": [\n        \"C04 logs a 'LockOperationError' at 07:23:00 immediately preceding a successful lock operation and door contact flip, which may indicate a forced entry attempt or electronic tampering before the door was secured.\",\n        \"Multiple lock_state_flips (4 total) recorded in structured signals suggest frequent state changes inconsistent with a single entry/exit event.\"\n      ],\n      \"weaknesses\": [\n        \"The subsequent successful lock operation and auto-lock suggests the system recovered or the event was authorized by a legitimate user (UserIndex=1).\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The absolute magnitude of the kitchen temperature readings in Chunk C10 (2709K = ~2436°C) is the primary discriminator. This value is physically impossible for indoor air and rules out 'normal cooking heat' as an explanation, pointing definitively to sensor failure, hardware malfunction, or malicious data injection.\",\n    \"The temporal correlation between the impossible temperature spike and the presence of occupants ('Occupancy=1') creates an immediate health/safety paradox not explained by standard HVAC logic.\"\n  ],\n  \"missing_information\": [\n    \"Raw voltage/current readings or signal integrity metrics for the kitchen_temp_sensor to determine if the reading is electrical noise or a valid (but impossible) measurement.\",\n    \"Logs from other thermal sensors (smoke detectors, wall-mounted thermostats) to see if they detected the alleged 2700°C environment.\",\n    \"Video footage or motion detection specifics around the entrance during the 07:23:00 error event to verify if a person was present during the lock error.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The event represents a series of benign household activities: a resident returning home, cooking dinner in the kitchen, and normal temperature fluctuations due to appliance usage.", "evidence": ["C04 shows a standard entry sequence: LockOperationError followed immediately by successful locking and door contact flip, consistent with user interaction or minor sensor noise.", "C10 and C11 show typical daily patterns: AC activation upon occupancy (18:12), cooking surface usage (18:49), and dishwasher operation (20:13).", "Room activity counts are high in living room and bedroom, suggesting occupied residential use rather than intrusion."], "weaknesses": ["Kitchen temperature values in C10 (e.g., 2709) are physically impossible for ambient air sensors, indicating potential data corruption or mislabeling of device type.", "The sequence in C04 involves an error state that, while common, is a deviation from ideal system behavior requiring verification."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Critical Sensor Malfunction or Calibration Drift creating false safety signals; specifically, the kitchen temperature sensor reports values >2500K (approx. 2227°C) which indicates either total sensor failure, exposure to fire, or severe data spoofing.", "threat_type": "Environmental Hazard / Data Integrity Failure", "evidence": ["C10 records kitchen_temp_sensor values ranging from 2578K to 2710K between 18:15 and 19:35. These values correspond to temperatures exceeding 2300°C, far beyond any domestic environment or even a gas flame.", "This anomaly coincides with reported 'Occupancy=1' and 'AC Activation', creating a logical contradiction where the thermostat attempts to cool an area that is effectively molten.", "The sensor returns 'None' intermittently (18:50, 19:54) during these extreme readings, suggesting hardware saturation or communication loss."], "weaknesses": ["No concurrent fire alarms or smoke detector events are explicitly logged in the provided chunks to confirm physical combustion."]}, {"id": "A2", "description": "Perimeter Security Compromise involving lock manipulation and unauthorized entry simulation.", "threat_type": "Physical Intrusion / Bypass Attempt", "evidence": ["C04 logs a 'LockOperationError' at 07:23:00 immediately preceding a successful lock operation and door contact flip, which may indicate a forced entry attempt or electronic tampering before the door was secured.", "Multiple lock_state_flips (4 total) recorded in structured signals suggest frequent state changes inconsistent with a single entry/exit event."], "weaknesses": ["The subsequent successful lock operation and auto-lock suggests the system recovered or the event was authorized by a legitimate user (UserIndex=1)."]}], "most_discriminative_evidence": ["The absolute magnitude of the kitchen temperature readings in Chunk C10 (2709K = ~2436°C) is the primary discriminator. This value is physically impossible for indoor air and rules out 'normal cooking heat' as an explanation, pointing definitively to sensor failure, hardware malfunction, or malicious data injection.", "The temporal correlation between the impossible temperature spike and the presence of occupants ('Occupancy=1') creates an immediate health/safety paradox not explained by standard HVAC logic."], "missing_information": ["Raw voltage/current readings or signal integrity metrics for the kitchen_temp_sensor to determine if the reading is electrical noise or a valid (but impossible) measurement.", "Logs from other thermal sensors (smoke detectors, wall-mounted thermostats) to see if they detected the alleged 2700°C environment.", "Video footage or motion detection specifics around the entrance during the 07:23:00 error event to verify if a person was present during the lock error."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C03\", \"C05\"],\n  \"missing_checks\": [\n    \"Verify raw signal integrity or voltage readings for kitchen_temp_sensor in C10 to rule out electrical noise/spike.\",\n    \"Cross-reference logs from smoke detectors and other thermal sensors to confirm the impossibility of a 2700°C indoor environment.\",\n    \"Review video footage or specific motion data around entrance during the 07:23:00 LockOperationError event.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identifies the critical anomaly (physically impossible temperature) and the potential security breach (lock error).\",\n    \"However, the current evidence is insufficient because it relies solely on the suspect chunks (C04, C10, C11) without corroborating data from surrounding timeframes or alternative sensor types.\",\n    \"Chunk C03 should be checked to see if the lock error was an isolated incident or part of a pattern leading up to it.\",\n    \"Chunk C05 is needed to establish the baseline status immediately following the kitchen anomaly to determine if conditions normalized or persisted.\",\n    \"Without checking additional thermal sensors or raw signal data, we cannot definitively distinguish between catastrophic failure, sensor spoofing, or simple calibration drift.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C03", "C05"], "missing_checks": ["Verify raw signal integrity or voltage readings for kitchen_temp_sensor in C10 to rule out electrical noise/spike.", "Cross-reference logs from smoke detectors and other thermal sensors to confirm the impossibility of a 2700°C indoor environment.", "Review video footage or specific motion data around entrance during the 07:23:00 LockOperationError event."], "supervisor_notes": ["The analysis correctly identifies the critical anomaly (physically impossible temperature) and the potential security breach (lock error).", "However, the current evidence is insufficient because it relies solely on the suspect chunks (C04, C10, C11) without corroborating data from surrounding timeframes or alternative sensor types.", "Chunk C03 should be checked to see if the lock error was an isolated incident or part of a pattern leading up to it.", "Chunk C05 is needed to establish the baseline status immediately following the kitchen anomaly to determine if conditions normalized or persisted.", "Without checking additional thermal sensors or raw signal data, we cannot definitively distinguish between catastrophic failure, sensor spoofing, or simple calibration drift."]}, "preview_triage_prompt": "## Query\n以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。\n\n## Layout\nLayout: 一室一厅 (Studio/1BR)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅台灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 401,\n    \"bedroom\": 354,\n    \"kitchen\": 298,\n    \"bathroom\": 57,\n    \"entrance\": 17\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 866,\n    \"Occupancy\": 222,\n    \"OnOff\": 18,\n    \"StateValue\": 6,\n    \"LockState\": 4,\n    \"CurrentPositionLiftPercent100ths\": 2,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 222,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-02T00:00:00\",\n    \"end_ts\": \"2026-06-02T01:50:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 27,\n      \"bedroom\": 27,\n      \"kitchen\": 22,\n      \"bathroom\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"bathroom_occupancy\"\n    ],\n    \"alarmish_count\": 12,\n    \"preview_lines\": [\n      \"[2026-06-02T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2274\",\n      \"[2026-06-02T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2165\",\n      \"[2026-06-02T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2271\",\n      \"[2026-06-02T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-02T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-02T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-02T00:05:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2276\",\n      \"[2026-06-02T00:05:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2178\",\n      \"[2026-06-02T00:05:00] kitchen_temp_sensor | Temperature", "preview_verifier_prompt": "## Query\n以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。\n\n## Triage\n{\n  \"latent_task_profile\": \"single-event-safety | composite-safety\",\n  \"focus_rooms\": [\"entrance\", \"kitchen\", \"living_room\"],\n  \"focus_devices\": [\"front_door_lock\", \"front_door_contact\", \"kitchen_temp_sensor\", \"living_room_ac\", \"living_room_occupancy\"],\n  \"focus_chunk_ids\": [\"C04\", \"C10\", \"C11\"],\n  \"suspected_patterns\": [\n    \"lock_operation_failure_preceding_entry\",\n    \"abnormal_temperature_elevation_during_high_activity\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C04 captures a critical sequence: a LockOperationError immediately followed by a successful lock operation and door contact flip, indicating potential tampering or malfunction upon entry.\",\n    \"Chunks C10 and C11 show sustained high temperatures in the kitchen (2578K-2630K) coinciding with living room occupancy and AC activation, suggesting a heating anomaly or sensor calibration drift that requires immediate health verification.\",\n    \"The combination of mechanical failure at the perimeter (entrance) and thermal anomalies inside suggests a multi-vector safety event requiring cross-referencing.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The event represents a series of benign household activities: a resident returning home, cooking dinner in the kitchen, and normal temperature fluctuations due to appliance usage.\",\n      \"evidence\": [\n        \"C04 shows a standard entry sequence: LockOperationError followed immediately by successful locking and door contact flip, consistent with user interaction or minor sensor noise.\",\n        \"C10 and C11 show typical daily patterns: AC activation upon occupancy (18:12), cooking surface usage (18:49), and dishwasher operation (20:13).\",\n        \"Room activity counts are high in living room and bedroom, suggesting occupied residential use rather than intrusion.\"\n      ],\n      \"weaknesses\": [\n        \"Kitchen temperature values in C10 (e.g., 2709) are physically impossible for ambient air sensors, indicating potential data corruption or mislabeling of device type.\",\n        \"The sequence in C04 involves an error state that, while common, is a deviation from ideal system behavior requiring verification.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Critical Sensor Malfunction or Calibration Drift creating false safety signals; specifically, the kitchen temperature sensor reports values >2500K (approx. 2227°C) which"}}
{"episode_id": "SQ1_TP_B_0011", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq1\\SQ1_TP_B_0011.json", "metadata": {"sq_type": "SQ1", "sq_name": "设备健康诊断", "variant": "TP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "family_with_children", "base_date": "2026-06-08T00:00:00", "seed": 20260640, "scenario_id": "DF-05", "total_events": 1838, "anomaly_events_count": 3}, "ground_truth": {"scenario_id": "DF-05", "scenario_name": "烟雾报警器硬件故障", "category": "device_fault", "is_anomaly": true, "threat_type": "safety_device_failure", "key_evidence": ["HardwareFaultAlert = true，设备自检发现硬件问题"], "expected_response": "通知住户该区域烟雾报警器失灵，建议立即更换，期间注意防火", "difficulty_score": 6, "difficulty_level": 1, "difficulty_label": "L1_basic_detection", "difficulty_dimensions": {"D1_evidence_count": 1, "D2_signal_directness": 1, "D3_cross_device": 1, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "kitchen", "injection_time": "2026-06-08T18:05:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"The kitchen temperature sensor has suffered a hardware failure or communication loss, indicated by erratic readings prior to the incident and a definitive transition to 'None' immediately following stove activation.\",\n  \"reasoning\": [\n      \"Step 1: Baseline analysis of chunks C00/C01 shows the sensor was operational but exhibited higher noise/instability compared to other room sensors (e.g., jumping between 2312-2327), suggesting early-stage degradation.\",\n      \"Step 2: Chunk C16 reveals a critical sequence where the `kitchen_smoke_alarm` logged a `HardwareFaultAlert` at 18:05:00, coinciding with a general drop in temperatures across all sensors, indicating a potential shared power or environmental stress event.\",\n      \"Step 3: The most conclusive evidence is at 18:32:00 in chunk C16; immediately after the `kitchen_cook_surface` turned ON at 18:31:30, the `kitchen_temp_sensor` value dropped from 2300 to `None`. This instantaneous data loss signifies a hard sensor failure or disconnection rather than normal drift or calibration error.\",\n      \"Step 4: Although the sensor briefly returned a value at 18:35:00 (2297) and again at 18:55:00 (2306), these intermittent recoveries are characteristic of unstable failing hardware attempting to reconnect before permanent failure or reset.\",\n      \"Step 5: Chunk C17 confirms the instability persists, with another instance of `None` at 18:53:00, solidifying the diagnosis of an intermittent but severe malfunction.\"\n    ],\n    \"key_evidence\": [\n      \"At 18:32:00, the sensor reading changed abruptly from a valid number (2300) to 'None' exactly one minute after the cooking surface was activated.\",\n      \"A concurrent 'HardwareFaultAlert' was logged on the adjacent kitchen smoke alarm at 18:05:00, suggesting a shared circuit issue or environmental trigger affecting multiple kitchen devices.\",\n      \"The sensor displayed erratic fluctuations (e.g., 2312 -> 2327 -> 2317) in minutes preceding the total failure, which is inconsistent with stable sensor behavior.\"\n    ],\n    \"recommended_actions\": [\n      \"Immediately replace the kitchen temperature sensor as it is no longer reliable for monitoring high-temperature events during cooking.\",\n      \"Inspect the kitchen's power distribution and check the status of the smoke alarm to ensure the fault was not due to a broader electrical surge affecting the zone.\",\n      \"Review historical logs for any other kitchen appliances that may have failed simultaneously to determine if this was a systemic power issue.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "The kitchen temperature sensor has suffered a hardware failure or communication loss, indicated by erratic readings prior to the incident and a definitive transition to 'None' immediately following stove activation.", "reasoning": ["Step 1: Baseline analysis of chunks C00/C01 shows the sensor was operational but exhibited higher noise/instability compared to other room sensors (e.g., jumping between 2312-2327), suggesting early-stage degradation.", "Step 2: Chunk C16 reveals a critical sequence where the `kitchen_smoke_alarm` logged a `HardwareFaultAlert` at 18:05:00, coinciding with a general drop in temperatures across all sensors, indicating a potential shared power or environmental stress event.", "Step 3: The most conclusive evidence is at 18:32:00 in chunk C16; immediately after the `kitchen_cook_surface` turned ON at 18:31:30, the `kitchen_temp_sensor` value dropped from 2300 to `None`. This instantaneous data loss signifies a hard sensor failure or disconnection rather than normal drift or calibration error.", "Step 4: Although the sensor briefly returned a value at 18:35:00 (2297) and again at 18:55:00 (2306), these intermittent recoveries are characteristic of unstable failing hardware attempting to reconnect before permanent failure or reset.", "Step 5: Chunk C17 confirms the instability persists, with another instance of `None` at 18:53:00, solidifying the diagnosis of an intermittent but severe malfunction."], "key_evidence": ["At 18:32:00, the sensor reading changed abruptly from a valid number (2300) to 'None' exactly one minute after the cooking surface was activated.", "A concurrent 'HardwareFaultAlert' was logged on the adjacent kitchen smoke alarm at 18:05:00, suggesting a shared circuit issue or environmental trigger affecting multiple kitchen devices.", "The sensor displayed erratic fluctuations (e.g., 2312 -> 2327 -> 2317) in minutes preceding the total failure, which is inconsistent with stable sensor behavior."], "recommended_actions": ["Immediately replace the kitchen temperature sensor as it is no longer reliable for monitoring high-temperature events during cooking.", "Inspect the kitchen's power distribution and check the status of the smoke alarm to ensure the fault was not due to a broader electrical surge affecting the zone.", "Review historical logs for any other kitchen appliances that may have failed simultaneously to determine if this was a systemic power issue."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": true, "reasoning_steps": 5, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 64.40473532676697, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1838, "chunk_count": 23, "signals": {"room_activity": {"living_room": 402, "master_bedroom": 516, "second_bedroom": 336, "kitchen": 306, "bathroom": 48, "entrance": 230}, "attribute_frequency": {"MeasuredValue": 1156, "Occupancy": 644, "OnOff": 15, "StateValue": 7, "LockState": 5, "SystemMode": 1, "HardwareFaultAlert": 1, "ExpressedState": 1, "OperationalState": 1, "CurrentPositionLiftPercent100ths": 1}, "lock_state_flips": 5, "occupancy_events": 644, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"device-health\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"kitchen_smoke_co_alarm\", \"kitchen_contact_sensor\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C16\"],\n  \"suspected_patterns\": [\n    \"Temperature measurement drift (values starting at ~22.7°C rising to >25°C without corresponding HVAC activation)\",\n    \"Potential sensor calibration error or battery depletion causing false high readings\",\n    \"Lack of correlation between temperature spikes and appliance usage (dishwasher/cook_surface) events\"\n  ],\n  \"why_these_chunks\": [\n    \"C00/C01: Initial baseline establishment showing a consistent upward trend in kitchen temperature relative to other rooms, suggesting early-stage sensor drift.\",\n    \"C16: Contains non-temperature events for the kitchen area (Dishwasher state changes), allowing cross-validation to see if temperature spikes correlate with actual heat generation from appliances.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "device-health", "focus_rooms": ["kitchen"], "focus_devices": ["kitchen_temp_sensor", "kitchen_smoke_co_alarm", "kitchen_contact_sensor"], "focus_chunk_ids": ["C00", "C01", "C16"], "suspected_patterns": ["Temperature measurement drift (values starting at ~22.7°C rising to >25°C without corresponding HVAC activation)", "Potential sensor calibration error or battery depletion causing false high readings", "Lack of correlation between temperature spikes and appliance usage (dishwasher/cook_surface) events"], "why_these_chunks": ["C00/C01: Initial baseline establishment showing a consistent upward trend in kitchen temperature relative to other rooms, suggesting early-stage sensor drift.", "C16: Contains non-temperature events for the kitchen area (Dishwasher state changes), allowing cross-validation to see if temperature spikes correlate with actual heat generation from appliances."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The kitchen temperature sensor is experiencing a delayed thermal response due to high ambient room temperature (approx. 23°C baseline) rather than a hardware fault, as it tracks the general house warming trend.\",\n      \"evidence\": [\"In chunks C00 and C01, all sensors show values in the 2268-2359 range (scaled x10), indicating a consistent baseline of ~22.7°C - 23.6°C across the entire house.\", \"The kitchen sensor readings generally follow the trend of other rooms, albeit with slight lag or noise, suggesting environmental factors like external heat or HVAC inefficiency are affecting all zones uniformly.\"],\n      \"weaknesses\": [\"This hypothesis fails to explain the specific 'HardwareFaultAlert' generated by the smoke alarm at 18:05:00 in chunk C16.\", \"It cannot account for the sudden drop to `None` at 18:32:00 immediately after the stove was activated, which indicates a complete data loss event typical of sensor failure or power cycle, not just slow thermal response.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"The kitchen temperature sensor suffered a hardware failure or communication drop during active cooking usage, indicated by a fault alert and subsequent null reading.\",\n      \"threat_type\": \"Sensor Hardware Failure / Data Integrity Loss\",\n      \"evidence\": [\"At 18:05:00, the `kitchen_smoke_alarm` explicitly reports `HardwareFaultAlert = True` and `Event: HardwareFault()`. While this is on the smoke alarm, the proximity suggests a shared power bus or environmental stressor (overheat) affecting kitchen devices.\", \"At 18:31:30, the `kitchen_cook_surface` turns ON, initiating a heating event.\", \"Immediately following this, at 18:32:00, the `kitchen_temp_sensor` returns `TemperatureMeasurement.MeasuredValue = None`, a definitive sign of sensor disconnection, battery death, or internal error preventing measurement.\", \"Prior to the fault, the sensor showed erratic fluctuations (e.g., jumping from 2312 to 2327 to 2317 in minutes) compared to the smoother trends of other sensors, suggesting early instability before total failure.\"],\n      \"weaknesses\": [\"The specific error code 'HardwareFault' was logged on the *smoke* alarm, not directly on the temperature sensor, though they likely share a cause. It is possible the temp sensor failed silently without triggering its own explicit fault log in the provided snippet, relying instead on the missing value.\"]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"The kitchen sensor exhibits calibration drift or offset errors relative to the rest of the house, leading to inaccurate occupancy-based logic if used for climate control.\",\n      \"threat_type\": \"Calibration Error / Sensor Drift\",\n      \"evidence\": [\"In chunks C00/C01, while the master bedroom reaches ~23.4°C, the kitchen fluctuates between 22.8°C and 23.3°C even when the house is warming up, showing inconsistent tracking compared to the living room which rises more steadily to 23.6°C.\", \"During the evening event (C16), the kitchen sensor reads 2300 (23.0°C) while the living room is at 2316 (23.16°C) at the same timestamp, despite the kitchen being heated by the stove (activated at 18:31). A functional sensor should have read higher than the unheated living room during active cooking.\"],\n      \"weaknesses\": [\"The magnitude of deviation is relatively small (0.1-0.5°C), which might fall within normal tolerance for different room volumes unless strict precision is required.\", \"The most severe issue (the `None` value) is better explained by a hard failure (Hypothesis A1) than simple drift.\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The transition of `kitchen_temp_sensor` from a numeric value to `None` at 18:32:00 immediately after `kitchen_cook_surface` activation is the strongest evidence of a hard failure.\",\n    \"The concurrent `HardwareFaultAlert` on the kitchen smoke alarm at 18:05:00 provides context that the kitchen environment experienced a critical event likely causing the subsequent sensor failure.\",\n    \"The lack of temperature rise in the kitchen sensor during the active cooking period (18:31-18:38), while the living room continues to warm, contradicts the expected physical behavior of a working sensor.\"\n  ],\n  \"missing_information\": [\n    \"The specific error code or reason string associated with the `HardwareFault()` event on the smoke alarm to determine if it affected the power bus for the temperature sensor.\",\n    \"Historical logs from the minute prior to 18:32:00 to see if the temperature sensor was already reporting anomalous values or missed packets before dropping to `None`.\",\n    \"Power supply status or voltage readings for the kitchen circuit during the 18:32:00 event.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The kitchen temperature sensor is experiencing a delayed thermal response due to high ambient room temperature (approx. 23°C baseline) rather than a hardware fault, as it tracks the general house warming trend.", "evidence": ["In chunks C00 and C01, all sensors show values in the 2268-2359 range (scaled x10), indicating a consistent baseline of ~22.7°C - 23.6°C across the entire house.", "The kitchen sensor readings generally follow the trend of other rooms, albeit with slight lag or noise, suggesting environmental factors like external heat or HVAC inefficiency are affecting all zones uniformly."], "weaknesses": ["This hypothesis fails to explain the specific 'HardwareFaultAlert' generated by the smoke alarm at 18:05:00 in chunk C16.", "It cannot account for the sudden drop to `None` at 18:32:00 immediately after the stove was activated, which indicates a complete data loss event typical of sensor failure or power cycle, not just slow thermal response."]}], "anomaly_hypotheses": [{"id": "A1", "description": "The kitchen temperature sensor suffered a hardware failure or communication drop during active cooking usage, indicated by a fault alert and subsequent null reading.", "threat_type": "Sensor Hardware Failure / Data Integrity Loss", "evidence": ["At 18:05:00, the `kitchen_smoke_alarm` explicitly reports `HardwareFaultAlert = True` and `Event: HardwareFault()`. While this is on the smoke alarm, the proximity suggests a shared power bus or environmental stressor (overheat) affecting kitchen devices.", "At 18:31:30, the `kitchen_cook_surface` turns ON, initiating a heating event.", "Immediately following this, at 18:32:00, the `kitchen_temp_sensor` returns `TemperatureMeasurement.MeasuredValue = None`, a definitive sign of sensor disconnection, battery death, or internal error preventing measurement.", "Prior to the fault, the sensor showed erratic fluctuations (e.g., jumping from 2312 to 2327 to 2317 in minutes) compared to the smoother trends of other sensors, suggesting early instability before total failure."], "weaknesses": ["The specific error code 'HardwareFault' was logged on the *smoke* alarm, not directly on the temperature sensor, though they likely share a cause. It is possible the temp sensor failed silently without triggering its own explicit fault log in the provided snippet, relying instead on the missing value."]}, {"id": "A2", "description": "The kitchen sensor exhibits calibration drift or offset errors relative to the rest of the house, leading to inaccurate occupancy-based logic if used for climate control.", "threat_type": "Calibration Error / Sensor Drift", "evidence": ["In chunks C00/C01, while the master bedroom reaches ~23.4°C, the kitchen fluctuates between 22.8°C and 23.3°C even when the house is warming up, showing inconsistent tracking compared to the living room which rises more steadily to 23.6°C.", "During the evening event (C16), the kitchen sensor reads 2300 (23.0°C) while the living room is at 2316 (23.16°C) at the same timestamp, despite the kitchen being heated by the stove (activated at 18:31). A functional sensor should have read higher than the unheated living room during active cooking."], "weaknesses": ["The magnitude of deviation is relatively small (0.1-0.5°C), which might fall within normal tolerance for different room volumes unless strict precision is required.", "The most severe issue (the `None` value) is better explained by a hard failure (Hypothesis A1) than simple drift."]}], "most_discriminative_evidence": ["The transition of `kitchen_temp_sensor` from a numeric value to `None` at 18:32:00 immediately after `kitchen_cook_surface` activation is the strongest evidence of a hard failure.", "The concurrent `HardwareFaultAlert` on the kitchen smoke alarm at 18:05:00 provides context that the kitchen environment experienced a critical event likely causing the subsequent sensor failure.", "The lack of temperature rise in the kitchen sensor during the active cooking period (18:31-18:38), while the living room continues to warm, contradicts the expected physical behavior of a working sensor."], "missing_information": ["The specific error code or reason string associated with the `HardwareFault()` event on the smoke alarm to determine if it affected the power bus for the temperature sensor.", "Historical logs from the minute prior to 18:32:00 to see if the temperature sensor was already reporting anomalous values or missed packets before dropping to `None`.", "Power supply status or voltage readings for the kitchen circuit during the 18:32:00 event."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C15\", \"C17\"],\n  \"missing_checks\": [\n    \"Verify if the 'HardwareFaultAlert' at 18:05:00 in C16 is isolated to the smoke alarm or if other kitchen devices (like the temp sensor) were logging errors simultaneously.\",\n    \"Check data continuity immediately before 18:32:00 in C16 to confirm if the drop to 'None' was instantaneous or preceded by signal degradation.\",\n    \"Cross-reference power events or circuit status logs around 18:32:00 in adjacent chunks (C15/C17) to rule out a total kitchen circuit outage.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identified the transition from valid data to 'None' as a critical failure indicator (A1). However, the current evidence relies heavily on a single chunk (C16) for the failure event and lacks context from the immediate preceding (C15) and succeeding (C17) minutes.\",\n    \"We need C15 to establish the baseline stability of the sensor right before the stove activation and fault alert to rule out pre-existing issues. We need C17 to see if the sensor recovers after a potential reboot or if the failure persists.\",\n    \"The correlation between the smoke alarm fault and the temperature sensor failure needs verification via C15/C17 to determine if they share a common cause (e.g., shared power bus) or if they are independent incidents.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C15", "C17"], "missing_checks": ["Verify if the 'HardwareFaultAlert' at 18:05:00 in C16 is isolated to the smoke alarm or if other kitchen devices (like the temp sensor) were logging errors simultaneously.", "Check data continuity immediately before 18:32:00 in C16 to confirm if the drop to 'None' was instantaneous or preceded by signal degradation.", "Cross-reference power events or circuit status logs around 18:32:00 in adjacent chunks (C15/C17) to rule out a total kitchen circuit outage."], "supervisor_notes": ["The analysis correctly identified the transition from valid data to 'None' as a critical failure indicator (A1). However, the current evidence relies heavily on a single chunk (C16) for the failure event and lacks context from the immediate preceding (C15) and succeeding (C17) minutes.", "We need C15 to establish the baseline stability of the sensor right before the stove activation and fault alert to rule out pre-existing issues. We need C17 to see if the sensor recovers after a potential reboot or if the failure persists.", "The correlation between the smoke alarm fault and the temperature sensor failure needs verification via C15/C17 to determine if they share a common cause (e.g., shared power bus) or if they are independent incidents."]}, "preview_triage_prompt": "## Query\n请检查以下设备状态历史，判断 kitchen 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 402,\n    \"master_bedroom\": 516,\n    \"second_bedroom\": 336,\n    \"kitchen\": 306,\n    \"bathroom\": 48,\n    \"entrance\": 230\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1156,\n    \"Occupancy\": 644,\n    \"OnOff\": 15,\n    \"StateValue\": 7,\n    \"LockState\": 5,\n    \"SystemMode\": 1,\n    \"HardwareFaultAlert\": 1,\n    \"ExpressedState\": 1,\n    \"OperationalState\": 1,\n    \"CurrentPositionLiftPercent100ths\": 1\n  },\n  \"lock_state_flips\": 5,\n  \"occupancy_events\": 644,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-08T00:00:00\",\n    \"end_ts\": \"2026-06-08T01:20:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 20,\n      \"master_bedroom\": 19,\n      \"second_bedroom\": 19,\n      \"kitchen\": 16,\n      \"bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"master_bedroom_occupancy\"\n    ],\n    \"alarmish_count\": 15,\n    \"preview_lines\": [\n      \"[2026-06-08T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2268\",\n      \"[2026-06-08T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2269\",\n      \"[2026-06-08T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2270\",\n      \"[2026-06-08T00:00:00] kitchen_temp_sensor | TemperatureM", "preview_verifier_prompt": "## Query\n请检查以下设备状态历史，判断 kitchen 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。\n\n## Triage\n{\n  \"latent_task_profile\": \"device-health\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"kitchen_smoke_co_alarm\", \"kitchen_contact_sensor\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C16\"],\n  \"suspected_patterns\": [\n    \"Temperature measurement drift (values starting at ~22.7°C rising to >25°C without corresponding HVAC activation)\",\n    \"Potential sensor calibration error or battery depletion causing false high readings\",\n    \"Lack of correlation between temperature spikes and appliance usage (dishwasher/cook_surface) events\"\n  ],\n  \"why_these_chunks\": [\n    \"C00/C01: Initial baseline establishment showing a consistent upward trend in kitchen temperature relative to other rooms, suggesting early-stage sensor drift.\",\n    \"C16: Contains non-temperature events for the kitchen area (Dishwasher state changes), allowing cross-validation to see if temperature spikes correlate with actual heat generation from appliances.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The kitchen temperature sensor is experiencing a delayed thermal response due to high ambient room temperature (approx. 23°C baseline) rather than a hardware fault, as it tracks the general house warming trend.\",\n      \"evidence\": [\"In chunks C00 and C01, all sensors show values in the 2268-2359 range (scaled x10), indicating a consistent baseline of ~22.7°C - 23.6°C across the entire house.\", \"The kitchen sensor readings generally follow the trend of other rooms, albeit with slight lag or noise, suggesting environmental factors like external heat or HVAC inefficiency are affecting all zones uniformly.\"],\n      \"weaknesses\": [\"This hypothesis fails to explain the specific 'HardwareFaultAlert' generated by the smoke alarm at 18:05:00 in chunk C16.\", \"It cannot account for the sudden drop to `None` at 18:32:00 immediately after the stove was activated, which indicates a complete data loss event typical of sensor failure or power cycle, not just slow thermal response.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"The kitchen temperature sensor suffered a hardware failure or communication drop during active cooking usage, indicated by a fault alert and subsequent null reading.\",\n      \"threat_type\": \"Sensor Hardware Failure / Data Integrity Loss\",\n      \"evidence\": [\"At 18:05:00, the `kitchen_smoke_alarm` explicitly rep"}}
{"episode_id": "SQ2_FP_D_0299", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq2\\SQ2_FP_D_0299.json", "metadata": {"sq_type": "SQ2", "sq_name": "单事件安全判断", "variant": "FP", "layout_id": "D", "layout_name": "独居老人 (Elderly Living Alone)", "profile_id": "elderly_living_alone", "base_date": "2026-06-23T00:00:00", "seed": 20260928, "scenario_id": "FG-03", "total_events": 1855, "anomaly_events_count": 5}, "ground_truth": {"scenario_id": "FG-03-FP", "scenario_name": "FG-03-FP: 烟雾报警器自检触发CO检测", "category": "fire_gas", "is_anomaly": false, "threat_type": "none", "key_difference": "TestInProgress=true 表明是自检触发，不是真实CO泄漏；且COState很快恢复为0", "difficulty_score": 6, "difficulty_level": 1, "difficulty_label": "L1_basic_detection", "difficulty_dimensions": {"D1_evidence_count": 1, "D2_signal_directness": 1, "D3_cross_device": 1, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "kitchen", "injection_time": "2026-06-23T07:13:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"fire_risk\",\n  \"threat_description\": \"Sustained multi-room temperature rise and sensor failure indicate a significant uncontrolled thermal event or appliance malfunction, posing an immediate fire hazard.\",\n  \"reasoning\": [\n    \"Multiple room sensors (kitchen, living room, bedroom) recorded abnormally high values (~2400-2500, likely scaled Celsius indicating 24-25°C+) for over 4 hours without active heating systems, suggesting a genuine environmental anomaly rather than a localized sensor error.\",\n    \"The kitchen temperature sensor failed ('None') multiple times during the peak heat period, which correlates with the activation of the cook surface, implying physical damage or disconnection due to excessive heat or smoke exposure.\",\n    \"A door lock operation occurred at T07:04 while temperatures were critically high, followed by a smoke alarm self-test at T07:13, strongly suggesting occupant concern regarding a fire or toxic buildup.\"\n  ],\n  \"key_evidence\": [\n    \"Continuous temperature readings across three rooms rising from ~23°C equivalent to >25°C equivalent between T03:25 and T08:20.\",\n    \"Kitchen sensor returning 'None' at T06:02:05 and T06:37:00 coinciding with highest temperatures and cook surface usage.\",\n    \"Manual front door lock operation at T07:04:02 immediately preceding the smoke alarm test event.\"\n  ],\n  \"recommended_actions\": [\n    \"Dispatch emergency services/fire department to verify on-site conditions immediately.\",\n    \"Contact the resident to confirm safety status and evacuate if necessary.\",\n    \"Inspect kitchen appliances and HVAC systems for faults once scene is secure.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "fire_risk", "threat_description": "Sustained multi-room temperature rise and sensor failure indicate a significant uncontrolled thermal event or appliance malfunction, posing an immediate fire hazard.", "reasoning": ["Multiple room sensors (kitchen, living room, bedroom) recorded abnormally high values (~2400-2500, likely scaled Celsius indicating 24-25°C+) for over 4 hours without active heating systems, suggesting a genuine environmental anomaly rather than a localized sensor error.", "The kitchen temperature sensor failed ('None') multiple times during the peak heat period, which correlates with the activation of the cook surface, implying physical damage or disconnection due to excessive heat or smoke exposure.", "A door lock operation occurred at T07:04 while temperatures were critically high, followed by a smoke alarm self-test at T07:13, strongly suggesting occupant concern regarding a fire or toxic buildup."], "key_evidence": ["Continuous temperature readings across three rooms rising from ~23°C equivalent to >25°C equivalent between T03:25 and T08:20.", "Kitchen sensor returning 'None' at T06:02:05 and T06:37:00 coinciding with highest temperatures and cook surface usage.", "Manual front door lock operation at T07:04:02 immediately preceding the smoke alarm test event."], "recommended_actions": ["Dispatch emergency services/fire department to verify on-site conditions immediately.", "Contact the resident to confirm safety status and evacuate if necessary.", "Inspect kitchen appliances and HVAC systems for faults once scene is secure."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 67.96923613548279, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1855, "chunk_count": 24, "signals": {"room_activity": {"living_room": 495, "bedroom": 529, "kitchen": 538, "bathroom": 63, "entrance": 230}, "attribute_frequency": {"Occupancy": 942, "MeasuredValue": 870, "OnOff": 21, "CurrentPositionLiftPercent100ths": 4, "LockState": 4, "StateValue": 4, "TestInProgress": 2, "COState": 2, "CurrentLevel": 1}, "lock_state_flips": 4, "occupancy_events": 942, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\"],\n  \"focus_devices\": [\n    \"kitchen_temp_sensor\",\n    \"living_room_temp_sensor\",\n    \"bedroom_temp_sensor\",\n    \"kitchen_occupancy\",\n    \"entrance_occupancy\"\n  ],\n  \"focus_chunk_ids\": [\"C02\", \"C03\", \"C04\", \"C16\"],\n  \"suspected_patterns\": [\n    \"sustained_abnormal_temperature_rise\",\n    \"persistent_high_temperatures_despite_no_recent_activity_change\",\n    \"temperature_sensor_data_format_anomaly\"\n  ],\n  \"why_these_chunks\": [\n    \"C02-C04 show a continuous and steep rise in temperature readings across multiple rooms (from ~22°C to >25°C), which is abnormal for a residential environment without an active heating system.\",\n    \"C16 contains critical data anomalies: 'kitchen_temp_sensor' returns 'None', suggesting sensor failure or disconnection, while other sensors still report high temperatures. Additionally, the cook surface turned off ('OnOff.OnOff = False') while occupancy remains high, raising questions about whether the heat source was recently extinguished or if the temperature spike occurred before shutdown.\",\n    \"The combination of persistently high temperatures, fluctuating sensor states, and the specific context of an elderly person living alone suggests a potential fire hazard, malfunctioning appliance, or environmental control failure requiring immediate verification.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "living_room"], "focus_devices": ["kitchen_temp_sensor", "living_room_temp_sensor", "bedroom_temp_sensor", "kitchen_occupancy", "entrance_occupancy"], "focus_chunk_ids": ["C02", "C03", "C04", "C16"], "suspected_patterns": ["sustained_abnormal_temperature_rise", "persistent_high_temperatures_despite_no_recent_activity_change", "temperature_sensor_data_format_anomaly"], "why_these_chunks": ["C02-C04 show a continuous and steep rise in temperature readings across multiple rooms (from ~22°C to >25°C), which is abnormal for a residential environment without an active heating system.", "C16 contains critical data anomalies: 'kitchen_temp_sensor' returns 'None', suggesting sensor failure or disconnection, while other sensors still report high temperatures. Additionally, the cook surface turned off ('OnOff.OnOff = False') while occupancy remains high, raising questions about whether the heat source was recently extinguished or if the temperature spike occurred before shutdown.", "The combination of persistently high temperatures, fluctuating sensor states, and the specific context of an elderly person living alone suggests a potential fire hazard, malfunctioning appliance, or environmental control failure requiring immediate verification."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The system experienced a prolonged period of sensor failure in the kitchen, leading to erroneous high temperature readings (e.g., 2300-2500) which were actually invalid data points rather than physical heat.\",\n      \"evidence\": [\"C02-C04 show 'TemperatureMeasurement.MeasuredValue' in the range of 2300-2500, which is physically impossible for Celsius and likely represents an overflow or calibration error code.\", \"At C03/T06:02:05 and C04/T06:37:00, the sensor explicitly returns 'None', confirming intermittent hardware or communication failure during the high-value period.\", \"When the sensor resumes reporting at C16 (T17:27), values drop to realistic ranges (~2300-2350, assuming a decimal shift or different unit scale initially, but stabilizing to ~23°C by T18:20).\"],\n      \"weaknesses\": [\"Even if the values are invalid, the pattern of *other* sensors (living room, bedroom) also rising from ~22°C to ~25°C over 4 hours suggests a real environmental change, not just a kitchen-specific sensor bug.\", \"The correlation between the start of the 'high' values and human activity (cooking surface turned ON at T06:01) makes it plausible that the sensor malfunctioned specifically due to heat proximity, masking a real hazard.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Uncontrolled thermal event (Fire/Overheating) in the Kitchen with potential sensor degradation due to extreme heat.\",\n      \"threat_type\": \"Environmental Safety / Fire Hazard\",\n      \"evidence\": [\"Sustained temperature rise across multiple rooms (Kitchen, Living Room, Bedroom) from ~22°C to >25°C between T03:25 and T07:15, despite no active heating system being reported ON until T06:01.\", \"Cooking surface was activated at T06:01 ('OnOff = True') while occupants were present.\", \"Smoke alarm entered self-test mode at T07:13 immediately following the peak temperature period, suggesting a pre-existing sensitivity issue or a reaction to low-level combustion products.\", \"Sensor failure ('None' returned) correlates temporally with the highest temperatures and appliance usage, indicating possible sensor melting or disconnection due to excessive heat.\", \"Door lock operations at T07:04 coincide with occupancy changes, possibly indicating an attempt to leave or enter due to discomfort/emergency.\"],\n      \"weaknesses\": [\"Occupancy data shows people moving around freely (lights on, windows opened), which might argue against a life-threatening fire at that exact moment, though they could be unaware of the severity.\", \"The final reading in C16 shows temperatures returning to normal ranges (~23°C), which could imply the initial spike was transient or the sensor finally recovered after cooling down.\"]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Systematic Data Interpretation Error: The raw data units are non-standard (likely millikelvin or internal integer encoding), causing the visualization/model to misinterpret ~23.00 as 2300.\",\n      \"threat_type\": \"False Positive / Data Integrity Issue\",\n      \"evidence\": [\"All temperature sensors report values consistently shifted by a factor of 100 or more compared to standard residential norms (e.g., 2300 vs 23°C).\", \"The values stabilize and behave logically once interpreted as a scaled unit (2300 -> 23.00), showing a gradual decline in C16 consistent with natural cooling or AC usage.\", \"No other safety signals (smoke detection, door alarms) were triggered by this specific numerical anomaly alone; the smoke alarm only ran a test later.\"],\n      \"weaknesses\": [\"If the data is indeed scaled, the living room and bedroom also rose to ~25°C (2500), which is still abnormally hot for a summer night (June 23rd) in a residential setting without air conditioning, suggesting a genuine thermal event regardless of unit scaling.\", \"The sudden appearance of 'None' values alongside these high numbers strongly suggests a hardware fault triggered by actual heat, not just a software unit conversion error.\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The temporal sequence: Cooking surface turns ON at T06:01, followed by a rapid climb in all room temperatures, then sensor failure ('None'), followed by a smoke alarm self-test at T07:13.\",\n    \"The multi-room correlation: The temperature rise is not isolated to the kitchen; the living room and bedroom also increased significantly, ruling out a localized sensor glitch in the kitchen only.\",\n    \"The explicit sensor failure ('None') occurring at the peak of the temperature event indicates physical stress on the sensor, corroborating the presence of extreme heat beyond normal operating parameters.\"\n  ],\n  \"missing_information\": [\n    \"Actual unit of measurement for 'MeasuredValue' (Is it Kelvin? Millidegrees? Or just a typo in the log?).\",\n    \"Status of the HVAC/Air Conditioning system (Was it off, broken, or set incorrectly?).\",\n    \"Historical baseline for 'TestInProgress' events on the smoke alarm (Is T07:13 a routine daily check or an emergency trigger?).\",\n    \"Video feed or audio logs from the time period T06:00-T07:00 to confirm occupant behavior and auditory cues.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The system experienced a prolonged period of sensor failure in the kitchen, leading to erroneous high temperature readings (e.g., 2300-2500) which were actually invalid data points rather than physical heat.", "evidence": ["C02-C04 show 'TemperatureMeasurement.MeasuredValue' in the range of 2300-2500, which is physically impossible for Celsius and likely represents an overflow or calibration error code.", "At C03/T06:02:05 and C04/T06:37:00, the sensor explicitly returns 'None', confirming intermittent hardware or communication failure during the high-value period.", "When the sensor resumes reporting at C16 (T17:27), values drop to realistic ranges (~2300-2350, assuming a decimal shift or different unit scale initially, but stabilizing to ~23°C by T18:20)."], "weaknesses": ["Even if the values are invalid, the pattern of *other* sensors (living room, bedroom) also rising from ~22°C to ~25°C over 4 hours suggests a real environmental change, not just a kitchen-specific sensor bug.", "The correlation between the start of the 'high' values and human activity (cooking surface turned ON at T06:01) makes it plausible that the sensor malfunctioned specifically due to heat proximity, masking a real hazard."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Uncontrolled thermal event (Fire/Overheating) in the Kitchen with potential sensor degradation due to extreme heat.", "threat_type": "Environmental Safety / Fire Hazard", "evidence": ["Sustained temperature rise across multiple rooms (Kitchen, Living Room, Bedroom) from ~22°C to >25°C between T03:25 and T07:15, despite no active heating system being reported ON until T06:01.", "Cooking surface was activated at T06:01 ('OnOff = True') while occupants were present.", "Smoke alarm entered self-test mode at T07:13 immediately following the peak temperature period, suggesting a pre-existing sensitivity issue or a reaction to low-level combustion products.", "Sensor failure ('None' returned) correlates temporally with the highest temperatures and appliance usage, indicating possible sensor melting or disconnection due to excessive heat.", "Door lock operations at T07:04 coincide with occupancy changes, possibly indicating an attempt to leave or enter due to discomfort/emergency."], "weaknesses": ["Occupancy data shows people moving around freely (lights on, windows opened), which might argue against a life-threatening fire at that exact moment, though they could be unaware of the severity.", "The final reading in C16 shows temperatures returning to normal ranges (~23°C), which could imply the initial spike was transient or the sensor finally recovered after cooling down."]}, {"id": "A2", "description": "Systematic Data Interpretation Error: The raw data units are non-standard (likely millikelvin or internal integer encoding), causing the visualization/model to misinterpret ~23.00 as 2300.", "threat_type": "False Positive / Data Integrity Issue", "evidence": ["All temperature sensors report values consistently shifted by a factor of 100 or more compared to standard residential norms (e.g., 2300 vs 23°C).", "The values stabilize and behave logically once interpreted as a scaled unit (2300 -> 23.00), showing a gradual decline in C16 consistent with natural cooling or AC usage.", "No other safety signals (smoke detection, door alarms) were triggered by this specific numerical anomaly alone; the smoke alarm only ran a test later."], "weaknesses": ["If the data is indeed scaled, the living room and bedroom also rose to ~25°C (2500), which is still abnormally hot for a summer night (June 23rd) in a residential setting without air conditioning, suggesting a genuine thermal event regardless of unit scaling.", "The sudden appearance of 'None' values alongside these high numbers strongly suggests a hardware fault triggered by actual heat, not just a software unit conversion error."]}], "most_discriminative_evidence": ["The temporal sequence: Cooking surface turns ON at T06:01, followed by a rapid climb in all room temperatures, then sensor failure ('None'), followed by a smoke alarm self-test at T07:13.", "The multi-room correlation: The temperature rise is not isolated to the kitchen; the living room and bedroom also increased significantly, ruling out a localized sensor glitch in the kitchen only.", "The explicit sensor failure ('None') occurring at the peak of the temperature event indicates physical stress on the sensor, corroborating the presence of extreme heat beyond normal operating parameters."], "missing_information": ["Actual unit of measurement for 'MeasuredValue' (Is it Kelvin? Millidegrees? Or just a typo in the log?).", "Status of the HVAC/Air Conditioning system (Was it off, broken, or set incorrectly?).", "Historical baseline for 'TestInProgress' events on the smoke alarm (Is T07:13 a routine daily check or an emergency trigger?).", "Video feed or audio logs from the time period T06:00-T07:00 to confirm occupant behavior and auditory cues."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C05\", \"C17\", \"C20\"],\n  \"missing_checks\": [\n    \"Verify HVAC system status and logs during the temperature spike.\",\n    \"Determine if the smoke alarm 'TestInProgress' at T07:13 was a routine daily check or an emergency trigger.\",\n    \"Review video/audio feeds from C05-C06 range to confirm occupant behavior and auditory cues (smoke/heat sounds).\",\n    \"Check historical baseline for sensor data formatting to rule out systematic unit encoding errors.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identified the multi-room temperature correlation and sensor failure patterns as critical indicators of a potential thermal event.\",\n    \"However, the evidence is currently insufficient to definitively classify the threat level because it relies heavily on inferred states (e.g., assuming the smoke alarm test implies a hazard) without verifying the actual source of that signal.\",\n    \"Chunks C05 and C17 are needed to cover the immediate aftermath of the peak temperature to see if conditions stabilized or worsened, and C20 may contain the specific HVAC configuration logs required to rule out mechanical failure as the sole cause.\",\n    \"The hypothesis regarding data unit scaling (A2) remains a strong contender; checking raw log formats in missing chunks is essential before escalating to emergency protocols.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C05", "C17", "C20"], "missing_checks": ["Verify HVAC system status and logs during the temperature spike.", "Determine if the smoke alarm 'TestInProgress' at T07:13 was a routine daily check or an emergency trigger.", "Review video/audio feeds from C05-C06 range to confirm occupant behavior and auditory cues (smoke/heat sounds).", "Check historical baseline for sensor data formatting to rule out systematic unit encoding errors."], "supervisor_notes": ["The analysis correctly identified the multi-room temperature correlation and sensor failure patterns as critical indicators of a potential thermal event.", "However, the evidence is currently insufficient to definitively classify the threat level because it relies heavily on inferred states (e.g., assuming the smoke alarm test implies a hazard) without verifying the actual source of that signal.", "Chunks C05 and C17 are needed to cover the immediate aftermath of the peak temperature to see if conditions stabilized or worsened, and C20 may contain the specific HVAC configuration logs required to rule out mechanical failure as the sole cause.", "The hypothesis regarding data unit scaling (A2) remains a strong contender; checking raw log formats in missing chunks is essential before escalating to emergency protocols."]}, "preview_triage_prompt": "## Query\n以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。\n\n## Layout\nLayout: 独居老人 (Elderly Living Alone)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>, 床头灯<onoff_light>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房运动传感器<occupancy_sensor>\n- living_room: 客厅温度传感器<temperature_sensor>, 客厅灯<dimmable_light>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 495,\n    \"bedroom\": 529,\n    \"kitchen\": 538,\n    \"bathroom\": 63,\n    \"entrance\": 230\n  },\n  \"attribute_frequency\": {\n    \"Occupancy\": 942,\n    \"MeasuredValue\": 870,\n    \"OnOff\": 21,\n    \"CurrentPositionLiftPercent100ths\": 4,\n    \"LockState\": 4,\n    \"StateValue\": 4,\n    \"TestInProgress\": 2,\n    \"COState\": 2,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 942,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-23T00:00:00\",\n    \"end_ts\": \"2026-06-23T01:35:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 24,\n      \"bedroom\": 24,\n      \"kitchen\": 24,\n      \"bathroom\": 4,\n      \"entrance\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"kitchen_occupancy\"\n    ],\n    \"alarmish_count\": 20,\n    \"preview_lines\": [\n      \"[2026-06-23T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2272\",\n      \"[2026-06-23T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2172\",\n      \"[2026-06-23T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2261\",\n      \"[2026-06-23T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-23T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-23T00:00:00] kitchen_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-23T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-23T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0\",\n    ", "preview_verifier_prompt": "## Query\n以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\"],\n  \"focus_devices\": [\n    \"kitchen_temp_sensor\",\n    \"living_room_temp_sensor\",\n    \"bedroom_temp_sensor\",\n    \"kitchen_occupancy\",\n    \"entrance_occupancy\"\n  ],\n  \"focus_chunk_ids\": [\"C02\", \"C03\", \"C04\", \"C16\"],\n  \"suspected_patterns\": [\n    \"sustained_abnormal_temperature_rise\",\n    \"persistent_high_temperatures_despite_no_recent_activity_change\",\n    \"temperature_sensor_data_format_anomaly\"\n  ],\n  \"why_these_chunks\": [\n    \"C02-C04 show a continuous and steep rise in temperature readings across multiple rooms (from ~22°C to >25°C), which is abnormal for a residential environment without an active heating system.\",\n    \"C16 contains critical data anomalies: 'kitchen_temp_sensor' returns 'None', suggesting sensor failure or disconnection, while other sensors still report high temperatures. Additionally, the cook surface turned off ('OnOff.OnOff = False') while occupancy remains high, raising questions about whether the heat source was recently extinguished or if the temperature spike occurred before shutdown.\",\n    \"The combination of persistently high temperatures, fluctuating sensor states, and the specific context of an elderly person living alone suggests a potential fire hazard, malfunctioning appliance, or environmental control failure requiring immediate verification.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The system experienced a prolonged period of sensor failure in the kitchen, leading to erroneous high temperature readings (e.g., 2300-2500) which were actually invalid data points rather than physical heat.\",\n      \"evidence\": [\"C02-C04 show 'TemperatureMeasurement.MeasuredValue' in the range of 2300-2500, which is physically impossible for Celsius and likely represents an overflow or calibration error code.\", \"At C03/T06:02:05 and C04/T06:37:00, the sensor explicitly returns 'None', confirming intermittent hardware or communication failure during the high-value period.\", \"When the sensor resumes reporting at C16 (T17:27), values drop to realistic ranges (~2300-2350, assuming a decimal shift or different unit scale initially, but stabilizing to ~23°C by T18:20).\"],\n      \"weaknesses\": [\"Even if the values are invalid, the pattern of *other* sensors (living room, bedroom) also rising from ~22°C to ~25°C over 4 hours suggests a real environmental chan"}}
{"episode_id": "SQ2_FP_C_0307", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq2\\SQ2_FP_C_0307.json", "metadata": {"sq_type": "SQ2", "sq_name": "单事件安全判断", "variant": "FP", "layout_id": "C", "layout_name": "三室两厅 (3BR)", "profile_id": "family_with_children", "base_date": "2026-06-05T00:00:00", "seed": 20260936, "scenario_id": "WD-03", "total_events": 2292, "anomaly_events_count": 2}, "ground_truth": {"scenario_id": "WD-03-FP", "scenario_name": "WD-03-FP: 住户外出但开了自动浇花系统", "category": "water_damage", "is_anomaly": false, "threat_type": "none", "key_difference": "漏水传感器触发后在短时间内（3分钟）恢复为false，而非持续触发超过10分钟", "difficulty_score": 10, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 1, "D3_cross_device": 2, "D4_temporal_span": 3, "D5_fp_similarity": 2}, "target_room": "second_bathroom", "injection_time": "2026-06-05T10:50:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"fire_risk\",\n  \"threat_description\": \"A sustained, linear temperature rise across all monitored rooms over several hours indicates a critical HVAC failure or system malfunction, creating an imminent fire and health hazard.\",\n  \"reasoning\": [\n    \"The data shows a continuous, unexplained increase in ambient temperature from approximately 23°C to over 25°C (50°C+ on raw scale) across every room simultaneously, which is inconsistent with normal passive heating or external weather patterns that would show variance.\",\n    \"Despite multiple occupancy events where residents entered the house and turned on lights/appliances, there were no 'OnOff' commands for the Air Conditioner or Thermostat, nor any indication of cooling activity, suggesting the system has failed to activate or respond.\",\n    \"The kitchen sensor eventually returned 'None' at 07:01:10 immediately after a cooking surface was activated, likely due to sensor saturation from extreme heat, confirming dangerous overheating conditions.\",\n    \"The uniformity and linearity of the temperature spike across disconnected zones strongly point to a central mechanical failure (e.g., compressor lockout, fan failure, or power loss) rather than localized issues.\"\n  ],\n  \"key_evidence\": [\n    \"Temperature readings rose steadily from ~23°C to >25°C over a 6-hour period in Living Room, Kitchen, Master Bedroom, and Kids Room simultaneously.\",\n    \"No thermostat commands or cooling cycles were logged during the entire event, despite the temperature exceeding typical comfort thresholds.\",\n    \"Kitchen sensor data dropped to 'None' upon activation of the cooktop, indicating potential sensor burnout due to excessive ambient heat.\",\n    \"Occupancy logs confirm the house was occupied towards the end, yet temperatures continued to climb rapidly without intervention.\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately dispatch emergency services or contact a technician to inspect the HVAC/cooling system.\",\n    \"Evacuate the premises if smoke alarms trigger or if temperatures continue to rise uncontrollably.\",\n    \"Do not attempt to manually reset the HVAC unit until a professional has identified the cause of the failure.\",\n    \"Check external weather conditions to rule out extreme ambient heat, though internal uniformity suggests mechanical failure.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "fire_risk", "threat_description": "A sustained, linear temperature rise across all monitored rooms over several hours indicates a critical HVAC failure or system malfunction, creating an imminent fire and health hazard.", "reasoning": ["The data shows a continuous, unexplained increase in ambient temperature from approximately 23°C to over 25°C (50°C+ on raw scale) across every room simultaneously, which is inconsistent with normal passive heating or external weather patterns that would show variance.", "Despite multiple occupancy events where residents entered the house and turned on lights/appliances, there were no 'OnOff' commands for the Air Conditioner or Thermostat, nor any indication of cooling activity, suggesting the system has failed to activate or respond.", "The kitchen sensor eventually returned 'None' at 07:01:10 immediately after a cooking surface was activated, likely due to sensor saturation from extreme heat, confirming dangerous overheating conditions.", "The uniformity and linearity of the temperature spike across disconnected zones strongly point to a central mechanical failure (e.g., compressor lockout, fan failure, or power loss) rather than localized issues."], "key_evidence": ["Temperature readings rose steadily from ~23°C to >25°C over a 6-hour period in Living Room, Kitchen, Master Bedroom, and Kids Room simultaneously.", "No thermostat commands or cooling cycles were logged during the entire event, despite the temperature exceeding typical comfort thresholds.", "Kitchen sensor data dropped to 'None' upon activation of the cooktop, indicating potential sensor burnout due to excessive ambient heat.", "Occupancy logs confirm the house was occupied towards the end, yet temperatures continued to climb rapidly without intervention."], "recommended_actions": ["Immediately dispatch emergency services or contact a technician to inspect the HVAC/cooling system.", "Evacuate the premises if smoke alarms trigger or if temperatures continue to rise uncontrollably.", "Do not attempt to manually reset the HVAC unit until a professional has identified the cause of the failure.", "Check external weather conditions to rule out extreme ambient heat, though internal uniformity suggests mechanical failure."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 72.1536545753479, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 2292, "chunk_count": 29, "signals": {"room_activity": {"living_room": 399, "master_bedroom": 520, "kids_room": 519, "kitchen": 303, "dining_room": 217, "second_bedroom": 48, "master_bathroom": 54, "entrance": 229, "second_bathroom": 3}, "attribute_frequency": {"MeasuredValue": 1156, "Occupancy": 1086, "OnOff": 26, "StateValue": 9, "LockState": 5, "CurrentPositionLiftPercent100ths": 3, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 5, "occupancy_events": 1086, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"single-event-safety | composite-safety\",\n  \"focus_rooms\": [\n    \"kitchen\",\n    \"living_room\",\n    \"master_bedroom\",\n    \"kids_room\"\n  ],\n  \"focus_devices\": [\n    \"kitchen_temp_sensor\",\n    \"living_room_temp_sensor\",\n    \"master_bedroom_temp_sensor\",\n    \"kids_room_temp_sensor\",\n    \"smoke_co_alarm\",\n    \"air_conditioner\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C01\",\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C06\",\n    \"C07\",\n    \"C08\",\n    \"C09\",\n    \"C10\",\n    \"C11\",\n    \"C12\",\n    \"C13\",\n    \"C14\",\n    \"C15\",\n    \"C16\",\n    \"C17\",\n    \"C18\",\n    \"C19\",\n    \"C20\",\n    \"C21\",\n    \"C22\",\n    \"C23\",\n    \"C24\",\n    \"C25\",\n    \"C26\",\n    \"C27\",\n    \"C28\"\n  ],\n  \"suspected_patterns\": [\n    \"Continuous temperature spike across all living spaces (approx. 23°C -> 25.6°C) over ~12 hours despite no occupancy change in some rooms.\",\n    \"Correlation between rising ambient temperature and potential HVAC failure or malfunction.\",\n    \"Risk of fire hazard due to overheating kitchen appliances or electrical systems if AC fails.\"\n  ],\n  \"why_these_chunks\": [\n    \"All chunks from C01 to C28 show a progressive, linear increase in temperature readings for sensors in the kitchen, living room, master bedroom, and kids room.\",\n    \"The initial chunks (C00-C01) establish the baseline (~22-23°C). Subsequent chunks reveal the anomaly where temperatures climb steadily to exceed 25°C.\",\n    \"This pattern indicates a latent safety threat (potential heating system failure or lack of cooling) that requires immediate verification against smoke alarms and appliance states, rather than just analyzing discrete events like door locks or lights.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "single-event-safety | composite-safety", "focus_rooms": ["kitchen", "living_room", "master_bedroom", "kids_room"], "focus_devices": ["kitchen_temp_sensor", "living_room_temp_sensor", "master_bedroom_temp_sensor", "kids_room_temp_sensor", "smoke_co_alarm", "air_conditioner"], "focus_chunk_ids": ["C01", "C02", "C03", "C04", "C05", "C06", "C07", "C08", "C09", "C10", "C11", "C12", "C13", "C14", "C15", "C16", "C17", "C18", "C19", "C20", "C21", "C22", "C23", "C24", "C25", "C26", "C27", "C28"], "suspected_patterns": ["Continuous temperature spike across all living spaces (approx. 23°C -> 25.6°C) over ~12 hours despite no occupancy change in some rooms.", "Correlation between rising ambient temperature and potential HVAC failure or malfunction.", "Risk of fire hazard due to overheating kitchen appliances or electrical systems if AC fails."], "why_these_chunks": ["All chunks from C01 to C28 show a progressive, linear increase in temperature readings for sensors in the kitchen, living room, master bedroom, and kids room.", "The initial chunks (C00-C01) establish the baseline (~22-23°C). Subsequent chunks reveal the anomaly where temperatures climb steadily to exceed 25°C.", "This pattern indicates a latent safety threat (potential heating system failure or lack of cooling) that requires immediate verification against smoke alarms and appliance states, rather than just analyzing discrete events like door locks or lights."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The house is unoccupied and experiencing a gradual, benign temperature rise due to external ambient conditions (e.g., hot day) or delayed HVAC wake-up cycles after being off overnight.\",\n      \"evidence\": [\"All rooms show occupancy = 0 from 01:30 until 06:03.\", \"Temperature readings are consistent across multiple sensors in different zones, suggesting a systemic environmental factor rather than localized heating.\", \"No fire alarms or smoke detectors have triggered yet.\"],\n      \"weaknesses\": [\"The rate of increase is linear and continuous over 6 hours without any plateau, which is atypical for passive heat gain where equilibrium should eventually be reached or slowed by thermal mass. Normal diurnal swings rarely cause such a sustained, steep gradient in an enclosed space without active heating.\"],\n      \"weakness\": \"The uniformity of the rise across all rooms simultaneously suggests a common failure point (like total HVAC loss) rather than just outside weather, especially given the magnitude of the rise (~2.5°C per hour average).\"\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Total HVAC/Cooling System Failure leading to progressive overheating and potential structural/fire hazard.\",\n      \"threat_type\": \"Environmental Hazard / Fire Risk\",\n      \"evidence\": [\n      \"Sustained, linear temperature increase across ALL monitored rooms (Living, Kitchen, Bedrooms) from ~23°C to >25°C over a 6-hour period despite zero occupancy.\",\n      \"Kitchen sensor specifically shows erratic spikes near the end (2500+ -> None), possibly indicating sensor saturation or proximity to a failing appliance/heater.\",\n      \"Occupancy events (people entering rooms at 06:03) do not interrupt the heating trend; temperatures continue to climb rapidly even as humans enter, indicating no human intervention (like turning on AC) has occurred.\",\n      \"Correlation between rising ambient temp and lack of cooling response.\"\n    ],\n      \"weaknesses\": [\"Could be a sensor calibration error affecting all nodes simultaneously (less likely if they are distinct physical devices).\", \"External factors like direct sunlight through windows could theoretically drive temps up, but usually with more variance and lag.\"],\n      \"weakness\": \"Even with sun exposure, raising every room uniformly by nearly 3°C in 6 hours without any fluctuation is highly improbable without a mechanical failure of the cooling system.\"\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Undetected electrical fault or short circuit in the HVAC unit causing it to generate excessive heat instead of cooling.\",\n      \"threat_type\": \"Fire Hazard\",\n      \"evidence\": [\n      \"Rapid acceleration of temperature rise in later chunks (C04-C05) coinciding with occupant activity might indicate they noticed the heat and checked systems, but temps kept rising.\",\n      \"Kitchen temperature data drops to 'None' at 07:01:10, potentially indicating a sensor burnout or extreme heat distortion.\"\n    ],\n      \"weaknesses\": [\"No other electrical anomalies (trips, lights flickering) are explicitly logged in the provided chunks besides normal light switches.\", \"The pattern looks more like passive accumulation than sudden ignition.\"],\n      \"weakness\": \"Lack of explicit 'Power Fault' or 'Circuit Breaker Trip' signals in the structured data.\"\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"Linear, unceasing temperature ascent across the entire house (23°C -> 25°C+) over 6 hours with zero occupancy intervening.\",\n    \"Simultaneous rise in Kitchen and Bedroom sensors indicates a central system failure rather than localized cooking or appliance use.\",\n    \"Absence of any 'OnOff' commands for the Air Conditioner or Thermostat in the logs during this period.\"\n  ],\n  \"missing_information\": [\n    \"HVAC/Thermostat state logs (Was the system set to 'Cool'? Did it report 'Error'?).\",\n    \"External weather data (Outdoor temperature and humidity).\",\n    \"Smoke detector status/readings (Are they currently armed or silent?).\",\n    \"History of the last successful cooling cycle.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The house is unoccupied and experiencing a gradual, benign temperature rise due to external ambient conditions (e.g., hot day) or delayed HVAC wake-up cycles after being off overnight.", "evidence": ["All rooms show occupancy = 0 from 01:30 until 06:03.", "Temperature readings are consistent across multiple sensors in different zones, suggesting a systemic environmental factor rather than localized heating.", "No fire alarms or smoke detectors have triggered yet."], "weaknesses": ["The rate of increase is linear and continuous over 6 hours without any plateau, which is atypical for passive heat gain where equilibrium should eventually be reached or slowed by thermal mass. Normal diurnal swings rarely cause such a sustained, steep gradient in an enclosed space without active heating."], "weakness": "The uniformity of the rise across all rooms simultaneously suggests a common failure point (like total HVAC loss) rather than just outside weather, especially given the magnitude of the rise (~2.5°C per hour average)."}], "anomaly_hypotheses": [{"id": "A1", "description": "Total HVAC/Cooling System Failure leading to progressive overheating and potential structural/fire hazard.", "threat_type": "Environmental Hazard / Fire Risk", "evidence": ["Sustained, linear temperature increase across ALL monitored rooms (Living, Kitchen, Bedrooms) from ~23°C to >25°C over a 6-hour period despite zero occupancy.", "Kitchen sensor specifically shows erratic spikes near the end (2500+ -> None), possibly indicating sensor saturation or proximity to a failing appliance/heater.", "Occupancy events (people entering rooms at 06:03) do not interrupt the heating trend; temperatures continue to climb rapidly even as humans enter, indicating no human intervention (like turning on AC) has occurred.", "Correlation between rising ambient temp and lack of cooling response."], "weaknesses": ["Could be a sensor calibration error affecting all nodes simultaneously (less likely if they are distinct physical devices).", "External factors like direct sunlight through windows could theoretically drive temps up, but usually with more variance and lag."], "weakness": "Even with sun exposure, raising every room uniformly by nearly 3°C in 6 hours without any fluctuation is highly improbable without a mechanical failure of the cooling system."}, {"id": "A2", "description": "Undetected electrical fault or short circuit in the HVAC unit causing it to generate excessive heat instead of cooling.", "threat_type": "Fire Hazard", "evidence": ["Rapid acceleration of temperature rise in later chunks (C04-C05) coinciding with occupant activity might indicate they noticed the heat and checked systems, but temps kept rising.", "Kitchen temperature data drops to 'None' at 07:01:10, potentially indicating a sensor burnout or extreme heat distortion."], "weaknesses": ["No other electrical anomalies (trips, lights flickering) are explicitly logged in the provided chunks besides normal light switches.", "The pattern looks more like passive accumulation than sudden ignition."], "weakness": "Lack of explicit 'Power Fault' or 'Circuit Breaker Trip' signals in the structured data."}], "most_discriminative_evidence": ["Linear, unceasing temperature ascent across the entire house (23°C -> 25°C+) over 6 hours with zero occupancy intervening.", "Simultaneous rise in Kitchen and Bedroom sensors indicates a central system failure rather than localized cooking or appliance use.", "Absence of any 'OnOff' commands for the Air Conditioner or Thermostat in the logs during this period."], "missing_information": ["HVAC/Thermostat state logs (Was the system set to 'Cool'? Did it report 'Error'?).", "External weather data (Outdoor temperature and humidity).", "Smoke detector status/readings (Are they currently armed or silent?).", "History of the last successful cooling cycle."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [],\n  \"missing_checks\": [\n    \"HVAC/Thermostat state logs (Cool mode active? Error codes?)\",\n    \"External weather data (Outdoor temp/humidity)\",\n    \"Smoke detector status/readings\"\n  ],\n  \"supervisor_notes\": [\n    \"The investigation is currently on-topic and correctly identifies the core anomaly: a sustained, uniform temperature rise across all rooms despite zero occupancy, pointing towards HVAC failure rather than external weather or localized events.\",\n    \"However, the evidence is insufficient to confirm a 'safety threat' vs. a 'benign environmental event' with high confidence. The current chunk set (C01-C28) only covers sensor readings and basic occupancy/lighting; it lacks critical system state data.\",\n    \"Specifically, we need to verify if the AC was actually commanded to run and why it failed (logs for C01-C28 should include thermostat commands or error states). Without this, we cannot rule out that the system was never turned on or had a silent electrical fault not captured by generic 'light switch' logs.\",\n    \"Additionally, external weather data is missing from the provided chunks, making it impossible to distinguish between a total power loss to the AC unit versus an unusually hot day causing passive heating (though the linear rate suggests failure).\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": [], "missing_checks": ["HVAC/Thermostat state logs (Cool mode active? Error codes?)", "External weather data (Outdoor temp/humidity)", "Smoke detector status/readings"], "supervisor_notes": ["The investigation is currently on-topic and correctly identifies the core anomaly: a sustained, uniform temperature rise across all rooms despite zero occupancy, pointing towards HVAC failure rather than external weather or localized events.", "However, the evidence is insufficient to confirm a 'safety threat' vs. a 'benign environmental event' with high confidence. The current chunk set (C01-C28) only covers sensor readings and basic occupancy/lighting; it lacks critical system state data.", "Specifically, we need to verify if the AC was actually commanded to run and why it failed (logs for C01-C28 should include thermostat commands or error states). Without this, we cannot rule out that the system was never turned on or had a silent electrical fault not captured by generic 'light switch' logs.", "Additionally, external weather data is missing from the provided chunks, making it impossible to distinguish between a total power loss to the AC unit versus an unusually hot day causing passive heating (though the linear rate suggests failure)."]}, "preview_triage_prompt": "## Query\n以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。\n\n## Layout\nLayout: 三室两厅 (3BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kids_room: 儿童房温度传感器<temperature_sensor>, 儿童房灯<dimmable_light>, 儿童房窗帘<window_covering>, 儿童房窗户传感器<contact_sensor>, 儿童房运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅副灯<dimmable_light>, 客厅氛围灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘1<window_covering>, 客厅窗户传感器1<contact_sensor>, 客厅窗户传感器2<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n- master_bathroom: 主卫漏水传感器<water_leak_detector>, 主卫灯<onoff_light>, 主卫运动传感器<occupancy_sensor>\n- master_bedroom: 主卧床头灯<onoff_light>, 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>\n- second_bedroom: 次卧灯<dimmable_light>, 次卧空调<air_conditioner>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 399,\n    \"master_bedroom\": 520,\n    \"kids_room\": 519,\n    \"kitchen\": 303,\n    \"dining_room\": 217,\n    \"second_bedroom\": 48,\n    \"master_bathroom\": 54,\n    \"entrance\": 229,\n    \"second_bathroom\": 3\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1156,\n    \"Occupancy\": 1086,\n    \"OnOff\": 26,\n    \"StateValue\": 9,\n    \"LockState\": 5,\n    \"CurrentPositionLiftPercent100ths\": 3,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 5,\n  \"occupancy_events\": 1086,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-05T00:00:00\",\n    \"end_ts\": \"2026-06-05T01:10:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 18,\n      \"master_bedroom\": 18,\n      \"kids_room\": 18,\n      \"kitchen\": 14,\n      \"dining_room\": 3,\n      \"second_bedroom\": 3,\n      \"master_bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"kids_room_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"dining_roo", "preview_verifier_prompt": "## Query\n以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。\n\n## Triage\n{\n  \"latent_task_profile\": \"single-event-safety | composite-safety\",\n  \"focus_rooms\": [\n    \"kitchen\",\n    \"living_room\",\n    \"master_bedroom\",\n    \"kids_room\"\n  ],\n  \"focus_devices\": [\n    \"kitchen_temp_sensor\",\n    \"living_room_temp_sensor\",\n    \"master_bedroom_temp_sensor\",\n    \"kids_room_temp_sensor\",\n    \"smoke_co_alarm\",\n    \"air_conditioner\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C01\",\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C06\",\n    \"C07\",\n    \"C08\",\n    \"C09\",\n    \"C10\",\n    \"C11\",\n    \"C12\",\n    \"C13\",\n    \"C14\",\n    \"C15\",\n    \"C16\",\n    \"C17\",\n    \"C18\",\n    \"C19\",\n    \"C20\",\n    \"C21\",\n    \"C22\",\n    \"C23\",\n    \"C24\",\n    \"C25\",\n    \"C26\",\n    \"C27\",\n    \"C28\"\n  ],\n  \"suspected_patterns\": [\n    \"Continuous temperature spike across all living spaces (approx. 23°C -> 25.6°C) over ~12 hours despite no occupancy change in some rooms.\",\n    \"Correlation between rising ambient temperature and potential HVAC failure or malfunction.\",\n    \"Risk of fire hazard due to overheating kitchen appliances or electrical systems if AC fails.\"\n  ],\n  \"why_these_chunks\": [\n    \"All chunks from C01 to C28 show a progressive, linear increase in temperature readings for sensors in the kitchen, living room, master bedroom, and kids room.\",\n    \"The initial chunks (C00-C01) establish the baseline (~22-23°C). Subsequent chunks reveal the anomaly where temperatures climb steadily to exceed 25°C.\",\n    \"This pattern indicates a latent safety threat (potential heating system failure or lack of cooling) that requires immediate verification against smoke alarms and appliance states, rather than just analyzing discrete events like door locks or lights.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The house is unoccupied and experiencing a gradual, benign temperature rise due to external ambient conditions (e.g., hot day) or delayed HVAC wake-up cycles after being off overnight.\",\n      \"evidence\": [\"All rooms show occupancy = 0 from 01:30 until 06:03.\", \"Temperature readings are consistent across multiple sensors in different zones, suggesting a systemic environmental factor rather than localized heating.\", \"No fire alarms or smoke detectors have triggered yet.\"],\n      \"weaknesses\": [\"The rate of increase is linear and continuous over 6 hours without any plateau, which is atypical for passive heat gain where equilibrium should eventually be reached or slowed by thermal "}}
{"episode_id": "SQ2_TP_D_0206", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq2\\SQ2_TP_D_0206.json", "metadata": {"sq_type": "SQ2", "sq_name": "单事件安全判断", "variant": "TP", "layout_id": "D", "layout_name": "独居老人 (Elderly Living Alone)", "profile_id": "elderly_living_alone", "base_date": "2026-06-04T00:00:00", "seed": 20260835, "scenario_id": "FG-03", "total_events": 1855, "anomaly_events_count": 3}, "ground_truth": {"scenario_id": "FG-03", "scenario_name": "CO浓度升高", "category": "fire_gas", "is_anomaly": true, "threat_type": "carbon_monoxide", "key_evidence": ["SmokeCoAlarm 的 COState 变为 Warning 或 Critical", "CO 报警是严重安全事件，不同于烟雾报警"], "expected_response": "紧急通知所有住户撤离，开窗通风，联系燃气公司", "difficulty_score": 6, "difficulty_level": 1, "difficulty_label": "L1_basic_detection", "difficulty_dimensions": {"D1_evidence_count": 1, "D2_signal_directness": 1, "D3_cross_device": 1, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "kitchen", "injection_time": "2026-06-04T03:24:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"fire_risk\",\n  \"threat_description\": \"The system indicates a high probability of an unattended kitchen fire or gas leak due to a sustained temperature rise and CO alarm trigger while the house was empty.\",\n  \"reasoning\": [\n    \"Pre-incident analysis (C01) establishes a stable baseline where the kitchen temperature (~2320°C equivalent in data units) was consistently lower than the living room (~2330-2350), making the subsequent rapid and sustained heating anomaly statistically significant.\",\n    \"At 03:24:00, the CO alarm triggered ('COState = 1') concurrently with the kitchen temperature exceeding the living room temperature for the first time since monitoring began, indicating localized heat generation rather than ambient warming.\",\n    \"Post-trigger data (C02-C03) shows the kitchen temperature continuing to climb steadily (reaching ~2490 by 06:10) while other rooms remain relatively stable, and no human occupancy was detected until over two hours later when cooking appliances were manually turned on, suggesting the threat occurred without intervention.\",\n    \"The combination of a specific safety device trigger (CO Alarm) and divergent thermal behavior in an unoccupied space rules out simple sensor drift and points to a physical hazard like combustion or gas ignition.\"\n  ],\n  \"key_evidence\": [\n    \"Event 'COAlarm()' triggered at 2026-06-04T03:24:00 in the kitchen.\",\n    \"Kitchen temperature rose from 2320 to 2490 while living room remained near 2470, despite zero occupancy across all sensors during the incident window.\",\n    \"No manual override, reset, or siren activation logs were found between the alarm trigger and the arrival of occupants.\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately dispatch emergency services to investigate the kitchen for fire or hazardous gas presence.\",\n    \"Do not enter the scene until professionals have cleared it; assume the CO alarm and heat source are active.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "fire_risk", "threat_description": "The system indicates a high probability of an unattended kitchen fire or gas leak due to a sustained temperature rise and CO alarm trigger while the house was empty.", "reasoning": ["Pre-incident analysis (C01) establishes a stable baseline where the kitchen temperature (~2320°C equivalent in data units) was consistently lower than the living room (~2330-2350), making the subsequent rapid and sustained heating anomaly statistically significant.", "At 03:24:00, the CO alarm triggered ('COState = 1') concurrently with the kitchen temperature exceeding the living room temperature for the first time since monitoring began, indicating localized heat generation rather than ambient warming.", "Post-trigger data (C02-C03) shows the kitchen temperature continuing to climb steadily (reaching ~2490 by 06:10) while other rooms remain relatively stable, and no human occupancy was detected until over two hours later when cooking appliances were manually turned on, suggesting the threat occurred without intervention.", "The combination of a specific safety device trigger (CO Alarm) and divergent thermal behavior in an unoccupied space rules out simple sensor drift and points to a physical hazard like combustion or gas ignition."], "key_evidence": ["Event 'COAlarm()' triggered at 2026-06-04T03:24:00 in the kitchen.", "Kitchen temperature rose from 2320 to 2490 while living room remained near 2470, despite zero occupancy across all sensors during the incident window.", "No manual override, reset, or siren activation logs were found between the alarm trigger and the arrival of occupants."], "recommended_actions": ["Immediately dispatch emergency services to investigate the kitchen for fire or hazardous gas presence.", "Do not enter the scene until professionals have cleared it; assume the CO alarm and heat source are active."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": true, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 41.220821142196655, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1855, "chunk_count": 24, "signals": {"room_activity": {"living_room": 496, "bedroom": 529, "kitchen": 537, "bathroom": 63, "entrance": 230}, "attribute_frequency": {"Occupancy": 944, "MeasuredValue": 870, "OnOff": 21, "CurrentPositionLiftPercent100ths": 4, "LockState": 4, "StateValue": 4, "COState": 1, "ExpressedState": 1, "CurrentLevel": 1}, "lock_state_flips": 4, "occupancy_events": 944, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"single-event-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_smoke_co_alarm\", \"kitchen_temp_sensor\", \"kitchen_occupancy\"],\n  \"focus_chunk_ids\": [\"C02\"],\n  \"suspected_patterns\": [\n    \"COAlarm event triggered at 03:24:00 indicating potential smoke or carbon monoxide presence\",\n    \"Rapid temperature rise in kitchen (2320 -> 2370 -> 2390) concurrent with alarm\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C02 contains the critical 'Event: COAlarm()' from the kitchen smoke detector, which is a definitive safety threat indicator.\",\n    \"The temperature readings in C02 show an anomalous spike pattern consistent with a fire or gas leak incident starting around this time.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "single-event-safety", "focus_rooms": ["kitchen"], "focus_devices": ["kitchen_smoke_co_alarm", "kitchen_temp_sensor", "kitchen_occupancy"], "focus_chunk_ids": ["C02"], "suspected_patterns": ["COAlarm event triggered at 03:24:00 indicating potential smoke or carbon monoxide presence", "Rapid temperature rise in kitchen (2320 -> 2370 -> 2390) concurrent with alarm"], "why_these_chunks": ["Chunk C02 contains the critical 'Event: COAlarm()' from the kitchen smoke detector, which is a definitive safety threat indicator.", "The temperature readings in C02 show an anomalous spike pattern consistent with a fire or gas leak incident starting around this time."]}, "investigator_raw": "```json\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"False Positive CO Alarm due to environmental interference or sensor malfunction, with subsequent high temperatures caused by an external heat source (e.g., open window near a hot HVAC unit, sunlight exposure, or a nearby appliance running at full capacity).\",\n      \"evidence\": [\"All occupancy sensors report '0' immediately after the alarm, suggesting no one was present to manually trigger it or investigate.\", \"Temperatures are elevated (~24°C) but not extreme for a room-sized space over 2.5 hours, which might indicate gradual heating rather than rapid fire combustion.\"],\n      \"weaknesses\": [\"The temperature in the kitchen is consistently higher than other rooms and shows a slight upward trend, which contradicts typical passive cooling from an open window.\", \"A standard false positive usually triggers a reset or silence within minutes; here, the system continues logging without user intervention.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Early-stage residential fire or gas leak ignition in the kitchen.\",\n      \"threat_type\": \"Fire / Hazardous Gas Leak\",\n      \"evidence\": [\n      \"Definitive Trigger: 'Event: COAlarm()' at 03:24:00 indicates the presence of carbon monoxide or smoke.\",\n      \"Anomalous Thermal Gradient: The kitchen temperature (2370 -> 2438K/°C scale relative to baseline, effectively rising ~68 degrees over time) remains significantly higher than bedroom/living room temperatures.\",\n      \"Sustained Heat Rise: Unlike normal fluctuations, the kitchen temperature shows a consistent monotonic increase throughout the monitoring window, while other rooms remain stable.\",\n      \"Occupancy Context: The house appears empty ('Occupancy = 0') during the incident, meaning the threat is unmitigated and unaddressed by humans.\"\n    ]\n  ],\n  \"most_discriminative_evidence\": [\n    \"The concurrent occurrence of a specific 'COAlarm()' event followed by a sustained, localized temperature rise exclusively in the kitchen, despite all rooms being reported as unoccupied.\"\n  ],\n  \"missing_information\": [\n    \"Pre-incident baseline temperatures for the kitchen to calculate the exact rate of rise.\",\n    \"Status of any manual override buttons or siren activation logs.\",\n    \"Outdoor weather conditions (temperature/humidity) to rule out external environmental influence.\"\n  ]\n}\n```", "investigator_parsed": {"_parse_failed": true, "raw_preview": "```json\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"False Positive CO Alarm due to environmental interference or sensor malfunction, with subsequent high temperatures caused by an external heat source (e.g., open window near a hot HVAC unit, sunlight exposure, or a nearby appliance running at full capacity).\",\n      \"evidence\": [\"All occupancy sensors report '0' immediately after the alarm, suggesting no one was present to manually trigger it or investigate.\", \"Temperatures are elevated (~24°C) but not extreme for a room-sized space over 2.5 hours, which might indicate gradual heating rather than rapid fire combustion.\"],\n      \"weaknesses\": [\"The temperature in the kitchen is consistently higher than other rooms and shows a slight upward trend, which contradicts typical passive cooling from an open window.\", \"A standard false positive usually triggers a reset or silence within minutes; here, the system continues logging without user intervention.\"]\n    }\n "}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C01\", \"C03\"],\n  \"missing_checks\": [\"Verify pre-incident baseline temperatures in C01 to calculate rate of rise accurately.\", \"Check C03 for any subsequent alarm resets, sirens activation, or external sensor data (weather/outside temperature) to rule out environmental interference.\"],\n  \"supervisor_notes\": [\n      \"The investigation correctly identifies the core threat indicators (CO Alarm + Temp Rise) in C02 and formulates valid hypotheses.\",\n      \"However, the evidence is currently insufficient because it relies heavily on a single chunk (C02).\",\n      \"To validate the 'Anomaly' hypothesis vs. the 'False Positive' hypothesis, we need context from adjacent time windows: C01 should establish the pre-incident thermal baseline to confirm if the rise is anomalous or part of a trend, and C03 should check for system responses (sirens/reset) or outdoor conditions that might explain the readings.\",\n      \"Without establishing the baseline (C01) and checking immediate follow-up events/environmental context (C03), the rate-of-rise calculation and exclusion of external factors remain speculative.\"\n    ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C01", "C03"], "missing_checks": ["Verify pre-incident baseline temperatures in C01 to calculate rate of rise accurately.", "Check C03 for any subsequent alarm resets, sirens activation, or external sensor data (weather/outside temperature) to rule out environmental interference."], "supervisor_notes": ["The investigation correctly identifies the core threat indicators (CO Alarm + Temp Rise) in C02 and formulates valid hypotheses.", "However, the evidence is currently insufficient because it relies heavily on a single chunk (C02).", "To validate the 'Anomaly' hypothesis vs. the 'False Positive' hypothesis, we need context from adjacent time windows: C01 should establish the pre-incident thermal baseline to confirm if the rise is anomalous or part of a trend, and C03 should check for system responses (sirens/reset) or outdoor conditions that might explain the readings.", "Without establishing the baseline (C01) and checking immediate follow-up events/environmental context (C03), the rate-of-rise calculation and exclusion of external factors remain speculative."]}, "preview_triage_prompt": "## Query\n以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。\n\n## Layout\nLayout: 独居老人 (Elderly Living Alone)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>, 床头灯<onoff_light>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房运动传感器<occupancy_sensor>\n- living_room: 客厅温度传感器<temperature_sensor>, 客厅灯<dimmable_light>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 496,\n    \"bedroom\": 529,\n    \"kitchen\": 537,\n    \"bathroom\": 63,\n    \"entrance\": 230\n  },\n  \"attribute_frequency\": {\n    \"Occupancy\": 944,\n    \"MeasuredValue\": 870,\n    \"OnOff\": 21,\n    \"CurrentPositionLiftPercent100ths\": 4,\n    \"LockState\": 4,\n    \"StateValue\": 4,\n    \"COState\": 1,\n    \"ExpressedState\": 1,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 944,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-04T00:00:00\",\n    \"end_ts\": \"2026-06-04T01:35:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 24,\n      \"bedroom\": 24,\n      \"kitchen\": 24,\n      \"bathroom\": 4,\n      \"entrance\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"kitchen_occupancy\"\n    ],\n    \"alarmish_count\": 20,\n    \"preview_lines\": [\n      \"[2026-06-04T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2277\",\n      \"[2026-06-04T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2174\",\n      \"[2026-06-04T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2261\",\n      \"[2026-06-04T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-04T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-04T00:00:00] kitchen_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-04T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-04T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0\",\n    ", "preview_verifier_prompt": "## Query\n以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。\n\n## Triage\n{\n  \"latent_task_profile\": \"single-event-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_smoke_co_alarm\", \"kitchen_temp_sensor\", \"kitchen_occupancy\"],\n  \"focus_chunk_ids\": [\"C02\"],\n  \"suspected_patterns\": [\n    \"COAlarm event triggered at 03:24:00 indicating potential smoke or carbon monoxide presence\",\n    \"Rapid temperature rise in kitchen (2320 -> 2370 -> 2390) concurrent with alarm\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C02 contains the critical 'Event: COAlarm()' from the kitchen smoke detector, which is a definitive safety threat indicator.\",\n    \"The temperature readings in C02 show an anomalous spike pattern consistent with a fire or gas leak incident starting around this time.\"\n  ]\n}\n\n## Investigator\n```json\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"False Positive CO Alarm due to environmental interference or sensor malfunction, with subsequent high temperatures caused by an external heat source (e.g., open window near a hot HVAC unit, sunlight exposure, or a nearby appliance running at full capacity).\",\n      \"evidence\": [\"All occupancy sensors report '0' immediately after the alarm, suggesting no one was present to manually trigger it or investigate.\", \"Temperatures are elevated (~24°C) but not extreme for a room-sized space over 2.5 hours, which might indicate gradual heating rather than rapid fire combustion.\"],\n      \"weaknesses\": [\"The temperature in the kitchen is consistently higher than other rooms and shows a slight upward trend, which contradicts typical passive cooling from an open window.\", \"A standard false positive usually triggers a reset or silence within minutes; here, the system continues logging without user intervention.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Early-stage residential fire or gas leak ignition in the kitchen.\",\n      \"threat_type\": \"Fire / Hazardous Gas Leak\",\n      \"evidence\": [\n      \"Definitive Trigger: 'Event: COAlarm()' at 03:24:00 indicates the presence of carbon monoxide or smoke.\",\n      \"Anomalous Thermal Gradient: The kitchen temperature (2370 -> 2438K/°C scale relative to baseline, effectively rising ~68 degrees over time) remains significantly higher than bedroom/living room temperatures.\",\n      \"Sustained Heat Rise: Unlike normal fluctuations, the kitchen temperature shows a consistent monotonic increase throughout the monitoring window, while other r"}}
{"episode_id": "SQ2_TP_B_0220", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq2\\SQ2_TP_B_0220.json", "metadata": {"sq_type": "SQ2", "sq_name": "单事件安全判断", "variant": "TP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "young_professional", "base_date": "2026-06-14T00:00:00", "seed": 20260849, "scenario_id": "WD-03", "total_events": 1569, "anomaly_events_count": 3}, "ground_truth": {"scenario_id": "WD-03", "scenario_name": "无人在家时漏水持续", "category": "water_damage", "is_anomaly": true, "threat_type": "water_leak", "key_evidence": ["漏水传感器持续触发超过10分钟", "全屋无人（所有 occupancy = 0，门锁为 Locked）", "无人处理导致损失持续扩大"], "expected_response": "紧急通知住户，如有智能水阀立即关闭", "difficulty_score": 10, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 1, "D3_cross_device": 2, "D4_temporal_span": 3, "D5_fp_similarity": 2}, "target_room": "bathroom", "injection_time": "2026-06-14T16:57:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"fire_risk\",\n  \"threat_description\": \"The kitchen temperature sensor exhibits physically impossible readings (>2800) and subsequent failure ('None') immediately following cook surface activation, strongly indicating a thermal event (fire or equipment malfunction) that may have been masked by sensor burnout.\",\n  \"reasoning\": [\n    \"Temporal correlation: The cook surface turned ON at 11:52:30, and exactly 30 seconds later the temperature sensor returned 'None' while reporting impossible values (>2800) just prior. This precise timing suggests the sensor failed due to extreme heat generated by the appliance.\",\n    \"Magnitude anomaly: Indoor ambient temperatures never exceed 100°C (~347°F). Readings of 2887 units are physically implausible for normal operation and indicate sensor saturation or destruction from a fire or electrical arc.\",\n    \"Asymmetric recovery: The temperature gradually normalized over an hour after the initial spike, consistent with the cooling down of a hot object or room after a thermal event ceased, rather than a simple software glitch.\"\n  ],\n  \"key_evidence\": [\n    \"[2026-06-14T11:52:30] kitchen_cook_surface | OnOff.OnOff = True\",\n    \"[2026-06-14T11:53:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = None\",\n    \"[2026-06-14T11:45:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2887\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately inspect the kitchen area for signs of smoke, soot, or damaged appliances.\",\n    \"Replace the kitchen temperature sensor as it appears to be permanently compromised.\",\n    \"Check smoke detector and CO alarm logs for this time window to confirm if they were triggered but missed, or if they also failed.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "fire_risk", "threat_description": "The kitchen temperature sensor exhibits physically impossible readings (>2800) and subsequent failure ('None') immediately following cook surface activation, strongly indicating a thermal event (fire or equipment malfunction) that may have been masked by sensor burnout.", "reasoning": ["Temporal correlation: The cook surface turned ON at 11:52:30, and exactly 30 seconds later the temperature sensor returned 'None' while reporting impossible values (>2800) just prior. This precise timing suggests the sensor failed due to extreme heat generated by the appliance.", "Magnitude anomaly: Indoor ambient temperatures never exceed 100°C (~347°F). Readings of 2887 units are physically implausible for normal operation and indicate sensor saturation or destruction from a fire or electrical arc.", "Asymmetric recovery: The temperature gradually normalized over an hour after the initial spike, consistent with the cooling down of a hot object or room after a thermal event ceased, rather than a simple software glitch."], "key_evidence": ["[2026-06-14T11:52:30] kitchen_cook_surface | OnOff.OnOff = True", "[2026-06-14T11:53:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = None", "[2026-06-14T11:45:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2887"], "recommended_actions": ["Immediately inspect the kitchen area for signs of smoke, soot, or damaged appliances.", "Replace the kitchen temperature sensor as it appears to be permanently compromised.", "Check smoke detector and CO alarm logs for this time window to confirm if they were triggered but missed, or if they also failed."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 60.795575857162476, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1569, "chunk_count": 20, "signals": {"room_activity": {"living_room": 481, "master_bedroom": 336, "second_bedroom": 336, "kitchen": 308, "bathroom": 57, "entrance": 51}, "attribute_frequency": {"MeasuredValue": 1158, "Occupancy": 383, "OnOff": 16, "StateValue": 7, "SystemMode": 1, "CurrentPositionLiftPercent100ths": 1, "OperationalState": 1, "LockState": 1}, "lock_state_flips": 1, "occupancy_events": 383, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"single-event-safety | behavior-sequence\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"kitchen_cook_surface\", \"kitchen_window_contact\", \"kitchen_light\"],\n  \"focus_chunk_ids\": [\"C07\", \"C09\"],\n  \"suspected_patterns\": [\n    \"Sensor data corruption (MeasuredValue = None) coinciding with appliance activation\",\n    \"Unusually high temperature readings (>2800 units) suggesting sensor drift or fault before normalization\",\n    \"Window state change (False/Open) detected while cooking surface is active\"\n  ],\n  \"why_these_chunks\": \"Chunk C09 contains a critical anomaly where the kitchen temperature sensor returns 'None' exactly when the cook surface turns on, preceded by impossible temperature values (~2887). This indicates a sensor failure that could mask a fire hazard. Chunk C07 shows the onset of these erratic high values and includes an open window event during cooking, which are key indicators for potential safety incidents requiring immediate investigation.\"\n}", "triage_parsed": {"latent_task_profile": "single-event-safety | behavior-sequence", "focus_rooms": ["kitchen"], "focus_devices": ["kitchen_temp_sensor", "kitchen_cook_surface", "kitchen_window_contact", "kitchen_light"], "focus_chunk_ids": ["C07", "C09"], "suspected_patterns": ["Sensor data corruption (MeasuredValue = None) coinciding with appliance activation", "Unusually high temperature readings (>2800 units) suggesting sensor drift or fault before normalization", "Window state change (False/Open) detected while cooking surface is active"], "why_these_chunks": "Chunk C09 contains a critical anomaly where the kitchen temperature sensor returns 'None' exactly when the cook surface turns on, preceded by impossible temperature values (~2887). This indicates a sensor failure that could mask a fire hazard. Chunk C07 shows the onset of these erratic high values and includes an open window event during cooking, which are key indicators for potential safety incidents requiring immediate investigation."}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Sensor calibration drift or temporary communication glitch causing transient high readings and null values.\",\n      \"evidence\": [\"kitchen_temp_sensor returned 'None' at 09:32:00 after normal operation in C07; similar 'None' at 12:50:00 after cooking ended in C09; other room sensors remained stable (~2500 units) during these events, suggesting a localized kitchen sensor issue rather than a systemic failure.\", \"High values in C09 (2887 -> 2502 over ~1 hour) show a gradual normalization consistent with sensor recovery or environmental cooling after an event.\"],\n      \"weaknesses\": [\"Does not explain the specific temporal correlation between the cook surface activation and the first 'None' reading in C09 (11:53:00). Normal glitches do not consistently coincide with appliance state changes. The magnitude of the spike (>2800) is physically impossible for ambient temperature, indicating a fault mechanism beyond simple drift.\"}\n    ]\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Hidden fire hazard or uncontrolled heating event in the kitchen masked by sensor failure.\",\n      \"threat_type\": \"Fire Hazard / Equipment Failure\",\n      \"evidence\": [\"In C09, at 11:52:30 the cook surface turned ON. Exactly 30 seconds later (11:53:00), the sensor reported 'None', coinciding with the onset of impossible high values (2887 at 11:45, dropping to 2808 at 11:55). This suggests the sensor was overwhelmed or disconnected due to extreme heat/fire.\", \"The pattern of impossible values (2800+) followed by a gradual decline back to normal (2500s) indicates a thermal event that ceased or was mitigated, leaving a cooling residue.\", \"In C07, a window opened while the cook surface was active (or vice versa contextually), potentially exacerbating smoke spread if a fire occurred, though no direct fire signal is present yet.\"],\n      \"weaknesses\": [\"No direct confirmation of flame, smoke detection, or CO alarms triggered in the logs provided.\", \"Occupancy data shows residents were away (Living Room occupancy 0-1, Bedrooms 0) during the peak anomaly period in C09 (11:45-12:00), which may have delayed discovery but does not confirm the cause.\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"Temporal coincidence: In Chunk C09, the kitchen cook surface activates at 11:52:30, and exactly 30 seconds later, the temperature sensor fails ('None') while reporting impossible values (>2800) immediately prior and during the failure. Normal sensor noise does not correlate perfectly with appliance state changes.\",\n    \"Magnitude anomaly: Readings exceeding 2800 units are physically implausible for indoor ambient temperature, strongly indicating a sensor burnout from extreme heat (fire) or electrical arcing rather than software error.\",\n    \"Asymmetric recovery: The return to normal values (~2500) occurs gradually after the initial spike, consistent with cooling down from a thermal event, whereas a simple power cycle would likely reset the sensor differently or immediately.\"\n  ],\n  \"missing_information\": [\n    \"Logs from Smoke Detectors and Carbon Monoxide (CO) sensors for the kitchen.\",\n    \"Video feed or motion sensor data specifically inside the kitchen during the 11:45–12:00 window to verify if a person was interacting with the stove or if an explosion/fire occurred.\",\n    \"Power grid logs to check for simultaneous voltage spikes or circuit breaker trips associated with the cook surface activation.\"\n  ]\n}", "investigator_parsed": {"_parse_failed": true, "raw_preview": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Sensor calibration drift or temporary communication glitch causing transient high readings and null values.\",\n      \"evidence\": [\"kitchen_temp_sensor returned 'None' at 09:32:00 after normal operation in C07; similar 'None' at 12:50:00 after cooking ended in C09; other room sensors remained stable (~2500 units) during these events, suggesting a localized kitchen sensor issue rather than a systemic failure.\", \"High values in C09 (2887 -> 2502 over ~1 hour) show a gradual normalization consistent with sensor recovery or environmental cooling after an event.\"],\n      \"weaknesses\": [\"Does not explain the specific temporal correlation between the cook surface activation and the first 'None' reading in C09 (11:53:00). Normal glitches do not consistently coincide with appliance state changes. The magnitude of the spike (>2800) is physically impossible for ambient temperature, indicating a fault mechanism beyond simple dr"}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [],\n  \"missing_checks\": [\n    \"Verify Smoke Detector and CO sensor logs for the kitchen during C09.\",\n    \"Check power grid logs for voltage spikes or circuit trips at 11:52:30.\",\n    \"Review video/motion data for the kitchen between 11:45-12:00.\",\n    \"Cross-reference Living Room/Bedroom occupancy logs to confirm if residents were truly away during the peak anomaly.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis is on-topic and correctly identifies the core anomaly (sensor failure coinciding with cook surface activation and impossible temperature readings).\",\n    \"Evidence is currently insufficient to definitively classify this as a confirmed safety threat versus a hardware fault without corroborating data from other systems (smoke, CO, power).\",\n    \"The Investigator Output correctly lists specific missing checks; these should be prioritized immediately to rule in/out fire hazards.\",\n    \"No additional time-window chunks (C08, C10) appear strictly necessary beyond the ones already selected (C07, C09) for the initial hypothesis testing, but external system logs are required.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": [], "missing_checks": ["Verify Smoke Detector and CO sensor logs for the kitchen during C09.", "Check power grid logs for voltage spikes or circuit trips at 11:52:30.", "Review video/motion data for the kitchen between 11:45-12:00.", "Cross-reference Living Room/Bedroom occupancy logs to confirm if residents were truly away during the peak anomaly."], "supervisor_notes": ["The analysis is on-topic and correctly identifies the core anomaly (sensor failure coinciding with cook surface activation and impossible temperature readings).", "Evidence is currently insufficient to definitively classify this as a confirmed safety threat versus a hardware fault without corroborating data from other systems (smoke, CO, power).", "The Investigator Output correctly lists specific missing checks; these should be prioritized immediately to rule in/out fire hazards.", "No additional time-window chunks (C08, C10) appear strictly necessary beyond the ones already selected (C07, C09) for the initial hypothesis testing, but external system logs are required."]}, "preview_triage_prompt": "## Query\n以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 481,\n    \"master_bedroom\": 336,\n    \"second_bedroom\": 336,\n    \"kitchen\": 308,\n    \"bathroom\": 57,\n    \"entrance\": 51\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1158,\n    \"Occupancy\": 383,\n    \"OnOff\": 16,\n    \"StateValue\": 7,\n    \"SystemMode\": 1,\n    \"CurrentPositionLiftPercent100ths\": 1,\n    \"OperationalState\": 1,\n    \"LockState\": 1\n  },\n  \"lock_state_flips\": 1,\n  \"occupancy_events\": 383,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-14T00:00:00\",\n    \"end_ts\": \"2026-06-14T01:20:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 20,\n      \"master_bedroom\": 19,\n      \"second_bedroom\": 19,\n      \"kitchen\": 16,\n      \"bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"master_bedroom_occupancy\"\n    ],\n    \"alarmish_count\": 15,\n    \"preview_lines\": [\n      \"[2026-06-14T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2262\",\n      \"[2026-06-14T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2268\",\n      \"[2026-06-14T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2274\",\n      \"[2026-06-14T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2272\",\n      \"[2026-06-14T00:00:00] living_room_occ", "preview_verifier_prompt": "## Query\n以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。\n\n## Triage\n{\n  \"latent_task_profile\": \"single-event-safety | behavior-sequence\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"kitchen_cook_surface\", \"kitchen_window_contact\", \"kitchen_light\"],\n  \"focus_chunk_ids\": [\"C07\", \"C09\"],\n  \"suspected_patterns\": [\n    \"Sensor data corruption (MeasuredValue = None) coinciding with appliance activation\",\n    \"Unusually high temperature readings (>2800 units) suggesting sensor drift or fault before normalization\",\n    \"Window state change (False/Open) detected while cooking surface is active\"\n  ],\n  \"why_these_chunks\": \"Chunk C09 contains a critical anomaly where the kitchen temperature sensor returns 'None' exactly when the cook surface turns on, preceded by impossible temperature values (~2887). This indicates a sensor failure that could mask a fire hazard. Chunk C07 shows the onset of these erratic high values and includes an open window event during cooking, which are key indicators for potential safety incidents requiring immediate investigation.\"\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Sensor calibration drift or temporary communication glitch causing transient high readings and null values.\",\n      \"evidence\": [\"kitchen_temp_sensor returned 'None' at 09:32:00 after normal operation in C07; similar 'None' at 12:50:00 after cooking ended in C09; other room sensors remained stable (~2500 units) during these events, suggesting a localized kitchen sensor issue rather than a systemic failure.\", \"High values in C09 (2887 -> 2502 over ~1 hour) show a gradual normalization consistent with sensor recovery or environmental cooling after an event.\"],\n      \"weaknesses\": [\"Does not explain the specific temporal correlation between the cook surface activation and the first 'None' reading in C09 (11:53:00). Normal glitches do not consistently coincide with appliance state changes. The magnitude of the spike (>2800) is physically impossible for ambient temperature, indicating a fault mechanism beyond simple drift.\"}\n    ]\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Hidden fire hazard or uncontrolled heating event in the kitchen masked by sensor failure.\",\n      \"threat_type\": \"Fire Hazard / Equipment Failure\",\n      \"evidence\": [\"In C09, at 11:52:30 the cook surface turned ON. Exactly 30 seconds later (11:53:00), the sensor reported 'None', coinciding with the onset of imposs"}}
{"episode_id": "SQ2_TP_B_0192", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq2\\SQ2_TP_B_0192.json", "metadata": {"sq_type": "SQ2", "sq_name": "单事件安全判断", "variant": "TP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "family_with_children", "base_date": "2026-06-29T00:00:00", "seed": 20260821, "scenario_id": "INS-02", "total_events": 1841, "anomaly_events_count": 5}, "ground_truth": {"scenario_id": "INS-02", "scenario_name": "门锁暴力破解", "category": "intrusion", "is_anomaly": true, "threat_type": "intrusion", "key_evidence": ["短时间内多次 LockOperationError (InvalidCredential)", "DoorLockAlarm (WrongCodeEntryLimit) 触发", "操作来源为 Keypad 而非 Remote/Auto"], "expected_response": "触发安全警报，临时禁用 Keypad 输入，通知住户", "difficulty_score": 8, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 3, "D2_signal_directness": 1, "D3_cross_device": 1, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "living_room", "injection_time": "2026-06-29T14:17:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"unattended_cooking\",\n  \"threat_description\": \"A stove was activated and remained on for over an hour while the house occupancy sensors reported zero occupants, creating a severe fire hazard in an empty home.\",\n  \"reasoning\": [\n    \"Analysis of Chunk C05 reveals that at timestamp 2026-06-29T06:41:33, the 'kitchen_cook_surface' state changed to True (ON).\",\n    \"At this exact moment and for the subsequent 31 minutes until 07:12:00, all occupancy sensors (living_room, master_bedroom, second_bedroom, bathroom, entrance) consistently reported a value of 0 (empty), indicating no one was present to monitor the cooking activity.\",\n    \"The temperature data, despite exhibiting physically impossible absolute values (>2000°C) indicative of sensor scaling errors or drift, shows a clear, sustained linear increase starting immediately after the stove turned on. This relative trend confirms active heating energy input into the environment without human supervision.\",\n    \"While the door lock sequence in C06 suggests potential tampering, the unattended cooking event poses an immediate and catastrophic property damage risk due to the likelihood of smoke, flame, or gas accumulation in an unmonitored kitchen.\"\n  ],\n  \"key_evidence\": [\n    \"Event log entry at 06:41:33: 'kitchen_cook_surface | OnOff.OnOff = True'.\",\n    \"Concurrent state logs from 06:41:33 to 07:12:00 showing 'living_room_occupancy', 'master_bedroom_occupancy', etc., all equal to 0.\",\n    \"Temperature readings rising steadily from ~2500 to ~2530 during the period the cook surface was ON while the house was reported empty.\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately send a voice alert to the homeowner's mobile device warning of unattended cooking and instructing them to return home or dispatch help.\",\n    \"Trigger emergency services (Fire Department) if video feeds show smoke, flames, or heat signatures consistent with combustion, given the high confidence in the unattended cooking scenario.\",\n    \"Dispatch a security responder or trusted neighbor to verify the status of the residence and extinguish any potential fire.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "unattended_cooking", "threat_description": "A stove was activated and remained on for over an hour while the house occupancy sensors reported zero occupants, creating a severe fire hazard in an empty home.", "reasoning": ["Analysis of Chunk C05 reveals that at timestamp 2026-06-29T06:41:33, the 'kitchen_cook_surface' state changed to True (ON).", "At this exact moment and for the subsequent 31 minutes until 07:12:00, all occupancy sensors (living_room, master_bedroom, second_bedroom, bathroom, entrance) consistently reported a value of 0 (empty), indicating no one was present to monitor the cooking activity.", "The temperature data, despite exhibiting physically impossible absolute values (>2000°C) indicative of sensor scaling errors or drift, shows a clear, sustained linear increase starting immediately after the stove turned on. This relative trend confirms active heating energy input into the environment without human supervision.", "While the door lock sequence in C06 suggests potential tampering, the unattended cooking event poses an immediate and catastrophic property damage risk due to the likelihood of smoke, flame, or gas accumulation in an unmonitored kitchen."], "key_evidence": ["Event log entry at 06:41:33: 'kitchen_cook_surface | OnOff.OnOff = True'.", "Concurrent state logs from 06:41:33 to 07:12:00 showing 'living_room_occupancy', 'master_bedroom_occupancy', etc., all equal to 0.", "Temperature readings rising steadily from ~2500 to ~2530 during the period the cook surface was ON while the house was reported empty."], "recommended_actions": ["Immediately send a voice alert to the homeowner's mobile device warning of unattended cooking and instructing them to return home or dispatch help.", "Trigger emergency services (Fire Department) if video feeds show smoke, flames, or heat signatures consistent with combustion, given the high confidence in the unattended cooking scenario.", "Dispatch a security responder or trusted neighbor to verify the status of the residence and extinguish any potential fire."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 63.99435210227966, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1841, "chunk_count": 24, "signals": {"room_activity": {"living_room": 404, "master_bedroom": 520, "second_bedroom": 336, "kitchen": 303, "bathroom": 48, "entrance": 230}, "attribute_frequency": {"MeasuredValue": 1156, "Occupancy": 645, "OnOff": 15, "StateValue": 7, "LockState": 5, "SystemMode": 1, "OperationalState": 1, "CurrentPositionLiftPercent100ths": 1}, "lock_state_flips": 5, "occupancy_events": 645, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\", \"entrance\", \"master_bedroom\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"kitchen_cook_surface\", \"front_door_lock\", \"front_door_contact\", \"master_bedroom_occupancy\", \"living_room_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C05\", \"C06\", \"C07\"],\n  \"suspected_patterns\": [\n    \"abnormal_temperature_spike\",\n    \"unattended_heating_device\",\n    \"inconsistent_occupancy_and_entry_events\"\n  ],\n  \"why_these_chunks\": [\n    \"C00/C01: Initial data shows nonsensical temperature readings (~2200-2400), indicating sensor calibration failure or device malfunction that invalidates subsequent thermal analysis.\",\n    \"C05: Critical safety window where the kitchen cook surface turns ON while all occupancy sensors report '0' (empty house), creating a high fire risk scenario.\",\n    \"C06: Contradictory events at the entrance show a manual unlock followed by an automatic re-lock and door contact flip, suggesting potential forced entry, tampering, or system glitch requiring immediate verification.\",\n    \"C07: Temperature anomalies persist into this chunk with continued empty-house heating activity, escalating the fire hazard established in C05.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "living_room", "entrance", "master_bedroom"], "focus_devices": ["kitchen_temp_sensor", "kitchen_cook_surface", "front_door_lock", "front_door_contact", "master_bedroom_occupancy", "living_room_temp_sensor"], "focus_chunk_ids": ["C00", "C01", "C05", "C06", "C07"], "suspected_patterns": ["abnormal_temperature_spike", "unattended_heating_device", "inconsistent_occupancy_and_entry_events"], "why_these_chunks": ["C00/C01: Initial data shows nonsensical temperature readings (~2200-2400), indicating sensor calibration failure or device malfunction that invalidates subsequent thermal analysis.", "C05: Critical safety window where the kitchen cook surface turns ON while all occupancy sensors report '0' (empty house), creating a high fire risk scenario.", "C06: Contradictory events at the entrance show a manual unlock followed by an automatic re-lock and door contact flip, suggesting potential forced entry, tampering, or system glitch requiring immediate verification.", "C07: Temperature anomalies persist into this chunk with continued empty-house heating activity, escalating the fire hazard established in C05."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"System malfunction with sensor calibration drift and false occupancy triggers.\",\n      \"evidence\": [\"All temperature sensors report values >2000°C (e.g., 2261, 2533) which is physically impossible for indoor environments, indicating a scale error or unit conversion failure.\", \"Occupancy sensors intermittently report '1' in the master bedroom while other rooms remain '0', possibly due to pet movement or sensor noise rather than human presence.\"],\n      \"weaknesses\": [\"The pattern of temperature readings increasing steadily over time (from ~2200 to ~2550) mimics heat accumulation from an active source, not random noise. The coincidence of the stove turning ON at 06:41 while temperatures were already anomalous suggests a causal link between the device state and the reading magnitude, even if the magnitude is wrong.\", \"A single person moving between rooms could explain intermittent occupancy changes, but cannot explain why *all* temperature sensors across the house simultaneously display impossibly high values that correlate with cooking activity.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Unattended cooking event creating a severe fire hazard under the guise of system error.\",\n      \"threat_type\": \"Fire Hazard / Property Damage\",\n      \"evidence\": [\"At 06:41:33, the kitchen_cook_surface turns ON despite all occupancy sensors reporting '0' (empty house).\", \"Temperature readings immediately begin a sustained, linear climb consistent with heating (e.g., rising from ~2500 to ~2560), confirming energy input into the environment.\", \"The cook surface remains ON for over 30 minutes (until 07:12) without any subsequent occupancy detection, allowing unmonitored heating to continue.\", \"Even if the absolute numbers are scaled errors, the relative increase indicates a real thermal event occurring in an empty house.\"],\n      \"weaknesses\": [\"If the entire data stream is corrupted by a firmware bug, the correlation between the specific action (stove ON) and the subsequent data trend might be coincidental rather than causal.\"],\n      \"discriminative_note\": \"The temporal alignment of the device state change (Stove ON) with the start of the thermal ramp-up is the strongest evidence against total system corruption; a glitch would likely affect all fields randomly, not specifically escalate during a power-on event.\"\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Forced entry or unauthorized access attempt at the front door.\",\n      \"threat_type\": \"Burglary / Unauthorized Access\",\n      \"evidence\": [\"At 07:49:30, a manual lock operation occurs on the front door.\", \"Immediately after (07:49:32), the door contact flips to False (open), suggesting the door was forced open or removed.\", \"The door contact flips back to True (closed) within seconds (07:49:34), followed by an automatic re-locking event.\", \"This rapid sequence (Open -> Close -> Lock) without a corresponding 'entering' occupancy event at the entrance sensor initially suggests mechanical manipulation (prying) rather than standard entry.\"],\n      \"weaknesses\": [\"The sequence could represent a user fumbling with the lock and accidentally pulling the door slightly before it latched, though the speed makes this less likely.\", \"The high ambient temperature in the home could be causing expansion of components leading to spurious contact signals.\"],\n      \"discriminative_note\": \"The combination of Manual Unlock -> Contact Open -> Contact Close -> Auto Lock creates a 'tamper' signature distinct from normal use where Occupancy should transition 0->1 upon entry.\"\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The exact timestamp correlation: KitchenCookSurface=ON at 06:41:33 coincides precisely with the start of the steep temperature rise, implying the stove is the heat source despite the empty house status.\",\n    \"The specific lock sequence at 07:49:30-07:49:35 showing Manual Op -> Door Open -> Door Closed -> Auto Lock, which deviates from standard user behavior patterns.\"\n  ],\n  \"missing_information\": [\n    \"Video footage from the kitchen to visually confirm smoke, flames, or lack of activity.\",\n    \"Raw voltage/current draw data from the kitchen circuit breaker to verify the stove is actually consuming power.\",\n    \"History of the front door lock's previous states to determine if the 'manual unlock' was part of a normal routine or an anomaly.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "System malfunction with sensor calibration drift and false occupancy triggers.", "evidence": ["All temperature sensors report values >2000°C (e.g., 2261, 2533) which is physically impossible for indoor environments, indicating a scale error or unit conversion failure.", "Occupancy sensors intermittently report '1' in the master bedroom while other rooms remain '0', possibly due to pet movement or sensor noise rather than human presence."], "weaknesses": ["The pattern of temperature readings increasing steadily over time (from ~2200 to ~2550) mimics heat accumulation from an active source, not random noise. The coincidence of the stove turning ON at 06:41 while temperatures were already anomalous suggests a causal link between the device state and the reading magnitude, even if the magnitude is wrong.", "A single person moving between rooms could explain intermittent occupancy changes, but cannot explain why *all* temperature sensors across the house simultaneously display impossibly high values that correlate with cooking activity."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Unattended cooking event creating a severe fire hazard under the guise of system error.", "threat_type": "Fire Hazard / Property Damage", "evidence": ["At 06:41:33, the kitchen_cook_surface turns ON despite all occupancy sensors reporting '0' (empty house).", "Temperature readings immediately begin a sustained, linear climb consistent with heating (e.g., rising from ~2500 to ~2560), confirming energy input into the environment.", "The cook surface remains ON for over 30 minutes (until 07:12) without any subsequent occupancy detection, allowing unmonitored heating to continue.", "Even if the absolute numbers are scaled errors, the relative increase indicates a real thermal event occurring in an empty house."], "weaknesses": ["If the entire data stream is corrupted by a firmware bug, the correlation between the specific action (stove ON) and the subsequent data trend might be coincidental rather than causal."], "discriminative_note": "The temporal alignment of the device state change (Stove ON) with the start of the thermal ramp-up is the strongest evidence against total system corruption; a glitch would likely affect all fields randomly, not specifically escalate during a power-on event."}, {"id": "A2", "description": "Forced entry or unauthorized access attempt at the front door.", "threat_type": "Burglary / Unauthorized Access", "evidence": ["At 07:49:30, a manual lock operation occurs on the front door.", "Immediately after (07:49:32), the door contact flips to False (open), suggesting the door was forced open or removed.", "The door contact flips back to True (closed) within seconds (07:49:34), followed by an automatic re-locking event.", "This rapid sequence (Open -> Close -> Lock) without a corresponding 'entering' occupancy event at the entrance sensor initially suggests mechanical manipulation (prying) rather than standard entry."], "weaknesses": ["The sequence could represent a user fumbling with the lock and accidentally pulling the door slightly before it latched, though the speed makes this less likely.", "The high ambient temperature in the home could be causing expansion of components leading to spurious contact signals."], "discriminative_note": "The combination of Manual Unlock -> Contact Open -> Contact Close -> Auto Lock creates a 'tamper' signature distinct from normal use where Occupancy should transition 0->1 upon entry."}], "most_discriminative_evidence": ["The exact timestamp correlation: KitchenCookSurface=ON at 06:41:33 coincides precisely with the start of the steep temperature rise, implying the stove is the heat source despite the empty house status.", "The specific lock sequence at 07:49:30-07:49:35 showing Manual Op -> Door Open -> Door Closed -> Auto Lock, which deviates from standard user behavior patterns."], "missing_information": ["Video footage from the kitchen to visually confirm smoke, flames, or lack of activity.", "Raw voltage/current draw data from the kitchen circuit breaker to verify the stove is actually consuming power.", "History of the front door lock's previous states to determine if the 'manual unlock' was part of a normal routine or an anomaly."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C02\", \"C03\", \"C04\"],\n  \"missing_checks\": [\n    \"Verify if the temperature spike started before or exactly when the stove turned ON (C02/C03 are critical to establish causality vs pre-existing error).\",\n    \"Check for any occupancy events in the kitchen or hallway during the unattended cooking window (C02-C04) to rule out a person being present but not detected.\",\n    \"Review door lock history immediately preceding C06 to confirm if the 'manual unlock' was an anomaly or part of a routine.\"\n  ],\n  \"supervisor_notes\": [\n    \"The current analysis focuses heavily on C00/C01 (sensor failure) and C05/C07 (fire risk), with some attention to C06 (door tampering). However, the causal link between the stove activation and the temperature rise is not fully established without seeing the data in the intervals immediately prior to 06:41 (C02, C03).\",\n    \"We must determine if the temperature was already spiking at 2200°C before the stove turned on. If yes, it's purely a sensor bug. If no, the stove triggered it.\",\n    \"Missing chunks C02, C03, and C04 are required to fill the gap between the initial anomalous readings and the specific stove activation event to validate the 'unattended cooking' hypothesis definitively.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C02", "C03", "C04"], "missing_checks": ["Verify if the temperature spike started before or exactly when the stove turned ON (C02/C03 are critical to establish causality vs pre-existing error).", "Check for any occupancy events in the kitchen or hallway during the unattended cooking window (C02-C04) to rule out a person being present but not detected.", "Review door lock history immediately preceding C06 to confirm if the 'manual unlock' was an anomaly or part of a routine."], "supervisor_notes": ["The current analysis focuses heavily on C00/C01 (sensor failure) and C05/C07 (fire risk), with some attention to C06 (door tampering). However, the causal link between the stove activation and the temperature rise is not fully established without seeing the data in the intervals immediately prior to 06:41 (C02, C03).", "We must determine if the temperature was already spiking at 2200°C before the stove turned on. If yes, it's purely a sensor bug. If no, the stove triggered it.", "Missing chunks C02, C03, and C04 are required to fill the gap between the initial anomalous readings and the specific stove activation event to validate the 'unattended cooking' hypothesis definitively."]}, "preview_triage_prompt": "## Query\n以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 404,\n    \"master_bedroom\": 520,\n    \"second_bedroom\": 336,\n    \"kitchen\": 303,\n    \"bathroom\": 48,\n    \"entrance\": 230\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1156,\n    \"Occupancy\": 645,\n    \"OnOff\": 15,\n    \"StateValue\": 7,\n    \"LockState\": 5,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"CurrentPositionLiftPercent100ths\": 1\n  },\n  \"lock_state_flips\": 5,\n  \"occupancy_events\": 645,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-29T00:00:00\",\n    \"end_ts\": \"2026-06-29T01:20:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 20,\n      \"master_bedroom\": 19,\n      \"second_bedroom\": 19,\n      \"kitchen\": 16,\n      \"bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"master_bedroom_occupancy\"\n    ],\n    \"alarmish_count\": 15,\n    \"preview_lines\": [\n      \"[2026-06-29T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2261\",\n      \"[2026-06-29T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2275\",\n      \"[2026-06-29T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2271\",\n      \"[2026-06-29T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2278\",\n      \"[2026-06-29T00:00:00] living_room_oc", "preview_verifier_prompt": "## Query\n以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\", \"entrance\", \"master_bedroom\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"kitchen_cook_surface\", \"front_door_lock\", \"front_door_contact\", \"master_bedroom_occupancy\", \"living_room_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C05\", \"C06\", \"C07\"],\n  \"suspected_patterns\": [\n    \"abnormal_temperature_spike\",\n    \"unattended_heating_device\",\n    \"inconsistent_occupancy_and_entry_events\"\n  ],\n  \"why_these_chunks\": [\n    \"C00/C01: Initial data shows nonsensical temperature readings (~2200-2400), indicating sensor calibration failure or device malfunction that invalidates subsequent thermal analysis.\",\n    \"C05: Critical safety window where the kitchen cook surface turns ON while all occupancy sensors report '0' (empty house), creating a high fire risk scenario.\",\n    \"C06: Contradictory events at the entrance show a manual unlock followed by an automatic re-lock and door contact flip, suggesting potential forced entry, tampering, or system glitch requiring immediate verification.\",\n    \"C07: Temperature anomalies persist into this chunk with continued empty-house heating activity, escalating the fire hazard established in C05.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"System malfunction with sensor calibration drift and false occupancy triggers.\",\n      \"evidence\": [\"All temperature sensors report values >2000°C (e.g., 2261, 2533) which is physically impossible for indoor environments, indicating a scale error or unit conversion failure.\", \"Occupancy sensors intermittently report '1' in the master bedroom while other rooms remain '0', possibly due to pet movement or sensor noise rather than human presence.\"],\n      \"weaknesses\": [\"The pattern of temperature readings increasing steadily over time (from ~2200 to ~2550) mimics heat accumulation from an active source, not random noise. The coincidence of the stove turning ON at 06:41 while temperatures were already anomalous suggests a causal link between the device state and the reading magnitude, even if the magnitude is wrong.\", \"A single person moving between rooms could explain intermittent occupancy changes, but cannot explain why *all* temperature sensors across the house simultaneously display impossibly high values that correlate with cooking activity.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\":"}}
{"episode_id": "SQ3_FP_C_0581", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq3\\SQ3_FP_C_0581.json", "metadata": {"sq_type": "SQ3", "sq_name": "行为序列分析", "variant": "FP", "layout_id": "C", "layout_name": "三室两厅 (3BR)", "profile_id": "family_with_children", "base_date": "2026-06-18T00:00:00", "seed": 20261210, "scenario_id": "CH-04", "total_events": 2296, "anomaly_events_count": 5}, "ground_truth": {"scenario_id": "CH-04-FP", "scenario_name": "CH-04-FP: 家长在玄关操作门锁", "category": "child_specific", "is_anomaly": false, "threat_type": "none", "key_difference": "成人成功解锁（UserIndex=1，无LockOperationError），不是儿童输错密码", "difficulty_score": 9, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "balcony", "injection_time": "2026-06-18T15:30:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"lock_malfunction\",\n  \"threat_description\": \"The front door lock and contact sensor reported a logical contradiction (door locked but contact open) immediately following a manual lock operation, indicating a potential mechanical failure or sensor malfunction rather than an intrusion.\",\n  \"reasoning\": [\n      \"Step 1: Analyze the critical event in C08 at 18:07:00 where 'front_door_lock' executed a Manual LockOperation, setting the state to Locked (2).\",\n      \"Step 2: Identify the immediate anomaly at 18:07:02 where 'front_door_contact' reported StateValue = False (Open), creating a physical impossibility if the lock successfully engaged the latch, suggesting either the lock failed to close the bolt, the contact sensor is faulty, or someone tampered with the door mechanism.\",\n      \"Step 3: Evaluate subsequent logs (C09-C14) which show consistent occupancy patterns, authorized cooking activities, and eventual proper auto-locking of the door at 22:38:28 without further conflicts, ruling out sustained forced entry and pointing towards an isolated hardware or sensor error.\",\n      \"Step 4: Conclude that while the temperature drop was noted, it correlates with window opening events (C12) and lacks evidence of HVAC failure, leaving the security sensor conflict as the primary high-confidence anomaly.\"\n    ],\n  \"key_evidence\": [\n      \"At 18:07:00-18:07:02: LockState=Locked followed immediately by DoorContact=False (Open).\",\n      \"At 22:38:28: Door automatically locked and Contact reported True (Closed) correctly, confirming the system can function properly under normal conditions.\"\n    ],\n  \"recommended_actions\": [\n      \"Inspect the front door lock mechanism for jamming, broken bolts, or misalignment.\",\n      \"Test and replace the front door magnetic contact sensor if the lock mechanism appears physically sound.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "lock_malfunction", "threat_description": "The front door lock and contact sensor reported a logical contradiction (door locked but contact open) immediately following a manual lock operation, indicating a potential mechanical failure or sensor malfunction rather than an intrusion.", "reasoning": ["Step 1: Analyze the critical event in C08 at 18:07:00 where 'front_door_lock' executed a Manual LockOperation, setting the state to Locked (2).", "Step 2: Identify the immediate anomaly at 18:07:02 where 'front_door_contact' reported StateValue = False (Open), creating a physical impossibility if the lock successfully engaged the latch, suggesting either the lock failed to close the bolt, the contact sensor is faulty, or someone tampered with the door mechanism.", "Step 3: Evaluate subsequent logs (C09-C14) which show consistent occupancy patterns, authorized cooking activities, and eventual proper auto-locking of the door at 22:38:28 without further conflicts, ruling out sustained forced entry and pointing towards an isolated hardware or sensor error.", "Step 4: Conclude that while the temperature drop was noted, it correlates with window opening events (C12) and lacks evidence of HVAC failure, leaving the security sensor conflict as the primary high-confidence anomaly."], "key_evidence": ["At 18:07:00-18:07:02: LockState=Locked followed immediately by DoorContact=False (Open).", "At 22:38:28: Door automatically locked and Contact reported True (Closed) correctly, confirming the system can function properly under normal conditions."], "recommended_actions": ["Inspect the front door lock mechanism for jamming, broken bolts, or misalignment.", "Test and replace the front door magnetic contact sensor if the lock mechanism appears physically sound."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 53.85282874107361, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1325, "chunk_count": 17, "signals": {"room_activity": {"living_room": 233, "master_bedroom": 292, "kids_room": 293, "kitchen": 153, "dining_room": 147, "entrance": 159, "second_bedroom": 24, "master_bathroom": 24}, "attribute_frequency": {"Occupancy": 712, "MeasuredValue": 582, "OnOff": 13, "StateValue": 6, "LockState": 3, "CurrentPositionLiftPercent100ths": 2, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 3, "occupancy_events": 712, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"behavior-sequence | composite-safety\",\n  \"focus_rooms\": [\"entrance\", \"kitchen\", \"living_room\", \"kids_room\", \"master_bedroom\"],\n  \"focus_devices\": [\"front_door_lock\", \"front_door_contact\", \"occupancy_sensor (multiple rooms)\", \"temperature_sensor (multiple rooms)\"],\n  \"focus_chunk_ids\": [\"C08\", \"C12\", \"C00\", \"C16\"],\n  \"suspected_patterns\": [\n    \"Occupancy mismatch: High occupancy events in 'kids_room' and 'living_room' persist late into the night (C12, C15), while other bedrooms show low activity, suggesting potential unauthorized access or a family member staying up unusually late.\",\n    \"Door state anomaly: A manual lock operation occurred in C08 followed immediately by the door contact sensor reporting open (False), indicating the door was unlocked/reopened after being secured.\",\n    \"Temperature drift: Room temperatures dropped significantly from ~25°C to ~22°C over the period, potentially indicating HVAC failure or windows left open during high occupancy.\"\n  ],\n  \"why_these_chunks\": [\n    \"C08 contains the critical security event sequence of locking/unlocking the front door with conflicting sensor states.\",\n    \"C12 shows the latest timestamped occupancy data revealing active presence in the children's room and living area late at night, which deviates from typical sleep patterns for these zones.\",\n    \"C00 establishes the baseline temperature readings (~25°C) to calculate the magnitude of the subsequent cooling trend observed across chunks.\",\n    \"C16 shows a reduction in total event count and activity levels near the end of the log, helping to define the transition from the anomalous active period to a quieter state.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "behavior-sequence | composite-safety", "focus_rooms": ["entrance", "kitchen", "living_room", "kids_room", "master_bedroom"], "focus_devices": ["front_door_lock", "front_door_contact", "occupancy_sensor (multiple rooms)", "temperature_sensor (multiple rooms)"], "focus_chunk_ids": ["C08", "C12", "C00", "C16"], "suspected_patterns": ["Occupancy mismatch: High occupancy events in 'kids_room' and 'living_room' persist late into the night (C12, C15), while other bedrooms show low activity, suggesting potential unauthorized access or a family member staying up unusually late.", "Door state anomaly: A manual lock operation occurred in C08 followed immediately by the door contact sensor reporting open (False), indicating the door was unlocked/reopened after being secured.", "Temperature drift: Room temperatures dropped significantly from ~25°C to ~22°C over the period, potentially indicating HVAC failure or windows left open during high occupancy."], "why_these_chunks": ["C08 contains the critical security event sequence of locking/unlocking the front door with conflicting sensor states.", "C12 shows the latest timestamped occupancy data revealing active presence in the children's room and living area late at night, which deviates from typical sleep patterns for these zones.", "C00 establishes the baseline temperature readings (~25°C) to calculate the magnitude of the subsequent cooling trend observed across chunks.", "C16 shows a reduction in total event count and activity levels near the end of the log, helping to define the transition from the anomalous active period to a quieter state."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Extended Family Gathering or Sleepover: The high occupancy in the kids' room and living area late at night, combined with active kitchen use (cooking surface on) and window opening, suggests a planned family event where children are staying up late or sleeping in common areas.\",\n      \"evidence\": [\"High occupancy counts in 'kids_room' (293) and 'living_room' (233) vs low in guest rooms ('second_bedroom': 24),\", \"Activity continues late into the log (C12, C16 timestamps show presence past 21:00 and 23:00),\", \"User-initiated device state changes (turning on AC, lights, cooking surface) indicate authorized human control.\"],\n      \"weaknesses\": [\"Does not fully explain the specific security sensor conflict where the door lock engaged but the contact sensor immediately reported 'open' (False).\"],\n      \"threat_level\": \"Low\"\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Forced Entry or Tampering Attempt: An intruder may have entered via the front door, manually unlocked/relocked it to bypass a latch or create noise, triggering a false negative on the magnetic contact sensor, followed by movement into the house.\",\n      \"evidence\": [\"In C08, 'front_door_lock' shows Manual LockOperation at 18:07:00, followed immediately by 'front_door_contact' StateValue = False (Open) at 18:07:02 despite the lock engaging,\", \"Occupancy sensors in 'entrance', 'kitchen', and 'kids_room' activate within seconds of this door anomaly sequence,\", \"The temperature drop (from ~25°C to ~23°C) correlates with windows being opened (C12: kids_room_window lift=100%) which could be part of an environmental manipulation or simply coincidental ventilation after entry.\"],\n      \"weaknesses\": [\"The sequence occurs during evening hours when residents are typically home; the subsequent activity (cooking, AC usage) looks consistent with normal household behavior rather than intrusion.\", \"No additional forced entry indicators like glass breakage or alarm triggers are explicitly logged beyond the sensor conflict.\"],\n      \"threat_level\": \"Medium-High\"\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"HVAC/System Failure leading to Abnormal Cooling: The significant temperature drop across all zones without a corresponding increase in fan/AC cycle events suggests a system failure rather than user action, potentially compromising comfort or safety if extreme.\",\n      \"evidence\": [\"Temperature drops from ~25°C (C00) to ~23°C (C08) and remains low in C12/C16,\", \"Despite 'living_room_ac' turning ON in C08, temperatures continue to trend downward or stabilize at lower levels rather than rising as expected for cooling,\", \"Correlation with window opening (C12) exacerbates heat loss.\"],\n      \"weaknesses\": [\"A 2-degree drop is within normal diurnal variance for summer evenings in many climates; it does not necessarily indicate a critical failure.\", \"The AC activation suggests the system is responding to conditions, albeit perhaps insufficiently.\"],\n      \"threat_level\": \"Low\"\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The timestamped sequence in C08: LockOperation (Manual) at 18:07:00 followed by DoorContact=False at 18:07:02 indicates a logical contradiction between mechanical locking and physical closure status.\",\n    \"Discrepancy between total activity volume: High occupancy in primary living/sleep areas vs very low occupancy in secondary bedrooms ('second_bedroom': 24), suggesting either a shift in family routine or unauthorized access to restricted zones.\",\n    \"Window covering adjustment (100% open) in C12 occurring simultaneously with sustained high occupancy and temperature fluctuations.\"\n  ],\n  \"missing_information\": [\n    \"Historical data regarding typical daily occupancy patterns for this specific household to distinguish between 'late night sleepover' and 'unusual absence from bedrooms'.\",\n    \"Detailed logs of the HVAC controller's output (fan speed, compressor status) to verify if the AC unit was actually running effectively or just cycling off.\",\n    \"Video footage or motion detection specifics to determine if the person triggering the door lock/contact sequence was inside or outside the perimeter at that exact moment.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Extended Family Gathering or Sleepover: The high occupancy in the kids' room and living area late at night, combined with active kitchen use (cooking surface on) and window opening, suggests a planned family event where children are staying up late or sleeping in common areas.", "evidence": ["High occupancy counts in 'kids_room' (293) and 'living_room' (233) vs low in guest rooms ('second_bedroom': 24),", "Activity continues late into the log (C12, C16 timestamps show presence past 21:00 and 23:00),", "User-initiated device state changes (turning on AC, lights, cooking surface) indicate authorized human control."], "weaknesses": ["Does not fully explain the specific security sensor conflict where the door lock engaged but the contact sensor immediately reported 'open' (False)."], "threat_level": "Low"}], "anomaly_hypotheses": [{"id": "A1", "description": "Forced Entry or Tampering Attempt: An intruder may have entered via the front door, manually unlocked/relocked it to bypass a latch or create noise, triggering a false negative on the magnetic contact sensor, followed by movement into the house.", "evidence": ["In C08, 'front_door_lock' shows Manual LockOperation at 18:07:00, followed immediately by 'front_door_contact' StateValue = False (Open) at 18:07:02 despite the lock engaging,", "Occupancy sensors in 'entrance', 'kitchen', and 'kids_room' activate within seconds of this door anomaly sequence,", "The temperature drop (from ~25°C to ~23°C) correlates with windows being opened (C12: kids_room_window lift=100%) which could be part of an environmental manipulation or simply coincidental ventilation after entry."], "weaknesses": ["The sequence occurs during evening hours when residents are typically home; the subsequent activity (cooking, AC usage) looks consistent with normal household behavior rather than intrusion.", "No additional forced entry indicators like glass breakage or alarm triggers are explicitly logged beyond the sensor conflict."], "threat_level": "Medium-High"}, {"id": "A2", "description": "HVAC/System Failure leading to Abnormal Cooling: The significant temperature drop across all zones without a corresponding increase in fan/AC cycle events suggests a system failure rather than user action, potentially compromising comfort or safety if extreme.", "evidence": ["Temperature drops from ~25°C (C00) to ~23°C (C08) and remains low in C12/C16,", "Despite 'living_room_ac' turning ON in C08, temperatures continue to trend downward or stabilize at lower levels rather than rising as expected for cooling,", "Correlation with window opening (C12) exacerbates heat loss."], "weaknesses": ["A 2-degree drop is within normal diurnal variance for summer evenings in many climates; it does not necessarily indicate a critical failure.", "The AC activation suggests the system is responding to conditions, albeit perhaps insufficiently."], "threat_level": "Low"}], "most_discriminative_evidence": ["The timestamped sequence in C08: LockOperation (Manual) at 18:07:00 followed by DoorContact=False at 18:07:02 indicates a logical contradiction between mechanical locking and physical closure status.", "Discrepancy between total activity volume: High occupancy in primary living/sleep areas vs very low occupancy in secondary bedrooms ('second_bedroom': 24), suggesting either a shift in family routine or unauthorized access to restricted zones.", "Window covering adjustment (100% open) in C12 occurring simultaneously with sustained high occupancy and temperature fluctuations."], "missing_information": ["Historical data regarding typical daily occupancy patterns for this specific household to distinguish between 'late night sleepover' and 'unusual absence from bedrooms'.", "Detailed logs of the HVAC controller's output (fan speed, compressor status) to verify if the AC unit was actually running effectively or just cycling off.", "Video footage or motion detection specifics to determine if the person triggering the door lock/contact sequence was inside or outside the perimeter at that exact moment."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C09\", \"C10\", \"C14\"],\n  \"missing_checks\": [\n    \"Verify HVAC controller output logs (fan/compressor status) in C09 and C10 to confirm AC failure vs. window-related cooling.\",\n    \"Cross-reference occupancy sensor data with specific motion detection timestamps in C14 to determine if the late-night activity aligns with authorized resident movement or intrusion patterns.\"\n  ],\n  \"supervisor_notes\": [\n    \"The investigation correctly identified the door lock/contact conflict (C08) as a critical anomaly but relied heavily on C12 and C16 for context regarding temperature and occupancy trends.\",\n    \"Evidence is insufficient because it lacks granular temporal data from the middle of the night (C09-C11, C13-C15) to establish a continuous timeline between the door anomaly and the subsequent high occupancy.\",\n    \"Specifically, C09-C11 are needed to see if the 'unauthorized access' hypothesis holds up immediately after the door event, while C14 is crucial to verify the nature of the late-night movement before concluding it was a planned sleepover.\",\n    \"The temperature analysis also needs detailed HVAC logs (likely in C09/C10 based on sequential logging) to rule out system failure definitively.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C09", "C10", "C14"], "missing_checks": ["Verify HVAC controller output logs (fan/compressor status) in C09 and C10 to confirm AC failure vs. window-related cooling.", "Cross-reference occupancy sensor data with specific motion detection timestamps in C14 to determine if the late-night activity aligns with authorized resident movement or intrusion patterns."], "supervisor_notes": ["The investigation correctly identified the door lock/contact conflict (C08) as a critical anomaly but relied heavily on C12 and C16 for context regarding temperature and occupancy trends.", "Evidence is insufficient because it lacks granular temporal data from the middle of the night (C09-C11, C13-C15) to establish a continuous timeline between the door anomaly and the subsequent high occupancy.", "Specifically, C09-C11 are needed to see if the 'unauthorized access' hypothesis holds up immediately after the door event, while C14 is crucial to verify the nature of the late-night movement before concluding it was a planned sleepover.", "The temperature analysis also needs detailed HVAC logs (likely in C09/C10 based on sequential logging) to rule out system failure definitively."]}, "preview_triage_prompt": "## Query\n以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Layout\nLayout: 三室两厅 (3BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kids_room: 儿童房温度传感器<temperature_sensor>, 儿童房灯<dimmable_light>, 儿童房窗帘<window_covering>, 儿童房窗户传感器<contact_sensor>, 儿童房运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅副灯<dimmable_light>, 客厅氛围灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘1<window_covering>, 客厅窗户传感器1<contact_sensor>, 客厅窗户传感器2<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n- master_bathroom: 主卫漏水传感器<water_leak_detector>, 主卫灯<onoff_light>, 主卫运动传感器<occupancy_sensor>\n- master_bedroom: 主卧床头灯<onoff_light>, 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>\n- second_bedroom: 次卧灯<dimmable_light>, 次卧空调<air_conditioner>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 233,\n    \"master_bedroom\": 292,\n    \"kids_room\": 293,\n    \"kitchen\": 153,\n    \"dining_room\": 147,\n    \"entrance\": 159,\n    \"second_bedroom\": 24,\n    \"master_bathroom\": 24\n  },\n  \"attribute_frequency\": {\n    \"Occupancy\": 712,\n    \"MeasuredValue\": 582,\n    \"OnOff\": 13,\n    \"StateValue\": 6,\n    \"LockState\": 3,\n    \"CurrentPositionLiftPercent100ths\": 2,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 3,\n  \"occupancy_events\": 712,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-18T11:55:00\",\n    \"end_ts\": \"2026-06-18T12:40:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 12,\n      \"master_bedroom\": 19,\n      \"kids_room\": 18,\n      \"kitchen\": 9,\n      \"dining_room\": 9,\n      \"entrance\": 9,\n      \"second_bedroom\": 2,\n      \"master_bathroom\": 2\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"kids_room_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"master_bedroom_occupancy\",\n      \"kids_room_occupancy\"\n    ]", "preview_verifier_prompt": "## Query\n以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Triage\n{\n  \"latent_task_profile\": \"behavior-sequence | composite-safety\",\n  \"focus_rooms\": [\"entrance\", \"kitchen\", \"living_room\", \"kids_room\", \"master_bedroom\"],\n  \"focus_devices\": [\"front_door_lock\", \"front_door_contact\", \"occupancy_sensor (multiple rooms)\", \"temperature_sensor (multiple rooms)\"],\n  \"focus_chunk_ids\": [\"C08\", \"C12\", \"C00\", \"C16\"],\n  \"suspected_patterns\": [\n    \"Occupancy mismatch: High occupancy events in 'kids_room' and 'living_room' persist late into the night (C12, C15), while other bedrooms show low activity, suggesting potential unauthorized access or a family member staying up unusually late.\",\n    \"Door state anomaly: A manual lock operation occurred in C08 followed immediately by the door contact sensor reporting open (False), indicating the door was unlocked/reopened after being secured.\",\n    \"Temperature drift: Room temperatures dropped significantly from ~25°C to ~22°C over the period, potentially indicating HVAC failure or windows left open during high occupancy.\"\n  ],\n  \"why_these_chunks\": [\n    \"C08 contains the critical security event sequence of locking/unlocking the front door with conflicting sensor states.\",\n    \"C12 shows the latest timestamped occupancy data revealing active presence in the children's room and living area late at night, which deviates from typical sleep patterns for these zones.\",\n    \"C00 establishes the baseline temperature readings (~25°C) to calculate the magnitude of the subsequent cooling trend observed across chunks.\",\n    \"C16 shows a reduction in total event count and activity levels near the end of the log, helping to define the transition from the anomalous active period to a quieter state.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Extended Family Gathering or Sleepover: The high occupancy in the kids' room and living area late at night, combined with active kitchen use (cooking surface on) and window opening, suggests a planned family event where children are staying up late or sleeping in common areas.\",\n      \"evidence\": [\"High occupancy counts in 'kids_room' (293) and 'living_room' (233) vs low in guest rooms ('second_bedroom': 24),\", \"Activity continues late into the log (C12, C16 timestamps show presence past 21:00 and 23:00),\", \"User-initiated device state changes (turning on AC, lights, cooking surface) indicate authorized human control.\"],\n      \"weaknesses\": [\"Does not fu"}}
{"episode_id": "SQ3_FP_B_0583", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq3\\SQ3_FP_B_0583.json", "metadata": {"sq_type": "SQ3", "sq_name": "行为序列分析", "variant": "FP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "family_with_children", "base_date": "2026-06-10T00:00:00", "seed": 20261212, "scenario_id": "INS-05", "total_events": 1841, "anomaly_events_count": 6}, "ground_truth": {"scenario_id": "INS-05-FP", "scenario_name": "INS-05-FP: 住户换了新手机/手表解锁", "category": "intrusion", "is_anomaly": false, "threat_type": "none", "key_difference": "虽然用了不常用的RFID方式解锁，但进门后最终开灯、正常活动，行为模式与住户一致", "difficulty_score": 13, "difficulty_level": 3, "difficulty_label": "L3_composite_reasoning", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 3, "D3_cross_device": 3, "D4_temporal_span": 2, "D5_fp_similarity": 3}, "target_room": "second_bedroom", "injection_time": "2026-06-10T15:18:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": false,\n  \"confidence\": \"high\",\n  \"threat_type\": \"none\",\n  \"threat_description\": \"No safety threats detected; the initial sensor data gap was a transient error that resolved shortly after normal household activity resumed.\",\n  \"reasoning\": [\n      \"Step 1: Analyzed the temporal sequence in C01 showing cooktop off (18:50), window open (18:50:30), and kitchen temp sensor reporting 'None' (18:51).\",\n      \"Step 2: Verified subsequent chunks (C01-C03) which show the kitchen_temp_sensor resuming valid temperature readings at 18:55:00 and remaining stable through the end of the log.\",\n      \"Step 3: Confirmed that no other safety indicators (e.g., prolonged high heat, unauthorized access, or persistent sensor failure) were present, attributing the brief outage to a transient glitch during routine ventilation.\"\n    ],\n    \"key_evidence\": [\n      \"Kitchen temperature sensor recovered valid readings ('2295') at 18:55:00, just 4 minutes after the data loss event.\",\n      \"All other room sensors operated normally throughout the entire 6-hour period, ruling out systemic network failures.\",\n      \"The dishwasher activated at 19:36:00, confirming continued normal kitchen usage without incident.\"\n    ],\n    \"recommended_actions\": [\n      \"Monitor the kitchen window contact for consistent closing events during future cooking activities.\",\n      \"Check physical connections of the kitchen temperature sensor if intermittent gaps persist in future logs.\"\n    ]\n}", "model_response": {"is_anomaly": false, "confidence": "high", "threat_type": "none", "threat_description": "No safety threats detected; the initial sensor data gap was a transient error that resolved shortly after normal household activity resumed.", "reasoning": ["Step 1: Analyzed the temporal sequence in C01 showing cooktop off (18:50), window open (18:50:30), and kitchen temp sensor reporting 'None' (18:51).", "Step 2: Verified subsequent chunks (C01-C03) which show the kitchen_temp_sensor resuming valid temperature readings at 18:55:00 and remaining stable through the end of the log.", "Step 3: Confirmed that no other safety indicators (e.g., prolonged high heat, unauthorized access, or persistent sensor failure) were present, attributing the brief outage to a transient glitch during routine ventilation."], "key_evidence": ["Kitchen temperature sensor recovered valid readings ('2295') at 18:55:00, just 4 minutes after the data loss event.", "All other room sensors operated normally throughout the entire 6-hour period, ruling out systemic network failures.", "The dishwasher activated at 19:36:00, confirming continued normal kitchen usage without incident."], "recommended_actions": ["Monitor the kitchen window contact for consistent closing events during future cooking activities.", "Check physical connections of the kitchen temperature sensor if intermittent gaps persist in future logs."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "CORRECT_REJECT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 58.44558572769165, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 548, "chunk_count": 7, "signals": {"room_activity": {"living_room": 147, "master_bedroom": 148, "second_bedroom": 85, "kitchen": 81, "entrance": 75, "bathroom": 12}, "attribute_frequency": {"MeasuredValue": 294, "Occupancy": 241, "OnOff": 7, "StateValue": 2, "OperationalState": 1, "CurrentPositionLiftPercent100ths": 1, "LockState": 1}, "lock_state_flips": 1, "occupancy_events": 241, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"device-health | single-event-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_cook_surface\", \"kitchen_window_contact\", \"kitchen_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C01\"],\n  \"suspected_patterns\": [\n    \"Cooking surface turned off while temperature data is still being reported, suggesting potential end-of-use state.\",\n    \"Kitchen window sensor reported 'False' (open) at the same timestamp the cooktop was turned off, which may indicate an open window during cooking or a sensor fault.\",\n    \"Temperature sensor in kitchen reported 'None' immediately after reporting a value, indicating a potential hardware disconnection or communication failure.\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C01 contains the specific deterministic signals regarding the cooktop state change ('OnOff.OnOff = False'), the window contact state ('BooleanState.StateValue = False'), and the critical telemetry loss ('MeasuredValue = None'). These events form a unique anomaly cluster not present in other chunks where sensors continue to report valid values consistently.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "device-health | single-event-safety", "focus_rooms": ["kitchen"], "focus_devices": ["kitchen_cook_surface", "kitchen_window_contact", "kitchen_temp_sensor"], "focus_chunk_ids": ["C01"], "suspected_patterns": ["Cooking surface turned off while temperature data is still being reported, suggesting potential end-of-use state.", "Kitchen window sensor reported 'False' (open) at the same timestamp the cooktop was turned off, which may indicate an open window during cooking or a sensor fault.", "Temperature sensor in kitchen reported 'None' immediately after reporting a value, indicating a potential hardware disconnection or communication failure."], "why_these_chunks": ["Chunk C01 contains the specific deterministic signals regarding the cooktop state change ('OnOff.OnOff = False'), the window contact state ('BooleanState.StateValue = False'), and the critical telemetry loss ('MeasuredValue = None'). These events form a unique anomaly cluster not present in other chunks where sensors continue to report valid values consistently."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Routine household activity where cooking was completed, sensors briefly glitched due to power fluctuation or network packet loss, and the kitchen window was opened for ventilation before being closed.\",\n      \"evidence\": [\n        \"Cook surface turned off at 18:50:00 indicating end of use.\",\n        \"Window sensor reported 'False' (open) shortly after cooking stopped, consistent with ventilation habits.\",\n        \"Temperature sensor recovered valid readings ('2295') 3 minutes later, suggesting a transient error rather than permanent failure.\",\n        \"Dishwasher activated at 19:36:00, indicating continued normal kitchen usage.\"\n      ],\n      \"weaknesses\": [\n        \"The gap between the open window state and subsequent data is short, but no explicit 'closed' event is logged immediately after.\",\n        \"Other rooms show perfectly stable temperature telemetry during the same period, making an isolated kitchen sensor fault less likely than a systemic issue affecting only the kitchen zone.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Potential safety hazard involving an unmonitored fire risk; the cooktop was turned off while the window remained open (or failed to close), and the primary temperature sensor lost connectivity exactly when it should have been monitoring for post-cooling hazards.\",\n      \"threat_type\": \"Fire_Safety_Monitoring_Gap\",\n      \"evidence\": [\n        \"At 18:50:00, cook surface turned OFF.\",\n        \"At 18:50:30, kitchen window contact reported OPEN (False).\",\n        \"At 18:51:00, kitchen temp sensor reported 'None' (data loss) despite other room sensors reporting normally, creating a blind spot for ~4.5 hours until the log ends or resets.\",\n        \"No confirmation of window closing or cooktop re-activation in the log between 18:51:00 and 19:36:00.\"\n      ],\n      \"weaknesses\": [\n        \"The temperature value before failure (2301) is within normal ambient range, reducing immediate overheating probability.\",\n        \"The dishwasher activation at 19:36 suggests someone entered the kitchen, which might have triggered the sensor recovery or manually verified conditions.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Hardware malfunction or tampering where the kitchen temperature sensor has physically disconnected or been bypassed, rendering the system blind to thermal anomalies in the kitchen specifically.\",\n      \"threat_type\": \"Sensor_Failure/Interference\",\n      \"evidence\": [\n        \"Sudden transition from 'MeasuredValue = 2301' to 'MeasuredValue = None' at 18:51:00.\",\n        \"Consistent absence of any new temperature measurements from the kitchen_temp_sensor for the remainder of the chunk (over 45 minutes of logs).\",\n        \"Contrast with living_room, master_bedroom, and second_bedroom sensors continuing to report values every 5 minutes without interruption.\"\n      ],\n      \"weaknesses\": [\n        \"Could be a legitimate temporary network dropout that resolved just outside the observed window or upon human interaction at 19:36.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The precise temporal sequence: Cook Off (18:50:00) -> Window Open (18:50:30) -> Temp Sensor Data Loss (18:51:00). This clustering of events points to a specific incident at the moment of cooking cessation.\",\n    \"The isolation of the anomaly: Only the kitchen_temp_sensor fails; all other sensors in the house operate normally, ruling out a general router outage or power cut.\"\n  ],\n  \"missing_information\": [\n    \"Did the window sensor ever report a return to 'True' (closed) state?\",\n    \"Was there any manual override or status update regarding the kitchen temperature sensor between 18:51:00 and 19:36:00?\",\n    \"What is the historical reliability of the kitchen_temp_sensor compared to others?\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Routine household activity where cooking was completed, sensors briefly glitched due to power fluctuation or network packet loss, and the kitchen window was opened for ventilation before being closed.", "evidence": ["Cook surface turned off at 18:50:00 indicating end of use.", "Window sensor reported 'False' (open) shortly after cooking stopped, consistent with ventilation habits.", "Temperature sensor recovered valid readings ('2295') 3 minutes later, suggesting a transient error rather than permanent failure.", "Dishwasher activated at 19:36:00, indicating continued normal kitchen usage."], "weaknesses": ["The gap between the open window state and subsequent data is short, but no explicit 'closed' event is logged immediately after.", "Other rooms show perfectly stable temperature telemetry during the same period, making an isolated kitchen sensor fault less likely than a systemic issue affecting only the kitchen zone."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Potential safety hazard involving an unmonitored fire risk; the cooktop was turned off while the window remained open (or failed to close), and the primary temperature sensor lost connectivity exactly when it should have been monitoring for post-cooling hazards.", "threat_type": "Fire_Safety_Monitoring_Gap", "evidence": ["At 18:50:00, cook surface turned OFF.", "At 18:50:30, kitchen window contact reported OPEN (False).", "At 18:51:00, kitchen temp sensor reported 'None' (data loss) despite other room sensors reporting normally, creating a blind spot for ~4.5 hours until the log ends or resets.", "No confirmation of window closing or cooktop re-activation in the log between 18:51:00 and 19:36:00."], "weaknesses": ["The temperature value before failure (2301) is within normal ambient range, reducing immediate overheating probability.", "The dishwasher activation at 19:36 suggests someone entered the kitchen, which might have triggered the sensor recovery or manually verified conditions."]}, {"id": "A2", "description": "Hardware malfunction or tampering where the kitchen temperature sensor has physically disconnected or been bypassed, rendering the system blind to thermal anomalies in the kitchen specifically.", "threat_type": "Sensor_Failure/Interference", "evidence": ["Sudden transition from 'MeasuredValue = 2301' to 'MeasuredValue = None' at 18:51:00.", "Consistent absence of any new temperature measurements from the kitchen_temp_sensor for the remainder of the chunk (over 45 minutes of logs).", "Contrast with living_room, master_bedroom, and second_bedroom sensors continuing to report values every 5 minutes without interruption."], "weaknesses": ["Could be a legitimate temporary network dropout that resolved just outside the observed window or upon human interaction at 19:36."]}], "most_discriminative_evidence": ["The precise temporal sequence: Cook Off (18:50:00) -> Window Open (18:50:30) -> Temp Sensor Data Loss (18:51:00). This clustering of events points to a specific incident at the moment of cooking cessation.", "The isolation of the anomaly: Only the kitchen_temp_sensor fails; all other sensors in the house operate normally, ruling out a general router outage or power cut."], "missing_information": ["Did the window sensor ever report a return to 'True' (closed) state?", "Was there any manual override or status update regarding the kitchen temperature sensor between 18:51:00 and 19:36:00?", "What is the historical reliability of the kitchen_temp_sensor compared to others?"]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C02\", \"C03\"],\n  \"missing_checks\": [\n    \"Verify if the kitchen window sensor returned to 'True' (closed) state after the initial 'False' report.\",\n    \"Check for any manual status updates or reconnection events for the kitchen_temp_sensor between 18:51 and 19:36.\",\n    \"Confirm the operational history of the kitchen_temp_sensor to distinguish between a one-time glitch and chronic failure.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identified the temporal clustering of events in C01 but stopped too early. To validate the 'Fire_Safety_Monitoring_Gap' hypothesis, we need to confirm the duration of the data loss by reviewing subsequent chunks (C02, C03) to see when/if the sensor recovered or if it remained offline until the dishwasher event at 19:36. The current evidence leaves ambiguity on whether the sensor was permanently disconnected during this period or if the log simply cut off before recovery.\",\n    \"The hypothesis regarding the window sensor closing is unverified; checking later logs is essential to rule out an open window scenario where ventilation was left active, which contradicts the safety assessment.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C02", "C03"], "missing_checks": ["Verify if the kitchen window sensor returned to 'True' (closed) state after the initial 'False' report.", "Check for any manual status updates or reconnection events for the kitchen_temp_sensor between 18:51 and 19:36.", "Confirm the operational history of the kitchen_temp_sensor to distinguish between a one-time glitch and chronic failure."], "supervisor_notes": ["The analysis correctly identified the temporal clustering of events in C01 but stopped too early. To validate the 'Fire_Safety_Monitoring_Gap' hypothesis, we need to confirm the duration of the data loss by reviewing subsequent chunks (C02, C03) to see when/if the sensor recovered or if it remained offline until the dishwasher event at 19:36. The current evidence leaves ambiguity on whether the sensor was permanently disconnected during this period or if the log simply cut off before recovery.", "The hypothesis regarding the window sensor closing is unverified; checking later logs is essential to rule out an open window scenario where ventilation was left active, which contradicts the safety assessment."]}, "preview_triage_prompt": "## Query\n以下是过去 6 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 147,\n    \"master_bedroom\": 148,\n    \"second_bedroom\": 85,\n    \"kitchen\": 81,\n    \"entrance\": 75,\n    \"bathroom\": 12\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 294,\n    \"Occupancy\": 241,\n    \"OnOff\": 7,\n    \"StateValue\": 2,\n    \"OperationalState\": 1,\n    \"CurrentPositionLiftPercent100ths\": 1,\n    \"LockState\": 1\n  },\n  \"lock_state_flips\": 1,\n  \"occupancy_events\": 241,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-10T17:55:00\",\n    \"end_ts\": \"2026-06-10T18:45:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 21,\n      \"master_bedroom\": 21,\n      \"second_bedroom\": 13,\n      \"kitchen\": 13,\n      \"entrance\": 10,\n      \"bathroom\": 2\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"entrance_occupancy\"\n    ],\n    \"alarmish_count\": 34,\n    \"preview_lines\": [\n      \"[2026-06-10T17:55:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2328\",\n      \"[2026-06-10T17:55:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2319\",\n      \"[2026-06-10T17:55:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2335\",\n      \"[2026-06-10T17:55:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2338\",\n      \"[2026-06-10T17:56:03] living_room_occupancy | OccupancySe", "preview_verifier_prompt": "## Query\n以下是过去 6 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Triage\n{\n  \"latent_task_profile\": \"device-health | single-event-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_cook_surface\", \"kitchen_window_contact\", \"kitchen_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C01\"],\n  \"suspected_patterns\": [\n    \"Cooking surface turned off while temperature data is still being reported, suggesting potential end-of-use state.\",\n    \"Kitchen window sensor reported 'False' (open) at the same timestamp the cooktop was turned off, which may indicate an open window during cooking or a sensor fault.\",\n    \"Temperature sensor in kitchen reported 'None' immediately after reporting a value, indicating a potential hardware disconnection or communication failure.\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C01 contains the specific deterministic signals regarding the cooktop state change ('OnOff.OnOff = False'), the window contact state ('BooleanState.StateValue = False'), and the critical telemetry loss ('MeasuredValue = None'). These events form a unique anomaly cluster not present in other chunks where sensors continue to report valid values consistently.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Routine household activity where cooking was completed, sensors briefly glitched due to power fluctuation or network packet loss, and the kitchen window was opened for ventilation before being closed.\",\n      \"evidence\": [\n        \"Cook surface turned off at 18:50:00 indicating end of use.\",\n        \"Window sensor reported 'False' (open) shortly after cooking stopped, consistent with ventilation habits.\",\n        \"Temperature sensor recovered valid readings ('2295') 3 minutes later, suggesting a transient error rather than permanent failure.\",\n        \"Dishwasher activated at 19:36:00, indicating continued normal kitchen usage.\"\n      ],\n      \"weaknesses\": [\n        \"The gap between the open window state and subsequent data is short, but no explicit 'closed' event is logged immediately after.\",\n        \"Other rooms show perfectly stable temperature telemetry during the same period, making an isolated kitchen sensor fault less likely than a systemic issue affecting only the kitchen zone.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Potential safety hazard involving an unmonitored fire risk; the cooktop was turned off while the window remained open (or failed to close), and the p"}}
{"episode_id": "SQ3_FP_B_0575", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq3\\SQ3_FP_B_0575.json", "metadata": {"sq_type": "SQ3", "sq_name": "行为序列分析", "variant": "FP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "family_with_children", "base_date": "2026-06-01T00:00:00", "seed": 20261204, "scenario_id": "BA-03", "total_events": 1840, "anomaly_events_count": 5}, "ground_truth": {"scenario_id": "BA-03-FP", "scenario_name": "BA-03-FP: 小孩玩开关", "category": "behavioral_anomaly", "is_anomaly": false, "threat_type": "none", "key_difference": "只在儿童房一个房间内发生，kids_room_occupancy=1，有小孩在场", "difficulty_score": 10, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 3, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "balcony", "injection_time": "2026-06-01T21:00:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"intrusion\",\n  \"threat_description\": \"Evidence indicates a potential unauthorized entry via the front door while the resident remained asleep in the master bedroom.\",\n  \"reasoning\": [\n    \"The log shows a critical event at 16:07:00 where a manual lock operation (Type=1) was followed immediately by the door state changing to '2' and contact becoming 'False', indicating the door was opened or breached from the outside.\",\n    \"During this specific breach window (16:07), the master bedroom occupancy sensor continued to read '1', suggesting the primary resident was unaware of the intrusion and likely sleeping.\",\n    \"While temperature readings show values in the thousands (e.g., 2533), these are consistent across all rooms and appear to be raw integer encoding errors (likely millikelvin or scaled units) rather than physical sensor failure, as the trend shows a steady decline correlating with time, which is physically impossible for standard sensors to fluctuate wildly without an environmental cause like infiltration.\",\n    \"The high-frequency entrance occupancy events (~every 4 minutes) combined with zero activity in adjacent living areas create a disjointed pattern inconsistent with normal household circulation, further supporting the theory of an intruder lingering near the threshold.\"\n  ],\n  \"key_evidence\": [\n    \"Timestamp 16:07:00 sequence: LockOperation(LockOperationType=1) -> DoorLock.LockState = 2 -> front_door_contact = False.\",\n    \"Master bedroom occupancy remained 1 throughout the 16:07 incident, implying the resident was incapacitated or asleep.\",\n    \"Consistent pattern of entrance occupancy triggers every ~4 minutes despite no corresponding activity in common areas.\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately dispatch security personnel or law enforcement to verify occupancy and secure the premises.\",\n    \"Check physical locks and door mechanisms for signs of forced entry or tampering.\",\n    \"Review camera footage from the entrance/hallway if available to identify any persons present during the lock flip event.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "intrusion", "threat_description": "Evidence indicates a potential unauthorized entry via the front door while the resident remained asleep in the master bedroom.", "reasoning": ["The log shows a critical event at 16:07:00 where a manual lock operation (Type=1) was followed immediately by the door state changing to '2' and contact becoming 'False', indicating the door was opened or breached from the outside.", "During this specific breach window (16:07), the master bedroom occupancy sensor continued to read '1', suggesting the primary resident was unaware of the intrusion and likely sleeping.", "While temperature readings show values in the thousands (e.g., 2533), these are consistent across all rooms and appear to be raw integer encoding errors (likely millikelvin or scaled units) rather than physical sensor failure, as the trend shows a steady decline correlating with time, which is physically impossible for standard sensors to fluctuate wildly without an environmental cause like infiltration.", "The high-frequency entrance occupancy events (~every 4 minutes) combined with zero activity in adjacent living areas create a disjointed pattern inconsistent with normal household circulation, further supporting the theory of an intruder lingering near the threshold."], "key_evidence": ["Timestamp 16:07:00 sequence: LockOperation(LockOperationType=1) -> DoorLock.LockState = 2 -> front_door_contact = False.", "Master bedroom occupancy remained 1 throughout the 16:07 incident, implying the resident was incapacitated or asleep.", "Consistent pattern of entrance occupancy triggers every ~4 minutes despite no corresponding activity in common areas."], "recommended_actions": ["Immediately dispatch security personnel or law enforcement to verify occupancy and secure the premises.", "Check physical locks and door mechanisms for signs of forced entry or tampering.", "Review camera footage from the entrance/hallway if available to identify any persons present during the lock flip event."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 64.32213282585144, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1032, "chunk_count": 13, "signals": {"room_activity": {"living_room": 240, "master_bedroom": 292, "second_bedroom": 169, "kitchen": 153, "entrance": 154, "bathroom": 24}, "attribute_frequency": {"MeasuredValue": 582, "Occupancy": 424, "OnOff": 13, "StateValue": 4, "LockState": 3, "SystemMode": 1, "OperationalState": 1, "CurrentPositionLiftPercent100ths": 1}, "lock_state_flips": 3, "occupancy_events": 424, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"behavior-sequence | composite-safety\",\n  \"focus_rooms\": [\"master_bedroom\", \"entrance\", \"living_room\", \"second_bedroom\"],\n  \"focus_devices\": [\"master_bedroom_occupancy\", \"entrance_occupancy\", \"living_room_occupancy\", \"front_door_lock\", \"temperature_sensor\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\", \"C05\", \"C06\", \"C07\", \"C08\", \"C09\", \"C10\", \"C11\", \"C12\"],\n  \"suspected_patterns\": [\n    \"High-frequency occupancy toggling in bedrooms vs consistent low activity elsewhere\",\n    \"Correlation between door lock state flips and high alarm counts\",\n    \"Gradual temperature drop across all rooms without HVAC intervention signals\",\n    \"Potential 'ghost occupancy' or sensor drift given constant occupancy=1 readings despite low event counts in other rooms\"\n  ],\n  \"why_these_chunks\": [\n    \"All chunks (C00-C12) are required to establish the full temporal sequence of the suspected anomaly, specifically tracking the consistency of occupancy sensors over time.\",\n    \"Chunks C00-C06 show the initial baseline and the onset of irregular temperature drops and occupancy patterns.\",\n    \"Chunk C11 is critical for cross-referencing the final door lock state flip against the preceding occupancy data to determine if it was a user action or an anomaly trigger.\",\n    \"The uniform presence of temperature sensors in every chunk allows for a system-wide thermal trend analysis.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "behavior-sequence | composite-safety", "focus_rooms": ["master_bedroom", "entrance", "living_room", "second_bedroom"], "focus_devices": ["master_bedroom_occupancy", "entrance_occupancy", "living_room_occupancy", "front_door_lock", "temperature_sensor"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04", "C05", "C06", "C07", "C08", "C09", "C10", "C11", "C12"], "suspected_patterns": ["High-frequency occupancy toggling in bedrooms vs consistent low activity elsewhere", "Correlation between door lock state flips and high alarm counts", "Gradual temperature drop across all rooms without HVAC intervention signals", "Potential 'ghost occupancy' or sensor drift given constant occupancy=1 readings despite low event counts in other rooms"], "why_these_chunks": ["All chunks (C00-C12) are required to establish the full temporal sequence of the suspected anomaly, specifically tracking the consistency of occupancy sensors over time.", "Chunks C00-C06 show the initial baseline and the onset of irregular temperature drops and occupancy patterns.", "Chunk C11 is critical for cross-referencing the final door lock state flip against the preceding occupancy data to determine if it was a user action or an anomaly trigger.", "The uniform presence of temperature sensors in every chunk allows for a system-wide thermal trend analysis."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Resident is home, sleeping in the master bedroom, with intermittent trips to the entrance (likely checking mail or retrieving items) and no one in common areas.\",\n      \"evidence\": [\"Master bedroom occupancy consistently reads 1 throughout all chunks.\", \"Entrance occupancy reads 1 at regular intervals (~4 minutes).\", \"Living room, second bedroom, bathroom occupancy are consistently 0.\", \"Temperature readings show natural diurnal cooling trends without HVAC intervention signals.\"],\n      \"weaknesses\": [\"The frequency of entrance 'occupancy' events is high for a sleeping resident but could be explained by routine checks.\", \"No activity in living room or kitchen contradicts typical evening routines, but this can happen during sleep hours.\"]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"System sensor drift causing false positive temperature fluctuations and erratic occupancy toggling.\",\n      \"evidence\": [\"Temperature values fluctuate irregularly between sensors (e.g., Kitchen jumps from 2387 to 2403).\", \"Occupancy sensors toggle between 0 and 1 rapidly in some logs, which may indicate calibration issues rather than human movement.\"],\n      \"weaknesses\": [\"Drift typically causes gradual deviation, not synchronized drops across multiple rooms unless there is a shared environmental factor like a power surge affecting sensors.\", \"The correlation between lock flips and specific time points suggests intentional action rather than random noise.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Undetected intruder entering via the front door while the primary resident sleeps in the master bedroom.\",\n      \"threat_type\": \"Burglary / Unauthorized Entry\",\n      \"evidence\": [\"At 16:07, a manual lock operation occurred immediately followed by a contact state change (False), indicating the door was opened from the outside or manipulated.\", \"Despite the door being open/manipulated, the master bedroom occupancy remained 1 (resident unaware).\", \"High-frequency 'entrance_occupancy = 1' events occur regularly even when the door lock state is stable, suggesting an entity moving in/out or lingering near the threshold without triggering other alarms.\", \"Temperature patterns show a consistent drop across all rooms, possibly due to external air infiltration through an unlocked/forced entry point.\"],\n      \"weaknesses\": [\"The system did not trigger an alarm on the single lock flip, potentially due to a delayed response or configuration setting.\", \"It is possible the resident left the house briefly and returned, though the sustained master bedroom occupancy makes this less likely.\"]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Sensor failure leading to 'ghost occupancy' where the entrance sensor falsely reports presence despite no human traffic matching the volume expected for that frequency.\",\n      \"threat_type\": \"System Malfunction / Data Integrity\",\n      \"evidence\": [\"Entrance occupancy triggers every ~4 minutes regardless of visible context.\", \"Other rooms (Living, Second Bed, Bath) remain empty (0), creating a disjointed spatial picture.\", \"Temperature anomalies (fluctuating values) suggest sensor instability.\"],\n      \"weaknesses\": [\"This hypothesis does not explain the specific timestamp of the manual lock operation at 16:07, which implies a physical interaction beyond simple sensor error.\", \"The total event counts in structured signals (424 occupancy vs 13 OnOff) suggest real activity, not just static drift.\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The sequence at 16:07 showing 'LockOperation(LockOperationType=1)' followed immediately by 'DoorLock.LockState = 2' and 'front_door_contact = False' indicates an unauthorized opening event.\",\n    \"The simultaneous maintenance of 'master_bedroom_occupancy = 1' during the door breach event suggests the resident was asleep or incapacitated and unaware of the intrusion.\",\n    \"The high frequency of entrance occupancy events (every ~4 mins) combined with zero activity in adjacent living spaces creates a pattern inconsistent with normal household circulation.\"\n  ],\n  \"missing_information\": [\n    \"Camera footage or video feed from the entrance/hallway to confirm if anyone was present at the door during the lock flip.\",\n    \"Log data for the HVAC system to verify if the temperature drop was caused by system failure or external infiltration.\",\n    \"History of previous lock state changes to determine if the 16:07 event was anomalous compared to baseline user behavior.\",\n    \"Signal strength or battery level logs for the entrance sensor to rule out communication errors causing false positives.\"]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Resident is home, sleeping in the master bedroom, with intermittent trips to the entrance (likely checking mail or retrieving items) and no one in common areas.", "evidence": ["Master bedroom occupancy consistently reads 1 throughout all chunks.", "Entrance occupancy reads 1 at regular intervals (~4 minutes).", "Living room, second bedroom, bathroom occupancy are consistently 0.", "Temperature readings show natural diurnal cooling trends without HVAC intervention signals."], "weaknesses": ["The frequency of entrance 'occupancy' events is high for a sleeping resident but could be explained by routine checks.", "No activity in living room or kitchen contradicts typical evening routines, but this can happen during sleep hours."]}, {"id": "N2", "description": "System sensor drift causing false positive temperature fluctuations and erratic occupancy toggling.", "evidence": ["Temperature values fluctuate irregularly between sensors (e.g., Kitchen jumps from 2387 to 2403).", "Occupancy sensors toggle between 0 and 1 rapidly in some logs, which may indicate calibration issues rather than human movement."], "weaknesses": ["Drift typically causes gradual deviation, not synchronized drops across multiple rooms unless there is a shared environmental factor like a power surge affecting sensors.", "The correlation between lock flips and specific time points suggests intentional action rather than random noise."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Undetected intruder entering via the front door while the primary resident sleeps in the master bedroom.", "threat_type": "Burglary / Unauthorized Entry", "evidence": ["At 16:07, a manual lock operation occurred immediately followed by a contact state change (False), indicating the door was opened from the outside or manipulated.", "Despite the door being open/manipulated, the master bedroom occupancy remained 1 (resident unaware).", "High-frequency 'entrance_occupancy = 1' events occur regularly even when the door lock state is stable, suggesting an entity moving in/out or lingering near the threshold without triggering other alarms.", "Temperature patterns show a consistent drop across all rooms, possibly due to external air infiltration through an unlocked/forced entry point."], "weaknesses": ["The system did not trigger an alarm on the single lock flip, potentially due to a delayed response or configuration setting.", "It is possible the resident left the house briefly and returned, though the sustained master bedroom occupancy makes this less likely."]}, {"id": "A2", "description": "Sensor failure leading to 'ghost occupancy' where the entrance sensor falsely reports presence despite no human traffic matching the volume expected for that frequency.", "threat_type": "System Malfunction / Data Integrity", "evidence": ["Entrance occupancy triggers every ~4 minutes regardless of visible context.", "Other rooms (Living, Second Bed, Bath) remain empty (0), creating a disjointed spatial picture.", "Temperature anomalies (fluctuating values) suggest sensor instability."], "weaknesses": ["This hypothesis does not explain the specific timestamp of the manual lock operation at 16:07, which implies a physical interaction beyond simple sensor error.", "The total event counts in structured signals (424 occupancy vs 13 OnOff) suggest real activity, not just static drift."]}], "most_discriminative_evidence": ["The sequence at 16:07 showing 'LockOperation(LockOperationType=1)' followed immediately by 'DoorLock.LockState = 2' and 'front_door_contact = False' indicates an unauthorized opening event.", "The simultaneous maintenance of 'master_bedroom_occupancy = 1' during the door breach event suggests the resident was asleep or incapacitated and unaware of the intrusion.", "The high frequency of entrance occupancy events (every ~4 mins) combined with zero activity in adjacent living spaces creates a pattern inconsistent with normal household circulation."], "missing_information": ["Camera footage or video feed from the entrance/hallway to confirm if anyone was present at the door during the lock flip.", "Log data for the HVAC system to verify if the temperature drop was caused by system failure or external infiltration.", "History of previous lock state changes to determine if the 16:07 event was anomalous compared to baseline user behavior.", "Signal strength or battery level logs for the entrance sensor to rule out communication errors causing false positives."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [],\n  \"missing_checks\": [\n    \"Verify the 'Temperature anomalies (fluctuating values)' mentioned in Hypothesis N2. The Triage output references temperature data to support sensor drift hypotheses, but the Investigator Output cites specific impossible values (e.g., 2387) that contradict standard Celsius readings unless it's a raw integer signal error. We need to confirm if this is a data parsing error or actual sensor failure.\",\n    \"Cross-reference the 'manual lock operation' at 16:07 with the 'History of previous lock state changes'. The Investigator notes this as a key discriminative point but lacks historical context to determine if this was an anomaly or routine behavior. This requires access to logs outside the current 12-hour window or a longer baseline within the available chunks if they contain prior history.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis is highly on-topic and logically structured, effectively identifying two competing hypotheses (Intrusion vs. Sensor Failure).\",\n    \"However, the evidence regarding temperature is suspiciously specific yet potentially flawed ('2387 degrees'). If the provided chunks contain raw data showing these numbers, we must verify if this indicates a system parsing bug rather than physical reality before concluding 'sensor instability'.\",\n    \"The conclusion about the 'unauthorized opening' relies heavily on the interpretation of the 16:07 event without historical baseline data included in the current chunk set. While the logic holds for the immediate timeframe, claiming 'anomaly' strictly requires knowing what normal looks like for *this* user over time.\",\n    \"No additional chunks are needed from the existing list (C00-C12) as they cover the full 12-hour sequence required to establish the trend and the specific incident. The insufficiency lies in the *type* of external checks needed (historical baselines, HVAC logs), not missing time windows.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": [], "missing_checks": ["Verify the 'Temperature anomalies (fluctuating values)' mentioned in Hypothesis N2. The Triage output references temperature data to support sensor drift hypotheses, but the Investigator Output cites specific impossible values (e.g., 2387) that contradict standard Celsius readings unless it's a raw integer signal error. We need to confirm if this is a data parsing error or actual sensor failure.", "Cross-reference the 'manual lock operation' at 16:07 with the 'History of previous lock state changes'. The Investigator notes this as a key discriminative point but lacks historical context to determine if this was an anomaly or routine behavior. This requires access to logs outside the current 12-hour window or a longer baseline within the available chunks if they contain prior history."], "supervisor_notes": ["The analysis is highly on-topic and logically structured, effectively identifying two competing hypotheses (Intrusion vs. Sensor Failure).", "However, the evidence regarding temperature is suspiciously specific yet potentially flawed ('2387 degrees'). If the provided chunks contain raw data showing these numbers, we must verify if this indicates a system parsing bug rather than physical reality before concluding 'sensor instability'.", "The conclusion about the 'unauthorized opening' relies heavily on the interpretation of the 16:07 event without historical baseline data included in the current chunk set. While the logic holds for the immediate timeframe, claiming 'anomaly' strictly requires knowing what normal looks like for *this* user over time.", "No additional chunks are needed from the existing list (C00-C12) as they cover the full 12-hour sequence required to establish the trend and the specific incident. The insufficiency lies in the *type* of external checks needed (historical baselines, HVAC logs), not missing time windows."]}, "preview_triage_prompt": "## Query\n以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 240,\n    \"master_bedroom\": 292,\n    \"second_bedroom\": 169,\n    \"kitchen\": 153,\n    \"entrance\": 154,\n    \"bathroom\": 24\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 582,\n    \"Occupancy\": 424,\n    \"OnOff\": 13,\n    \"StateValue\": 4,\n    \"LockState\": 3,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"CurrentPositionLiftPercent100ths\": 1\n  },\n  \"lock_state_flips\": 3,\n  \"occupancy_events\": 424,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-01T11:55:00\",\n    \"end_ts\": \"2026-06-01T12:55:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 15,\n      \"master_bedroom\": 25,\n      \"second_bedroom\": 14,\n      \"kitchen\": 12,\n      \"entrance\": 12,\n      \"bathroom\": 2\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"master_bedroom_occupancy\",\n      \"entrance_occupancy\"\n    ],\n    \"alarmish_count\": 30,\n    \"preview_lines\": [\n      \"[2026-06-01T11:55:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2533\",\n      \"[2026-06-01T11:55:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2521\",\n      \"[2026-06-01T11:55:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2539\",\n      \"[2026-06-01T11:55:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2528\",\n      \"[2026-06-01T11:56:00] master", "preview_verifier_prompt": "## Query\n以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Triage\n{\n  \"latent_task_profile\": \"behavior-sequence | composite-safety\",\n  \"focus_rooms\": [\"master_bedroom\", \"entrance\", \"living_room\", \"second_bedroom\"],\n  \"focus_devices\": [\"master_bedroom_occupancy\", \"entrance_occupancy\", \"living_room_occupancy\", \"front_door_lock\", \"temperature_sensor\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\", \"C05\", \"C06\", \"C07\", \"C08\", \"C09\", \"C10\", \"C11\", \"C12\"],\n  \"suspected_patterns\": [\n    \"High-frequency occupancy toggling in bedrooms vs consistent low activity elsewhere\",\n    \"Correlation between door lock state flips and high alarm counts\",\n    \"Gradual temperature drop across all rooms without HVAC intervention signals\",\n    \"Potential 'ghost occupancy' or sensor drift given constant occupancy=1 readings despite low event counts in other rooms\"\n  ],\n  \"why_these_chunks\": [\n    \"All chunks (C00-C12) are required to establish the full temporal sequence of the suspected anomaly, specifically tracking the consistency of occupancy sensors over time.\",\n    \"Chunks C00-C06 show the initial baseline and the onset of irregular temperature drops and occupancy patterns.\",\n    \"Chunk C11 is critical for cross-referencing the final door lock state flip against the preceding occupancy data to determine if it was a user action or an anomaly trigger.\",\n    \"The uniform presence of temperature sensors in every chunk allows for a system-wide thermal trend analysis.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Resident is home, sleeping in the master bedroom, with intermittent trips to the entrance (likely checking mail or retrieving items) and no one in common areas.\",\n      \"evidence\": [\"Master bedroom occupancy consistently reads 1 throughout all chunks.\", \"Entrance occupancy reads 1 at regular intervals (~4 minutes).\", \"Living room, second bedroom, bathroom occupancy are consistently 0.\", \"Temperature readings show natural diurnal cooling trends without HVAC intervention signals.\"],\n      \"weaknesses\": [\"The frequency of entrance 'occupancy' events is high for a sleeping resident but could be explained by routine checks.\", \"No activity in living room or kitchen contradicts typical evening routines, but this can happen during sleep hours.\"]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"System sensor drift causing false positive temperature fluctuations and erratic occupancy toggling.\",\n      \"evidence\": [\"Tempera"}}
{"episode_id": "SQ3_FP_C_0592", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq3\\SQ3_FP_C_0592.json", "metadata": {"sq_type": "SQ3", "sq_name": "行为序列分析", "variant": "FP", "layout_id": "C", "layout_name": "三室两厅 (3BR)", "profile_id": "family_with_children", "base_date": "2026-06-22T00:00:00", "seed": 20261221, "scenario_id": "INS-01", "total_events": 2301, "anomaly_events_count": 5}, "ground_truth": {"scenario_id": "INS-01-FP", "scenario_name": "INS-01-FP: 住户夜间开窗通风", "category": "intrusion", "is_anomaly": false, "threat_type": "none", "key_difference": "开窗前住户先在同一房间活动并开灯，是主动行为", "difficulty_score": 9, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "living_room", "injection_time": "2026-06-22T08:43:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"The kitchen temperature sensor exhibits a pattern of data loss ('None') that correlates precisely with the activation and deactivation of high-heat cooking appliances, indicating a hardware failure or calibration drift caused by thermal stress.\",\n  \"reasoning\": [\n    \"Temporal Correlation: The sensor reported 'None' exactly at 18:47:00, which is 3 minutes after the cook surface was activated at 18:46:30, and again at 19:10:00 shortly before it was turned off, suggesting the anomaly is triggered by the appliance's operation.\",\n    \"Isolation of Failure: While the kitchen sensor failed, all other room sensors (living_room, master_bedroom, kids_room) continued to report valid temperatures during these exact timestamps, ruling out a global network outage, power failure, or malicious signal injection affecting the entire system.\",\n    \"Recurring Pattern: The issue persisted across two distinct operational cycles (start-up and shut-down phases), confirming a consistent causal link between the heat generation from the cook surface and the sensor's inability to transmit data, rather than a random glitch.\"\n  ],\n  \"key_evidence\": [\n    \"[2026-06-22T18:46:30] kitchen_cook_surface | OnOff.OnOff = True followed immediately by [2026-06-22T18:47:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = None\",\n    \"[2026-06-22T19:09:00] kitchen_cook_surface | OnOff.OnOff = False followed by [2026-06-22T19:10:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = None while other sensors remained stable\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately inspect the physical placement of the kitchen temperature sensor relative to the cook surface to ensure it is not exposed to direct radiant heat.\",\n    \"Replace or recalibrate the kitchen temperature sensor as its reliability is compromised during active cooking scenarios, posing a safety risk for fire detection or ventilation control.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "The kitchen temperature sensor exhibits a pattern of data loss ('None') that correlates precisely with the activation and deactivation of high-heat cooking appliances, indicating a hardware failure or calibration drift caused by thermal stress.", "reasoning": ["Temporal Correlation: The sensor reported 'None' exactly at 18:47:00, which is 3 minutes after the cook surface was activated at 18:46:30, and again at 19:10:00 shortly before it was turned off, suggesting the anomaly is triggered by the appliance's operation.", "Isolation of Failure: While the kitchen sensor failed, all other room sensors (living_room, master_bedroom, kids_room) continued to report valid temperatures during these exact timestamps, ruling out a global network outage, power failure, or malicious signal injection affecting the entire system.", "Recurring Pattern: The issue persisted across two distinct operational cycles (start-up and shut-down phases), confirming a consistent causal link between the heat generation from the cook surface and the sensor's inability to transmit data, rather than a random glitch."], "key_evidence": ["[2026-06-22T18:46:30] kitchen_cook_surface | OnOff.OnOff = True followed immediately by [2026-06-22T18:47:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = None", "[2026-06-22T19:09:00] kitchen_cook_surface | OnOff.OnOff = False followed by [2026-06-22T19:10:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = None while other sensors remained stable"], "recommended_actions": ["Immediately inspect the physical placement of the kitchen temperature sensor relative to the cook surface to ensure it is not exposed to direct radiant heat.", "Replace or recalibrate the kitchen temperature sensor as its reliability is compromised during active cooking scenarios, posing a safety risk for fire detection or ventilation control."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 48.86668562889099, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1322, "chunk_count": 17, "signals": {"room_activity": {"living_room": 236, "master_bedroom": 291, "kids_room": 293, "kitchen": 153, "entrance": 155, "dining_room": 146, "second_bedroom": 24, "master_bathroom": 24}, "attribute_frequency": {"Occupancy": 713, "MeasuredValue": 582, "OnOff": 13, "StateValue": 4, "LockState": 3, "CurrentPositionLiftPercent100ths": 2, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 3, "occupancy_events": 713, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"device-health | single-event-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"kitchen_cook_surface\", \"kitchen_light\"],\n  \"focus_chunk_ids\": [\"C09\"],\n  \"suspected_patterns\": [\"sensor_data_loss\", \"sequence_anomaly\"],\n  \"why_these_chunks\": [\"Chunk C09 contains a critical data anomaly where the kitchen temperature sensor reports 'None' immediately after the cook surface and light are activated, suggesting a potential sensor failure or calibration drift during active cooking, which poses a safety risk.\"]\n}", "triage_parsed": {"latent_task_profile": "device-health | single-event-safety", "focus_rooms": ["kitchen"], "focus_devices": ["kitchen_temp_sensor", "kitchen_cook_surface", "kitchen_light"], "focus_chunk_ids": ["C09"], "suspected_patterns": ["sensor_data_loss", "sequence_anomaly"], "why_these_chunks": ["Chunk C09 contains a critical data anomaly where the kitchen temperature sensor reports 'None' immediately after the cook surface and light are activated, suggesting a potential sensor failure or calibration drift during active cooking, which poses a safety risk."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Intermittent sensor communication glitch or temporary data packet loss during high network load.\",\n      \"evidence\": [\"The kitchen_temp_sensor reports 'None' at specific timestamps (18:47:00, 19:10:00) while other room sensors report valid temperatures consistently.\", \"Data recovery occurs shortly after the gaps (e.g., at 18:50:00 and 19:10:00 later in the log), suggesting a transient error rather than permanent failure.\"],\n      \"weaknesses\": [\"This hypothesis fails to account for the correlation between the data loss and active cooking events (cook surface/light activation). Normal glitches are typically random and not synchronized with user actions.\"],\n      \"threat_type\": null\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Kitchen temperature sensor hardware failure or calibration drift induced by heat stress from active cooking appliances.\",\n      \"threat_type\": \"sensor_data_loss | safety_risk\",\n      \"evidence\": [\"Temporal Correlation: The first data loss event ('None') occurs exactly 3 minutes after the cook surface is activated (18:46:30 -> 18:47:00).\", \"Recurring Pattern: A second 'None' reading appears shortly before the cook surface is turned off (19:09:00 -> 19:10:00), coinciding with the window contact opening.\", \"Contextual Relevance: Unlike other rooms which maintain continuous readings, the kitchen sensor specifically fails during periods of elevated thermal load generated by cooking equipment.\", \"Duration: The sensor remains non-responsive for short intervals (approx. 2-3 mins) despite continuous polling attempts implied by subsequent valid reads.\"],\n      \"weaknesses\": [\"Could be a software bug in the sensor driver triggered by specific voltage spikes from the induction/stove unit, though this presents the same risk as hardware failure.\"],\n      \"threat_type\": \"safety_risk\"\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Coordinated malicious interference or environmental sabotage targeting the kitchen monitoring system.\",\n      \"threat_type\": \"intrusion | tampering\",\n      \"evidence\": [\"Precise Timing: The anomalies occur at distinct moments when the environment changes state (cooking starts/stops, window opens), suggesting an external trigger linked to these events.\", \"Selective Targeting: Other critical sensors in adjacent living areas remain unaffected throughout the same time windows.\"],\n      \"weaknesses\": [\"Lacks evidence of signal injection or physical tampering logs; the pattern is more consistent with a device reacting to its environment (heat/electrical noise) than being hacked remotely.\", \"The recovery of data suggests the system isn't permanently disabled, making a sophisticated remote hack less likely than a physical component issue.\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The exact temporal alignment of 'MeasuredValue = None' with the activation of the 'kitchen_cook_surface' (18:46:30 -> 18:47:00) strongly implies a causal link between heat generation/sensor exposure and data loss.\",\n    \"The persistence of valid temperature readings in all other rooms (living_room, master_bedroom, kids_room) during the exact same timestamps rules out a global network outage or power failure.\",\n    \"The recurrence of the anomaly upon re-engagement of the cooking environment (19:09:00 -> 19:10:00) confirms the issue is tied to the operational state of the kitchen appliance, not a one-time glitch.\"\n  ],\n  \"missing_information\": [\n    \"Raw telemetry or firmware logs from the kitchen_temp_sensor to check for error codes (e.g., over-range, connection timeout, EMI detection) around the failure times.\",\n    \"Power consumption logs for the kitchen circuit to rule out brownouts causing the sensor reset.\",\n    \"Physical inspection notes regarding sensor placement relative to the cook surface and potential direct heat exposure.\"]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Intermittent sensor communication glitch or temporary data packet loss during high network load.", "evidence": ["The kitchen_temp_sensor reports 'None' at specific timestamps (18:47:00, 19:10:00) while other room sensors report valid temperatures consistently.", "Data recovery occurs shortly after the gaps (e.g., at 18:50:00 and 19:10:00 later in the log), suggesting a transient error rather than permanent failure."], "weaknesses": ["This hypothesis fails to account for the correlation between the data loss and active cooking events (cook surface/light activation). Normal glitches are typically random and not synchronized with user actions."], "threat_type": null}], "anomaly_hypotheses": [{"id": "A1", "description": "Kitchen temperature sensor hardware failure or calibration drift induced by heat stress from active cooking appliances.", "threat_type": "safety_risk", "evidence": ["Temporal Correlation: The first data loss event ('None') occurs exactly 3 minutes after the cook surface is activated (18:46:30 -> 18:47:00).", "Recurring Pattern: A second 'None' reading appears shortly before the cook surface is turned off (19:09:00 -> 19:10:00), coinciding with the window contact opening.", "Contextual Relevance: Unlike other rooms which maintain continuous readings, the kitchen sensor specifically fails during periods of elevated thermal load generated by cooking equipment.", "Duration: The sensor remains non-responsive for short intervals (approx. 2-3 mins) despite continuous polling attempts implied by subsequent valid reads."], "weaknesses": ["Could be a software bug in the sensor driver triggered by specific voltage spikes from the induction/stove unit, though this presents the same risk as hardware failure."]}, {"id": "A2", "description": "Coordinated malicious interference or environmental sabotage targeting the kitchen monitoring system.", "threat_type": "intrusion | tampering", "evidence": ["Precise Timing: The anomalies occur at distinct moments when the environment changes state (cooking starts/stops, window opens), suggesting an external trigger linked to these events.", "Selective Targeting: Other critical sensors in adjacent living areas remain unaffected throughout the same time windows."], "weaknesses": ["Lacks evidence of signal injection or physical tampering logs; the pattern is more consistent with a device reacting to its environment (heat/electrical noise) than being hacked remotely.", "The recovery of data suggests the system isn't permanently disabled, making a sophisticated remote hack less likely than a physical component issue."]}], "most_discriminative_evidence": ["The exact temporal alignment of 'MeasuredValue = None' with the activation of the 'kitchen_cook_surface' (18:46:30 -> 18:47:00) strongly implies a causal link between heat generation/sensor exposure and data loss.", "The persistence of valid temperature readings in all other rooms (living_room, master_bedroom, kids_room) during the exact same timestamps rules out a global network outage or power failure.", "The recurrence of the anomaly upon re-engagement of the cooking environment (19:09:00 -> 19:10:00) confirms the issue is tied to the operational state of the kitchen appliance, not a one-time glitch."], "missing_information": ["Raw telemetry or firmware logs from the kitchen_temp_sensor to check for error codes (e.g., over-range, connection timeout, EMI detection) around the failure times.", "Power consumption logs for the kitchen circuit to rule out brownouts causing the sensor reset.", "Physical inspection notes regarding sensor placement relative to the cook surface and potential direct heat exposure."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C08\", \"C10\"],\n  \"missing_checks\": [\n    \"Verify if the anomaly persists during other high-heat events not involving cooking (e.g., boiling water in a pot without activating the cook surface).\",\n    \"Check for simultaneous voltage drops or brownouts on the kitchen circuit breaker logs to rule out power-induced resets.\",\n    \"Review firmware error codes from the sensor specifically for 'over-range' or 'EMI' triggers rather than generic communication loss.\"\n  ],\n  \"supervisor_notes\": [\n    \"The current analysis correctly identifies the temporal correlation between cooking events and data loss but relies heavily on Chunk C09. To confirm this is a hardware failure specific to heat stress versus a network glitch triggered by appliance startup, adjacent chunks showing the state immediately before activation (C08) and immediately after deactivation/recovery (C10) are required.\",\n    \"The hypothesis of 'malicious interference' (A2) is weakly supported; more context on network traffic spikes during these exact windows (found in surrounding chunks) would strengthen or refute this before concluding it's purely environmental.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C08", "C10"], "missing_checks": ["Verify if the anomaly persists during other high-heat events not involving cooking (e.g., boiling water in a pot without activating the cook surface).", "Check for simultaneous voltage drops or brownouts on the kitchen circuit breaker logs to rule out power-induced resets.", "Review firmware error codes from the sensor specifically for 'over-range' or 'EMI' triggers rather than generic communication loss."], "supervisor_notes": ["The current analysis correctly identifies the temporal correlation between cooking events and data loss but relies heavily on Chunk C09. To confirm this is a hardware failure specific to heat stress versus a network glitch triggered by appliance startup, adjacent chunks showing the state immediately before activation (C08) and immediately after deactivation/recovery (C10) are required.", "The hypothesis of 'malicious interference' (A2) is weakly supported; more context on network traffic spikes during these exact windows (found in surrounding chunks) would strengthen or refute this before concluding it's purely environmental."]}, "preview_triage_prompt": "## Query\n以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Layout\nLayout: 三室两厅 (3BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kids_room: 儿童房温度传感器<temperature_sensor>, 儿童房灯<dimmable_light>, 儿童房窗帘<window_covering>, 儿童房窗户传感器<contact_sensor>, 儿童房运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅副灯<dimmable_light>, 客厅氛围灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘1<window_covering>, 客厅窗户传感器1<contact_sensor>, 客厅窗户传感器2<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n- master_bathroom: 主卫漏水传感器<water_leak_detector>, 主卫灯<onoff_light>, 主卫运动传感器<occupancy_sensor>\n- master_bedroom: 主卧床头灯<onoff_light>, 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>\n- second_bedroom: 次卧灯<dimmable_light>, 次卧空调<air_conditioner>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 236,\n    \"master_bedroom\": 291,\n    \"kids_room\": 293,\n    \"kitchen\": 153,\n    \"entrance\": 155,\n    \"dining_room\": 146,\n    \"second_bedroom\": 24,\n    \"master_bathroom\": 24\n  },\n  \"attribute_frequency\": {\n    \"Occupancy\": 713,\n    \"MeasuredValue\": 582,\n    \"OnOff\": 13,\n    \"StateValue\": 4,\n    \"LockState\": 3,\n    \"CurrentPositionLiftPercent100ths\": 2,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 3,\n  \"occupancy_events\": 713,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-22T11:55:00\",\n    \"end_ts\": \"2026-06-22T12:40:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 12,\n      \"master_bedroom\": 19,\n      \"kids_room\": 18,\n      \"kitchen\": 9,\n      \"entrance\": 9,\n      \"dining_room\": 9,\n      \"second_bedroom\": 2,\n      \"master_bathroom\": 2\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"kids_room_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"kids_room_occupancy\",\n      \"entrance_occupancy\"\n    ],\n    ", "preview_verifier_prompt": "## Query\n以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Triage\n{\n  \"latent_task_profile\": \"device-health | single-event-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"kitchen_cook_surface\", \"kitchen_light\"],\n  \"focus_chunk_ids\": [\"C09\"],\n  \"suspected_patterns\": [\"sensor_data_loss\", \"sequence_anomaly\"],\n  \"why_these_chunks\": [\"Chunk C09 contains a critical data anomaly where the kitchen temperature sensor reports 'None' immediately after the cook surface and light are activated, suggesting a potential sensor failure or calibration drift during active cooking, which poses a safety risk.\"]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Intermittent sensor communication glitch or temporary data packet loss during high network load.\",\n      \"evidence\": [\"The kitchen_temp_sensor reports 'None' at specific timestamps (18:47:00, 19:10:00) while other room sensors report valid temperatures consistently.\", \"Data recovery occurs shortly after the gaps (e.g., at 18:50:00 and 19:10:00 later in the log), suggesting a transient error rather than permanent failure.\"],\n      \"weaknesses\": [\"This hypothesis fails to account for the correlation between the data loss and active cooking events (cook surface/light activation). Normal glitches are typically random and not synchronized with user actions.\"],\n      \"threat_type\": null\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Kitchen temperature sensor hardware failure or calibration drift induced by heat stress from active cooking appliances.\",\n      \"threat_type\": \"sensor_data_loss | safety_risk\",\n      \"evidence\": [\"Temporal Correlation: The first data loss event ('None') occurs exactly 3 minutes after the cook surface is activated (18:46:30 -> 18:47:00).\", \"Recurring Pattern: A second 'None' reading appears shortly before the cook surface is turned off (19:09:00 -> 19:10:00), coinciding with the window contact opening.\", \"Contextual Relevance: Unlike other rooms which maintain continuous readings, the kitchen sensor specifically fails during periods of elevated thermal load generated by cooking equipment.\", \"Duration: The sensor remains non-responsive for short intervals (approx. 2-3 mins) despite continuous polling attempts implied by subsequent valid reads.\"],\n      \"weaknesses\": [\"Could be a software bug in the sensor driver triggered by specific voltage spikes from the induction/stove unit, though this pr"}}
{"episode_id": "SQ3_FP_C_0642", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq3\\SQ3_FP_C_0642.json", "metadata": {"sq_type": "SQ3", "sq_name": "行为序列分析", "variant": "FP", "layout_id": "C", "layout_name": "三室两厅 (3BR)", "profile_id": "family_with_children", "base_date": "2026-06-25T00:00:00", "seed": 20261271, "scenario_id": "BA-01", "total_events": 2300, "anomaly_events_count": 4}, "ground_truth": {"scenario_id": "BA-01-FP", "scenario_name": "BA-01-FP: 住户失眠在家走动", "category": "behavioral_anomaly", "is_anomaly": false, "threat_type": "none", "key_difference": "活动从卧室开始（住户起床），路径合理（卧室→客厅→厨房→卧室），最终回到卧室", "difficulty_score": 11, "difficulty_level": 3, "difficulty_label": "L3_composite_reasoning", "difficulty_dimensions": {"D1_evidence_count": 3, "D2_signal_directness": 2, "D3_cross_device": 3, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "kitchen", "injection_time": "2026-06-25T20:38:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"Multiple temperature sensors are reporting physically impossible values (>2500) consistent with raw ADC counts or unit conversion errors rather than actual thermal readings, indicating a firmware or configuration failure.\",\n  \"reasoning\": [\n    \"The temperature readings across all zones (Kitchen, Living Room, Bedrooms) start at ~2276 and linearly increase to >2500 over 7 hours. If these were Celsius, the house would be melting; if millidegrees, they represent ~2.5°C which is too low for a heated home but the magnitude of change (linear drift without HVAC correlation) suggests a deterministic data error rather than environmental heating.\",\n    \"The perfect synchronization of this anomaly across disparate rooms with different physical characteristics rules out local heat sources and points to a system-wide software issue or shared bus error.\",\n    \"At C06/C07, the kitchen sensor drops to 'None' while others remain high, suggesting intermittent hardware communication loss or power cycling in addition to the persistent data scaling bug.\"\n  ],\n  \"key_evidence\": [\n    \"Temperature values exceed realistic limits (e.g., 2532) while occupancy logs show normal human activity patterns starting around 06:13.\",\n    \"Values exhibit a non-stochastic, linear progression typical of raw counter overflow or incorrect multiplier application in code, not natural thermal variance.\",\n    \"Simultaneous appearance of 'None' data for one sensor while others continue reporting inflated values indicates partial hardware failure alongside the logical error.\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately reset the affected temperature sensors via the device manager or gateway interface to clear stuck states.\",\n    \"Check the device firmware version and update if an older build known to have ADC conversion bugs is installed.\",\n    \"Verify the schema definition for 'MeasuredValue' on the server side to ensure no recent configuration changes altered the unit scaling factor.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "Multiple temperature sensors are reporting physically impossible values (>2500) consistent with raw ADC counts or unit conversion errors rather than actual thermal readings, indicating a firmware or configuration failure.", "reasoning": ["The temperature readings across all zones (Kitchen, Living Room, Bedrooms) start at ~2276 and linearly increase to >2500 over 7 hours. If these were Celsius, the house would be melting; if millidegrees, they represent ~2.5°C which is too low for a heated home but the magnitude of change (linear drift without HVAC correlation) suggests a deterministic data error rather than environmental heating.", "The perfect synchronization of this anomaly across disparate rooms with different physical characteristics rules out local heat sources and points to a system-wide software issue or shared bus error.", "At C06/C07, the kitchen sensor drops to 'None' while others remain high, suggesting intermittent hardware communication loss or power cycling in addition to the persistent data scaling bug."], "key_evidence": ["Temperature values exceed realistic limits (e.g., 2532) while occupancy logs show normal human activity patterns starting around 06:13.", "Values exhibit a non-stochastic, linear progression typical of raw counter overflow or incorrect multiplier application in code, not natural thermal variance.", "Simultaneous appearance of 'None' data for one sensor while others continue reporting inflated values indicates partial hardware failure alongside the logical error."], "recommended_actions": ["Immediately reset the affected temperature sensors via the device manager or gateway interface to clear stuck states.", "Check the device firmware version and update if an older build known to have ADC conversion bugs is installed.", "Verify the schema definition for 'MeasuredValue' on the server side to ensure no recent configuration changes altered the unit scaling factor."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 58.76428437232971, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 2300, "chunk_count": 29, "signals": {"room_activity": {"living_room": 403, "master_bedroom": 518, "kids_room": 521, "kitchen": 303, "dining_room": 221, "second_bedroom": 48, "master_bathroom": 57, "entrance": 228, "second_bathroom": 1}, "attribute_frequency": {"MeasuredValue": 1156, "Occupancy": 1092, "OnOff": 26, "StateValue": 7, "LockState": 5, "CurrentPositionLiftPercent100ths": 3, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 5, "occupancy_events": 1092, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"device-health | composite-safety\",\n  \"focus_rooms\": [\n    \"kitchen\",\n    \"living_room\"\n  ],\n  \"focus_devices\": [\n    \"kitchen_temp_sensor\",\n    \"living_room_temp_sensor\",\n    \"master_bedroom_temp_sensor\",\n    \"kids_room_temp_sensor\",\n    \"kitchen_cook_surface\",\n    \"kitchen_window_contact\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C00\",\n    \"C01\",\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C06\",\n    \"C07\"\n  ],\n  \"suspected_patterns\": [\n    \"Thermal drift anomaly: Temperature sensors report values >2000 (likely millidegrees or raw ADC) instead of standard Celsius, indicating a calibration failure or sensor malfunction starting early morning.\",\n    \"Data integrity loss: Sudden appearance of 'None' in temperature readings at C06 and C07 suggests sensor disconnection or power loss.\",\n    \"Contextual conflict: Despite high occupancy counts in living/kitchen areas, temperature data remains erratic rather than stabilizing around ambient levels.\",\n    \"State transition without actuation: Kitchen cook surface turns off while window contact opens during periods of high thermal reporting.\"\n  ],\n  \"why_these_chunks\": [\n    \"C00-C05 establish the baseline pattern of inflated temperature readings (>2200 to >2500) persisting throughout the night and morning.\",\n    \"C06 is critical as it shows the first instance of 'None' data for kitchen_temp_sensor, marking the potential onset of hardware failure or communication breakdown.\",\n    \"C07 contains key contextual events (cook_surface Off, window_contact False/Open) occurring simultaneously with continued anomalous temperature reporting, suggesting the system is reacting to faulty sensor inputs rather than actual environmental changes.\",\n    \"Subsequent chunks (C08+) show stabilization of the *pattern* (consistent high numbers) but likely not resolution of the underlying sensor fault, confirming a persistent device health issue.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "device-health | composite-safety", "focus_rooms": ["kitchen", "living_room"], "focus_devices": ["kitchen_temp_sensor", "living_room_temp_sensor", "master_bedroom_temp_sensor", "kids_room_temp_sensor", "kitchen_cook_surface", "kitchen_window_contact"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04", "C05", "C06", "C07"], "suspected_patterns": ["Thermal drift anomaly: Temperature sensors report values >2000 (likely millidegrees or raw ADC) instead of standard Celsius, indicating a calibration failure or sensor malfunction starting early morning.", "Data integrity loss: Sudden appearance of 'None' in temperature readings at C06 and C07 suggests sensor disconnection or power loss.", "Contextual conflict: Despite high occupancy counts in living/kitchen areas, temperature data remains erratic rather than stabilizing around ambient levels.", "State transition without actuation: Kitchen cook surface turns off while window contact opens during periods of high thermal reporting."], "why_these_chunks": ["C00-C05 establish the baseline pattern of inflated temperature readings (>2200 to >2500) persisting throughout the night and morning.", "C06 is critical as it shows the first instance of 'None' data for kitchen_temp_sensor, marking the potential onset of hardware failure or communication breakdown.", "C07 contains key contextual events (cook_surface Off, window_contact False/Open) occurring simultaneously with continued anomalous temperature reporting, suggesting the system is reacting to faulty sensor inputs rather than actual environmental changes.", "Subsequent chunks (C08+) show stabilization of the *pattern* (consistent high numbers) but likely not resolution of the underlying sensor fault, confirming a persistent device health issue."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The temperature sensors are calibrated in millidegrees Celsius (m°C), and the house is experiencing a gradual, uniform heating trend due to external weather or internal load.\",\n      \"evidence\": [\"All sensors report values consistently increasing from ~2276 to ~2491 over time.\", \"Values across all rooms remain statistically similar within a small variance (<5 units).\"],\n      \"weaknesses\": [\"A residential environment would not reach nearly 2500 m°C (2.5°C) overnight without significant HVAC activity, yet no 'SystemMode' changes or high occupancy events correlate with this rise.\", \"The absolute baseline (~2276) is physically inconsistent with typical indoor ambient temperatures if the unit were standard Celsius; however, assuming m°C, the magnitude of change is suspiciously linear and synchronized across disparate zones without differential thermal gradients expected in real homes.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Sensor Calibration/Unit Conversion Failure: Temperature sensors are outputting raw ADC counts or millidegrees instead of normalized degrees Celsius, indicating a firmware bug or configuration drift.\",\n      \"threat_type\": \"Device Health / Data Integrity\",\n      \"evidence\": [\"Values exceed realistic physical limits for standard reporting (e.g., 2491 vs expected ~20-30). If interpreted as °C, the house is melting; if m°C, the resolution implies raw data leakage.\", \"Perfect correlation between unrelated rooms (Kitchen, Living Room, Bedrooms) suggests a shared system-level error rather than independent environmental phenomena.\", \"No corresponding logical state changes (lights off, windows closed) to justify such uniform thermal spikes.\"],\n      \"weaknesses\": [\"Cannot rule out a hypothetical scenario where the entire building was subjected to extreme industrial heat sources, though the log context (residential) makes this highly improbable.\"]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Data Pipeline Malfunction: The ingestion system is misinterpreting timestamped telemetry packets, merging multiple readings into single entries or applying an incorrect scaling factor during serialization.\",\n      \"threat_type\": \"Operational Security / Reliability\",\n      \"evidence\": [\"The 'MeasuredValue' attribute frequency is 1156, matching the number of temperature logs, suggesting the anomaly is inherent to the specific stream being analyzed.\", \"The data remains stable and 'clean' until C06/C07 where it drops to 'None', implying the sensor itself may be functional but the reporting logic failed earlier.\"],\n      \"weaknesses\": [\"Does not explain why the 'Occupancy' stream reports valid binary data while the 'Temperature' stream reports invalid scalar data simultaneously.\"],\n      \"threat_level\": \"High\"\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The simultaneous presence of extremely high temperature values (>2400) and zero occupancy in living areas (00:00 - 06:12) creates a contextual conflict; humans do not generate enough heat to raise a whole house to 2500+ units without leaving traces on occupancy counters or triggering alarms.\",\n    \"The linear progression of values (e.g., Kitchen: 2272 -> 2482) lacks the stochastic noise expected in real-world thermal sensing, pointing to a deterministic software error.\"\n  ],\n  \"missing_information\": [\n    \"The definition of the 'MeasuredValue' unit in the schema documentation.\",\n    \"Historical data from previous 24-hour cycles to establish if this is a recurring calibration event or a one-time glitch.\",\n    \"Logs from the gateway/server side to determine if the values were generated by the sensor or injected/malformed during transmission.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The temperature sensors are calibrated in millidegrees Celsius (m°C), and the house is experiencing a gradual, uniform heating trend due to external weather or internal load.", "evidence": ["All sensors report values consistently increasing from ~2276 to ~2491 over time.", "Values across all rooms remain statistically similar within a small variance (<5 units)."], "weaknesses": ["A residential environment would not reach nearly 2500 m°C (2.5°C) overnight without significant HVAC activity, yet no 'SystemMode' changes or high occupancy events correlate with this rise.", "The absolute baseline (~2276) is physically inconsistent with typical indoor ambient temperatures if the unit were standard Celsius; however, assuming m°C, the magnitude of change is suspiciously linear and synchronized across disparate zones without differential thermal gradients expected in real homes."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Sensor Calibration/Unit Conversion Failure: Temperature sensors are outputting raw ADC counts or millidegrees instead of normalized degrees Celsius, indicating a firmware bug or configuration drift.", "threat_type": "Device Health / Data Integrity", "evidence": ["Values exceed realistic physical limits for standard reporting (e.g., 2491 vs expected ~20-30). If interpreted as °C, the house is melting; if m°C, the resolution implies raw data leakage.", "Perfect correlation between unrelated rooms (Kitchen, Living Room, Bedrooms) suggests a shared system-level error rather than independent environmental phenomena.", "No corresponding logical state changes (lights off, windows closed) to justify such uniform thermal spikes."], "weaknesses": ["Cannot rule out a hypothetical scenario where the entire building was subjected to extreme industrial heat sources, though the log context (residential) makes this highly improbable."]}, {"id": "A2", "description": "Data Pipeline Malfunction: The ingestion system is misinterpreting timestamped telemetry packets, merging multiple readings into single entries or applying an incorrect scaling factor during serialization.", "threat_type": "Operational Security / Reliability", "evidence": ["The 'MeasuredValue' attribute frequency is 1156, matching the number of temperature logs, suggesting the anomaly is inherent to the specific stream being analyzed.", "The data remains stable and 'clean' until C06/C07 where it drops to 'None', implying the sensor itself may be functional but the reporting logic failed earlier."], "weaknesses": ["Does not explain why the 'Occupancy' stream reports valid binary data while the 'Temperature' stream reports invalid scalar data simultaneously."], "threat_level": "High"}], "most_discriminative_evidence": ["The simultaneous presence of extremely high temperature values (>2400) and zero occupancy in living areas (00:00 - 06:12) creates a contextual conflict; humans do not generate enough heat to raise a whole house to 2500+ units without leaving traces on occupancy counters or triggering alarms.", "The linear progression of values (e.g., Kitchen: 2272 -> 2482) lacks the stochastic noise expected in real-world thermal sensing, pointing to a deterministic software error."], "missing_information": ["The definition of the 'MeasuredValue' unit in the schema documentation.", "Historical data from previous 24-hour cycles to establish if this is a recurring calibration event or a one-time glitch.", "Logs from the gateway/server side to determine if the values were generated by the sensor or injected/malformed during transmission."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C08\", \"C12\", \"C20\"],\n  \"missing_checks\": [\n    \"Verify unit definition schema for 'MeasuredValue' across all devices.\",\n    \"Check historical data from previous cycles to distinguish recurring calibration drift from one-time glitch.\",\n    \"Cross-reference gateway/server logs to determine if values originate at the sensor or are malformed during ingestion.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identifies the anomaly (likely raw ADC counts misinterpreted as Celsius) and focuses on the relevant time window (early morning baseline).\",\n    \"However, evidence is currently insufficient because it relies heavily on chunks C00-C07. To confirm this is a persistent hardware/firmware issue rather than a transient network event, we need to inspect later chunks (e.g., C08, C12, C20) to see if the anomalous pattern stabilizes or resolves after potential reboots or maintenance windows.\",\n    \"The current hypothesis about 'Data Pipeline Malfunction' requires validation against server-side logs which cannot be inferred from the provided client-side log chunks alone; these external checks must be explicitly initiated.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C08", "C12", "C20"], "missing_checks": ["Verify unit definition schema for 'MeasuredValue' across all devices.", "Check historical data from previous cycles to distinguish recurring calibration drift from one-time glitch.", "Cross-reference gateway/server logs to determine if values originate at the sensor or are malformed during ingestion."], "supervisor_notes": ["The analysis correctly identifies the anomaly (likely raw ADC counts misinterpreted as Celsius) and focuses on the relevant time window (early morning baseline).", "However, evidence is currently insufficient because it relies heavily on chunks C00-C07. To confirm this is a persistent hardware/firmware issue rather than a transient network event, we need to inspect later chunks (e.g., C08, C12, C20) to see if the anomalous pattern stabilizes or resolves after potential reboots or maintenance windows.", "The current hypothesis about 'Data Pipeline Malfunction' requires validation against server-side logs which cannot be inferred from the provided client-side log chunks alone; these external checks must be explicitly initiated."]}, "preview_triage_prompt": "## Query\n以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Layout\nLayout: 三室两厅 (3BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kids_room: 儿童房温度传感器<temperature_sensor>, 儿童房灯<dimmable_light>, 儿童房窗帘<window_covering>, 儿童房窗户传感器<contact_sensor>, 儿童房运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅副灯<dimmable_light>, 客厅氛围灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘1<window_covering>, 客厅窗户传感器1<contact_sensor>, 客厅窗户传感器2<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n- master_bathroom: 主卫漏水传感器<water_leak_detector>, 主卫灯<onoff_light>, 主卫运动传感器<occupancy_sensor>\n- master_bedroom: 主卧床头灯<onoff_light>, 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>\n- second_bedroom: 次卧灯<dimmable_light>, 次卧空调<air_conditioner>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 403,\n    \"master_bedroom\": 518,\n    \"kids_room\": 521,\n    \"kitchen\": 303,\n    \"dining_room\": 221,\n    \"second_bedroom\": 48,\n    \"master_bathroom\": 57,\n    \"entrance\": 228,\n    \"second_bathroom\": 1\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1156,\n    \"Occupancy\": 1092,\n    \"OnOff\": 26,\n    \"StateValue\": 7,\n    \"LockState\": 5,\n    \"CurrentPositionLiftPercent100ths\": 3,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 5,\n  \"occupancy_events\": 1092,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-25T00:00:00\",\n    \"end_ts\": \"2026-06-25T01:10:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 18,\n      \"master_bedroom\": 18,\n      \"kids_room\": 18,\n      \"kitchen\": 14,\n      \"dining_room\": 3,\n      \"second_bedroom\": 3,\n      \"master_bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"kids_room_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      ", "preview_verifier_prompt": "## Query\n以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Triage\n{\n  \"latent_task_profile\": \"device-health | composite-safety\",\n  \"focus_rooms\": [\n    \"kitchen\",\n    \"living_room\"\n  ],\n  \"focus_devices\": [\n    \"kitchen_temp_sensor\",\n    \"living_room_temp_sensor\",\n    \"master_bedroom_temp_sensor\",\n    \"kids_room_temp_sensor\",\n    \"kitchen_cook_surface\",\n    \"kitchen_window_contact\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C00\",\n    \"C01\",\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C06\",\n    \"C07\"\n  ],\n  \"suspected_patterns\": [\n    \"Thermal drift anomaly: Temperature sensors report values >2000 (likely millidegrees or raw ADC) instead of standard Celsius, indicating a calibration failure or sensor malfunction starting early morning.\",\n    \"Data integrity loss: Sudden appearance of 'None' in temperature readings at C06 and C07 suggests sensor disconnection or power loss.\",\n    \"Contextual conflict: Despite high occupancy counts in living/kitchen areas, temperature data remains erratic rather than stabilizing around ambient levels.\",\n    \"State transition without actuation: Kitchen cook surface turns off while window contact opens during periods of high thermal reporting.\"\n  ],\n  \"why_these_chunks\": [\n    \"C00-C05 establish the baseline pattern of inflated temperature readings (>2200 to >2500) persisting throughout the night and morning.\",\n    \"C06 is critical as it shows the first instance of 'None' data for kitchen_temp_sensor, marking the potential onset of hardware failure or communication breakdown.\",\n    \"C07 contains key contextual events (cook_surface Off, window_contact False/Open) occurring simultaneously with continued anomalous temperature reporting, suggesting the system is reacting to faulty sensor inputs rather than actual environmental changes.\",\n    \"Subsequent chunks (C08+) show stabilization of the *pattern* (consistent high numbers) but likely not resolution of the underlying sensor fault, confirming a persistent device health issue.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The temperature sensors are calibrated in millidegrees Celsius (m°C), and the house is experiencing a gradual, uniform heating trend due to external weather or internal load.\",\n      \"evidence\": [\"All sensors report values consistently increasing from ~2276 to ~2491 over time.\", \"Values across all rooms remain statistically similar within a small variance (<5 units).\"],\n      \"weaknesses\": [\"A residential environment wou"}}
{"episode_id": "SQ3_FP_C_0614", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq3\\SQ3_FP_C_0614.json", "metadata": {"sq_type": "SQ3", "sq_name": "行为序列分析", "variant": "FP", "layout_id": "C", "layout_name": "三室两厅 (3BR)", "profile_id": "family_with_children", "base_date": "2026-06-03T00:00:00", "seed": 20261243, "scenario_id": "CH-02", "total_events": 2301, "anomaly_events_count": 4}, "ground_truth": {"scenario_id": "CH-02-FP", "scenario_name": "CH-02-FP: 家长陪同孩子在厨房", "category": "child_specific", "is_anomaly": false, "threat_type": "none", "key_difference": "家长也在活动（living_room occupancy），不是孩子独自操作灶具", "difficulty_score": 10, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 3, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "dining_room", "injection_time": "2026-06-03T22:57:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"Systematic sensor data corruption causing phantom occupancy events and erratic temperature readings indicates a firmware loop or calibration failure rather than physical intrusion.\",\n  \"reasoning\": [\n      \"Occupancy sensors report '1' (occupied) with unnaturally high frequency (every 10-20 mins) across multiple rooms without corresponding door entry/exit events or light changes, suggesting a software reporting loop.\",\n      \"Temperature sensors exhibit non-linear fluctuations and sudden spikes (e.g., Master Bedroom jumping from 2258 to 2269 at 21:30 while the general trend was cooling), which contradicts standard thermal physics and indicates sensor noise or drift.\",\n      \"Critical actuator events like the Kitchen Window opening to 100% at 21:03 occurred while the room remained flagged as occupied, and subsequent lighting controls did not correlate with this state change, further pointing to disjointed sensor logic.\"\n    ],\n  \"key_evidence\": [\n      \"Timestamp 21:03:02 shows 'kids_room_window' lifting to 100% while 'kids_room_occupancy' remains 1, indicating a lack of environmental correlation typical of manual human activity.\",\n      \"Master bedroom temperature fluctuates erratically between 2254°C and 2269°C over short intervals, breaking the consistent cooling curve established by the HVAC activation.\",\n      \"Front door contact state changed to True (closed) and lock auto-locked at 22:36, yet entrance occupancy continued to log positive events in C06, creating a logical contradiction regarding occupant presence.\"\n    ],\n  \"recommended_actions\": [\n      \"Reboot the smart home hub and all affected sensors to clear potential firmware loops.\",\n      \"Replace the battery-powered occupancy sensors in the living room and kids' room if rebooting fails to stabilize the signal.\",\n      \"Calibrate temperature sensors or replace them if erratic variance persists after system reset.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "Systematic sensor data corruption causing phantom occupancy events and erratic temperature readings indicates a firmware loop or calibration failure rather than physical intrusion.", "reasoning": ["Occupancy sensors report '1' (occupied) with unnaturally high frequency (every 10-20 mins) across multiple rooms without corresponding door entry/exit events or light changes, suggesting a software reporting loop.", "Temperature sensors exhibit non-linear fluctuations and sudden spikes (e.g., Master Bedroom jumping from 2258 to 2269 at 21:30 while the general trend was cooling), which contradicts standard thermal physics and indicates sensor noise or drift.", "Critical actuator events like the Kitchen Window opening to 100% at 21:03 occurred while the room remained flagged as occupied, and subsequent lighting controls did not correlate with this state change, further pointing to disjointed sensor logic."], "key_evidence": ["Timestamp 21:03:02 shows 'kids_room_window' lifting to 100% while 'kids_room_occupancy' remains 1, indicating a lack of environmental correlation typical of manual human activity.", "Master bedroom temperature fluctuates erratically between 2254°C and 2269°C over short intervals, breaking the consistent cooling curve established by the HVAC activation.", "Front door contact state changed to True (closed) and lock auto-locked at 22:36, yet entrance occupancy continued to log positive events in C06, creating a logical contradiction regarding occupant presence."], "recommended_actions": ["Reboot the smart home hub and all affected sensors to clear potential firmware loops.", "Replace the battery-powered occupancy sensors in the living room and kids' room if rebooting fails to stabilize the signal.", "Calibrate temperature sensors or replace them if erratic variance persists after system reset."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 67.94674181938171, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 706, "chunk_count": 9, "signals": {"room_activity": {"living_room": 151, "master_bedroom": 148, "kids_room": 148, "kitchen": 82, "dining_room": 74, "entrance": 79, "second_bedroom": 12, "master_bathroom": 12}, "attribute_frequency": {"Occupancy": 388, "MeasuredValue": 294, "OnOff": 13, "StateValue": 3, "LockState": 2, "CurrentPositionLiftPercent100ths": 2, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 2, "occupancy_events": 388, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"behavior-sequence\",\n  \"focus_rooms\": [\n    \"kids_room\",\n    \"living_room\",\n    \"master_bedroom\",\n    \"entrance\"\n  ],\n  \"focus_devices\": [\n    \"kids_room_occupancy\",\n    \"living_room_occupancy\",\n    \"master_bedroom_occupancy\",\n    \"entrance_occupancy\",\n    \"kitchen_temp_sensor\",\n    \"living_room_temp_sensor\",\n    \"master_bedroom_temp_sensor\",\n    \"kids_room_temp_sensor\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C00\",\n    \"C01\",\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C06\",\n    \"C07\",\n    \"C08\"\n  ],\n  \"suspected_patterns\": [\n    \"High-frequency occupancy toggling in living areas (kids_room, living_room) suggests sensor sensitivity issues or rapid movement patterns.\",\n    \"Systematic temperature drift across all rooms (e.g., Kitchen: 2332 -> 2260; Living Room: 2323 -> 2251) indicates a potential HVAC malfunction or calibration error rather than environmental changes.\",\n    \"Disproportionate event count for occupancy sensors vs. other device types (LockState=2, OnOff=13) implies the primary system activity is motion detection logic.\",\n    \"Consistent 'alarmish_count' (~40-46 per chunk) despite lack of explicit alarm triggers suggests a high baseline noise floor or misconfigured thresholds.\"\n  ],\n  \"why_these_chunks\": [\n    \"All chunks are required to trace the continuous timeline of the suspected temperature drift and occupancy frequency anomalies.\",\n    \"Chunks C00-C03 establish the initial high temperature baseline and frequent room entry events.\",\n    \"Chunks C04-C08 confirm the progressive cooling trend and sustained high occupancy event rates, distinguishing between a one-time glitch and a systemic behavioral pattern.\",\n    \"The uniform distribution of events across chunks rules out localized hardware failure and points to a global configuration or environmental issue affecting the entire house.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "behavior-sequence", "focus_rooms": ["kids_room", "living_room", "master_bedroom", "entrance"], "focus_devices": ["kids_room_occupancy", "living_room_occupancy", "master_bedroom_occupancy", "entrance_occupancy", "kitchen_temp_sensor", "living_room_temp_sensor", "master_bedroom_temp_sensor", "kids_room_temp_sensor"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04", "C05", "C06", "C07", "C08"], "suspected_patterns": ["High-frequency occupancy toggling in living areas (kids_room, living_room) suggests sensor sensitivity issues or rapid movement patterns.", "Systematic temperature drift across all rooms (e.g., Kitchen: 2332 -> 2260; Living Room: 2323 -> 2251) indicates a potential HVAC malfunction or calibration error rather than environmental changes.", "Disproportionate event count for occupancy sensors vs. other device types (LockState=2, OnOff=13) implies the primary system activity is motion detection logic.", "Consistent 'alarmish_count' (~40-46 per chunk) despite lack of explicit alarm triggers suggests a high baseline noise floor or misconfigured thresholds."], "why_these_chunks": ["All chunks are required to trace the continuous timeline of the suspected temperature drift and occupancy frequency anomalies.", "Chunks C00-C03 establish the initial high temperature baseline and frequent room entry events.", "Chunks C04-C08 confirm the progressive cooling trend and sustained high occupancy event rates, distinguishing between a one-time glitch and a systemic behavioral pattern.", "The uniform distribution of events across chunks rules out localized hardware failure and points to a global configuration or environmental issue affecting the entire house."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"High-traffic household evening routine with active HVAC cooling cycle.\",\n      \"evidence\": [\n        \"Occupancy logs show consistent presence in living areas (Living Room: 151, Kids Room: 148) vs. low activity in secondary rooms (Second Bedroom: 12).\",\n        \"HVAC activation at 18:09 (SystemMode=3) followed by gradual temperature drop across all sensors from ~23°C to ~22.5°C over 6 hours.\",\n        \"Appliance usage events (Cook Surface ON at 18:25, Dishwasher ON at 19:40) align with typical meal preparation and cleanup times.\"\n      ],\n      \"weaknesses\": [\n        \"The frequency of occupancy toggling is extremely high for a single human resident; sensors report '1' every 10-20 minutes in the same room without clear movement context.\",\n        \"Temperature readings exhibit non-linear fluctuations that do not match standard thermal mass cooling curves (e.g., Kitchen jumps from 2267 to 2268 between 20:40 and 20:45).\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Sensor calibration drift or firmware loop causing phantom occupancy detection.\",\n      \"threat_type\": \"False Positive / Data Integrity\",\n      \"evidence\": [\n        \"Room Activity counts are disproportionately high for Living Room (151) and Master Bedroom (148) compared to physical likelihood of continuous re-detection within 6 hours.\",\n        \"Timestamps show repetitive 'Occupancy = 1' events with short intervals (e.g., C00: 18:00 -> 18:02 -> 18:07 -> 18:09) suggesting rapid cycling rather than distinct human entry/exit.\",\n        \"Temperature data shows erratic variance (e.g., Master Bedroom drops 2334->2321->2330->2318) inconsistent with ambient cooling, indicating potential sensor noise or reporting artifacts.\"\n      ],\n      \"weaknesses\": [\n        \"No explicit alarm triggers were generated despite the high event count, suggesting the system logic may be filtering these as noise rather than security breaches.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Covert surveillance or automated probing via window/lift devices.\",\n      \"threat_type\": \"Intrusion / Espionage\",\n      \"evidence\": [\n        \"Discrete interaction with specific devices outside of normal occupancy logic: Kids Room Window Covering set to 100% (fully open) at 21:03:02 while occupancy is still detected.\",\n        \"Front door lock manual operation at 18:09 followed immediately by door contact state change, but no corresponding long-term absence in entrance occupancy logs.\",\n        \"Sudden loss of temperature data points (Kitchen: None at 18:26 and 18:56) coinciding with appliance activity, potentially indicating sensor tampering or power interruption.\"\n      ],\n      \"weaknesses\": [\n        \"The timing of the window opening (21:03) occurs late in the log period when house appears settled, and the window covers returning to closed position would require another event not seen in this chunk set.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The statistical improbability of 148+ occupancy events in the Kids Room within 6 hours for a single dwelling indicates either sensor malfunction or an unlogged automated agent triggering the sensor repeatedly.\",\n    \"The specific sequence of 'Kids Room Window' lifting to 100% at 21:03:02 combined with persistent occupancy signals suggests a deliberate environmental change not explained by standard HVAC behavior.\",\n    \"Irregular temperature spikes (e.g., Living Room rising from 2253 to 2266 between 20:35 and 21:00) contradict the established cooling trend initiated at 18:09, pointing to external heat sources or sensor errors.\"\n  ],\n  \"missing_information\": [\n    \"Physical verification of whether occupants moved between rooms during the reported 'toggles' to rule out legitimate multi-room navigation.\",\n    \"Historical baseline of occupancy event rates for this specific hardware model to determine if the current frequency is abnormal.\",\n    \"Log entries for the specific timestamp ranges where temperature data returned 'None' to assess if it was a network dropout or sensor failure.\",\n    \"Status of the 'kids_room_light' which turned OFF at 21:03:02, same minute the window opened, to see if lighting control correlates with the window actuation.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "High-traffic household evening routine with active HVAC cooling cycle.", "evidence": ["Occupancy logs show consistent presence in living areas (Living Room: 151, Kids Room: 148) vs. low activity in secondary rooms (Second Bedroom: 12).", "HVAC activation at 18:09 (SystemMode=3) followed by gradual temperature drop across all sensors from ~23°C to ~22.5°C over 6 hours.", "Appliance usage events (Cook Surface ON at 18:25, Dishwasher ON at 19:40) align with typical meal preparation and cleanup times."], "weaknesses": ["The frequency of occupancy toggling is extremely high for a single human resident; sensors report '1' every 10-20 minutes in the same room without clear movement context.", "Temperature readings exhibit non-linear fluctuations that do not match standard thermal mass cooling curves (e.g., Kitchen jumps from 2267 to 2268 between 20:40 and 20:45)."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Sensor calibration drift or firmware loop causing phantom occupancy detection.", "threat_type": "False Positive / Data Integrity", "evidence": ["Room Activity counts are disproportionately high for Living Room (151) and Master Bedroom (148) compared to physical likelihood of continuous re-detection within 6 hours.", "Timestamps show repetitive 'Occupancy = 1' events with short intervals (e.g., C00: 18:00 -> 18:02 -> 18:07 -> 18:09) suggesting rapid cycling rather than distinct human entry/exit.", "Temperature data shows erratic variance (e.g., Master Bedroom drops 2334->2321->2330->2318) inconsistent with ambient cooling, indicating potential sensor noise or reporting artifacts."], "weaknesses": ["No explicit alarm triggers were generated despite the high event count, suggesting the system logic may be filtering these as noise rather than security breaches."]}, {"id": "A2", "description": "Covert surveillance or automated probing via window/lift devices.", "threat_type": "Intrusion / Espionage", "evidence": ["Discrete interaction with specific devices outside of normal occupancy logic: Kids Room Window Covering set to 100% (fully open) at 21:03:02 while occupancy is still detected.", "Front door lock manual operation at 18:09 followed immediately by door contact state change, but no corresponding long-term absence in entrance occupancy logs.", "Sudden loss of temperature data points (Kitchen: None at 18:26 and 18:56) coinciding with appliance activity, potentially indicating sensor tampering or power interruption."], "weaknesses": ["The timing of the window opening (21:03) occurs late in the log period when house appears settled, and the window covers returning to closed position would require another event not seen in this chunk set."]}], "most_discriminative_evidence": ["The statistical improbability of 148+ occupancy events in the Kids Room within 6 hours for a single dwelling indicates either sensor malfunction or an unlogged automated agent triggering the sensor repeatedly.", "The specific sequence of 'Kids Room Window' lifting to 100% at 21:03:02 combined with persistent occupancy signals suggests a deliberate environmental change not explained by standard HVAC behavior.", "Irregular temperature spikes (e.g., Living Room rising from 2253 to 2266 between 20:35 and 21:00) contradict the established cooling trend initiated at 18:09, pointing to external heat sources or sensor errors."], "missing_information": ["Physical verification of whether occupants moved between rooms during the reported 'toggles' to rule out legitimate multi-room navigation.", "Historical baseline of occupancy event rates for this specific hardware model to determine if the current frequency is abnormal.", "Log entries for the specific timestamp ranges where temperature data returned 'None' to assess if it was a network dropout or sensor failure.", "Status of the 'kids_room_light' which turned OFF at 21:03:02, same minute the window opened, to see if lighting control correlates with the window actuation."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C03\", \"C05\"],\n  \"missing_checks\": [\n    \"Verify specific temperature timestamps in C03 and C05 to confirm the erratic fluctuations mentioned in A1 (Master Bedroom spikes) and the cooling trend continuity.\",\n    \"Cross-reference occupancy event IDs in C03 and C05 with the 'Kids Room Window' actuation time (21:03:02) to determine if the sensor toggling persists before or after the window state change.\",\n    \"Check network connectivity status in missing chunks to rule out packet loss as the cause for 'None' temperature readings noted by the Investigator.\"\n  ],\n  \"supervisor_notes\": [\n    \"The current evidence is insufficient because the Investigator's hypothesis A1 relies on specific timestamped anomalies (temperature spikes and erratic variance) that must be verified against the raw log data in the identified chunks.\",\n    \"Chunk C03 is critical to verify the transition point of the 'cooling trend' and the initial frequency of occupancy toggles described in Triage.\",\n    \"Chunk C05 is required to isolate whether the 'window opening at 21:03' correlates with a spike in occupancy events or if it causes a drop in them; this distinction determines if the anomaly is behavioral or mechanical.\",\n    \"The lack of explicit alarm triggers makes the high event count ambiguous; without granular data from these specific chunks, we cannot confirm if the system is logging noise or missing actual intrusion patterns.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C03", "C05"], "missing_checks": ["Verify specific temperature timestamps in C03 and C05 to confirm the erratic fluctuations mentioned in A1 (Master Bedroom spikes) and the cooling trend continuity.", "Cross-reference occupancy event IDs in C03 and C05 with the 'Kids Room Window' actuation time (21:03:02) to determine if the sensor toggling persists before or after the window state change.", "Check network connectivity status in missing chunks to rule out packet loss as the cause for 'None' temperature readings noted by the Investigator."], "supervisor_notes": ["The current evidence is insufficient because the Investigator's hypothesis A1 relies on specific timestamped anomalies (temperature spikes and erratic variance) that must be verified against the raw log data in the identified chunks.", "Chunk C03 is critical to verify the transition point of the 'cooling trend' and the initial frequency of occupancy toggles described in Triage.", "Chunk C05 is required to isolate whether the 'window opening at 21:03' correlates with a spike in occupancy events or if it causes a drop in them; this distinction determines if the anomaly is behavioral or mechanical.", "The lack of explicit alarm triggers makes the high event count ambiguous; without granular data from these specific chunks, we cannot confirm if the system is logging noise or missing actual intrusion patterns."]}, "preview_triage_prompt": "## Query\n以下是过去 6 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Layout\nLayout: 三室两厅 (3BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kids_room: 儿童房温度传感器<temperature_sensor>, 儿童房灯<dimmable_light>, 儿童房窗帘<window_covering>, 儿童房窗户传感器<contact_sensor>, 儿童房运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅副灯<dimmable_light>, 客厅氛围灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘1<window_covering>, 客厅窗户传感器1<contact_sensor>, 客厅窗户传感器2<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n- master_bathroom: 主卫漏水传感器<water_leak_detector>, 主卫灯<onoff_light>, 主卫运动传感器<occupancy_sensor>\n- master_bedroom: 主卧床头灯<onoff_light>, 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>\n- second_bedroom: 次卧灯<dimmable_light>, 次卧空调<air_conditioner>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 151,\n    \"master_bedroom\": 148,\n    \"kids_room\": 148,\n    \"kitchen\": 82,\n    \"dining_room\": 74,\n    \"entrance\": 79,\n    \"second_bedroom\": 12,\n    \"master_bathroom\": 12\n  },\n  \"attribute_frequency\": {\n    \"Occupancy\": 388,\n    \"MeasuredValue\": 294,\n    \"OnOff\": 13,\n    \"StateValue\": 3,\n    \"LockState\": 2,\n    \"CurrentPositionLiftPercent100ths\": 2,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 2,\n  \"occupancy_events\": 388,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-03T17:55:00\",\n    \"end_ts\": \"2026-06-03T18:30:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 17,\n      \"master_bedroom\": 16,\n      \"kids_room\": 15,\n      \"kitchen\": 11,\n      \"dining_room\": 7,\n      \"entrance\": 11,\n      \"second_bedroom\": 2,\n      \"master_bathroom\": 1\n    },\n    \"top_devices\": [\n      \"kitchen_temp_sensor\",\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"kids_room_temp_sensor\",\n      \"master_bedroom_occupancy\",\n      \"entrance_occupancy\"\n    ],\n ", "preview_verifier_prompt": "## Query\n以下是过去 6 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Triage\n{\n  \"latent_task_profile\": \"behavior-sequence\",\n  \"focus_rooms\": [\n    \"kids_room\",\n    \"living_room\",\n    \"master_bedroom\",\n    \"entrance\"\n  ],\n  \"focus_devices\": [\n    \"kids_room_occupancy\",\n    \"living_room_occupancy\",\n    \"master_bedroom_occupancy\",\n    \"entrance_occupancy\",\n    \"kitchen_temp_sensor\",\n    \"living_room_temp_sensor\",\n    \"master_bedroom_temp_sensor\",\n    \"kids_room_temp_sensor\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C00\",\n    \"C01\",\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C06\",\n    \"C07\",\n    \"C08\"\n  ],\n  \"suspected_patterns\": [\n    \"High-frequency occupancy toggling in living areas (kids_room, living_room) suggests sensor sensitivity issues or rapid movement patterns.\",\n    \"Systematic temperature drift across all rooms (e.g., Kitchen: 2332 -> 2260; Living Room: 2323 -> 2251) indicates a potential HVAC malfunction or calibration error rather than environmental changes.\",\n    \"Disproportionate event count for occupancy sensors vs. other device types (LockState=2, OnOff=13) implies the primary system activity is motion detection logic.\",\n    \"Consistent 'alarmish_count' (~40-46 per chunk) despite lack of explicit alarm triggers suggests a high baseline noise floor or misconfigured thresholds.\"\n  ],\n  \"why_these_chunks\": [\n    \"All chunks are required to trace the continuous timeline of the suspected temperature drift and occupancy frequency anomalies.\",\n    \"Chunks C00-C03 establish the initial high temperature baseline and frequent room entry events.\",\n    \"Chunks C04-C08 confirm the progressive cooling trend and sustained high occupancy event rates, distinguishing between a one-time glitch and a systemic behavioral pattern.\",\n    \"The uniform distribution of events across chunks rules out localized hardware failure and points to a global configuration or environmental issue affecting the entire house.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"High-traffic household evening routine with active HVAC cooling cycle.\",\n      \"evidence\": [\n        \"Occupancy logs show consistent presence in living areas (Living Room: 151, Kids Room: 148) vs. low activity in secondary rooms (Second Bedroom: 12).\",\n        \"HVAC activation at 18:09 (SystemMode=3) followed by gradual temperature drop across all sensors from ~23°C to ~22.5°C over 6 hours.\",\n        \"Appliance usage events (Cook Surface ON at 18:25, Dishwasher ON at 19:40) align w"}}
{"episode_id": "SQ3_TN_A_0665", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq3\\SQ3_TN_A_0665.json", "metadata": {"sq_type": "SQ3", "sq_name": "行为序列分析", "variant": "TN", "layout_id": "A", "layout_name": "一室一厅 (Studio/1BR)", "profile_id": "young_professional", "base_date": "2026-06-24T00:00:00", "seed": 20261294, "scenario_id": null, "total_events": 1119, "anomaly_events_count": 0}, "ground_truth": {"scenario_id": "TN", "scenario_name": "Normal — no anomaly", "category": "none", "is_anomaly": false, "threat_type": "none", "variant": "TN", "difficulty_score": 0, "difficulty_level": 0, "difficulty_label": "TN_baseline", "difficulty_dimensions": {"D1_evidence_count": 0, "D2_signal_directness": 0, "D3_cross_device": 0, "D4_temporal_span": 0, "D5_fp_similarity": 0}}, "raw_response": "{\n  \"is_anomaly\": false,\n  \"confidence\": \"high\",\n  \"threat_type\": \"none\",\n  \"threat_description\": \"The observed high-frequency sensor polling is consistent with standard passive monitoring and routine household activity patterns, showing no evidence of intrusion or malfunction.\",\n  \"reasoning\": [\n      \"Analysis of chunks C01-C04 confirms that temperature and occupancy reports occur at regular intervals (e.g., :00, :03) which aligns with the Investigator's hypothesis N2 (Sensor polling loop artifact) rather than an external script (A1).\",\n      \"The occupancy data shows logical transitions corresponding to real-world events: Bedroom occupancy drops at 20:09, 20:39, and 21:39, followed by lights turning off and locks engaging around 22:00-22:05, indicating a normal sleep sequence where occupants leave the bedroom to settle in or use other facilities before locking up.\",\n      \"Environmental sensors report gradual thermal drift (e.g., Living Room cooling from ~22.8°C to ~22.4°C) without any actuator intervention (HVAC off), which is expected behavior for evening hours when heating/cooling systems are typically set back, ruling out sensor malfunction or unexplained anomalies.\"\n    ],\n  \"key_evidence\": [\n      \"Consistent correlation between 'Occupancy=0' events in the bedroom and subsequent door lock operations at 22:00:55.\",\n      \"Gradual, physically plausible temperature decreases across all rooms over the 6-hour period without sudden spikes or flatlining indicative of failure.\"\n    ],\n  \"recommended_actions\": [\n      \"Continue routine monitoring; no immediate intervention required.\",\n      \"Archive logs as part of standard historical baseline maintenance.\"\n  ]\n}", "model_response": {"is_anomaly": false, "confidence": "high", "threat_type": "none", "threat_description": "The observed high-frequency sensor polling is consistent with standard passive monitoring and routine household activity patterns, showing no evidence of intrusion or malfunction.", "reasoning": ["Analysis of chunks C01-C04 confirms that temperature and occupancy reports occur at regular intervals (e.g., :00, :03) which aligns with the Investigator's hypothesis N2 (Sensor polling loop artifact) rather than an external script (A1).", "The occupancy data shows logical transitions corresponding to real-world events: Bedroom occupancy drops at 20:09, 20:39, and 21:39, followed by lights turning off and locks engaging around 22:00-22:05, indicating a normal sleep sequence where occupants leave the bedroom to settle in or use other facilities before locking up.", "Environmental sensors report gradual thermal drift (e.g., Living Room cooling from ~22.8°C to ~22.4°C) without any actuator intervention (HVAC off), which is expected behavior for evening hours when heating/cooling systems are typically set back, ruling out sensor malfunction or unexplained anomalies."], "key_evidence": ["Consistent correlation between 'Occupancy=0' events in the bedroom and subsequent door lock operations at 22:00:55.", "Gradual, physically plausible temperature decreases across all rooms over the 6-hour period without sudden spikes or flatlining indicative of failure."], "recommended_actions": ["Continue routine monitoring; no immediate intervention required.", "Archive logs as part of standard historical baseline maintenance."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "CORRECT_REJECT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 53.336055278778076, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 344, "chunk_count": 5, "signals": {"room_activity": {"living_room": 145, "bedroom": 98, "kitchen": 81, "bathroom": 12, "entrance": 8}, "attribute_frequency": {"MeasuredValue": 221, "Occupancy": 100, "OnOff": 12, "StateValue": 3, "LockState": 2, "SystemMode": 1, "OperationalState": 1, "CurrentPositionLiftPercent100ths": 1, "CurrentLevel": 1}, "lock_state_flips": 2, "occupancy_events": 100, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"behavior-sequence\",\n  \"focus_rooms\": [\"living_room\", \"bedroom\"],\n  \"focus_devices\": [\"living_room_occupancy\", \"bedroom_occupancy\", \"living_room_temp_sensor\", \"bedroom_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C01\", \"C02\", \"C03\"],\n  \"suspected_patterns\": [\n    \"sustained occupancy without corresponding temperature regulation adjustments\",\n    \"disproportionate sensor polling frequency in occupied zones compared to activity logs\"\n  ],\n  \"why_these_chunks\": [\n    \"C01-C03 show continuous 'Occupancy=1' events in living/bedrooms while temperature readings remain static or drift slightly, suggesting passive monitoring rather than active thermal interaction.\",\n    \"The high frequency of occupancy toggles in these specific chunks indicates a sequence of presence detection that warrants verification against actual human activity (e.g., sleeping vs. awake) to rule out sensor malfunction or environmental anomalies.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "behavior-sequence", "focus_rooms": ["living_room", "bedroom"], "focus_devices": ["living_room_occupancy", "bedroom_occupancy", "living_room_temp_sensor", "bedroom_temp_sensor"], "focus_chunk_ids": ["C01", "C02", "C03"], "suspected_patterns": ["sustained occupancy without corresponding temperature regulation adjustments", "disproportionate sensor polling frequency in occupied zones compared to activity logs"], "why_these_chunks": ["C01-C03 show continuous 'Occupancy=1' events in living/bedrooms while temperature readings remain static or drift slightly, suggesting passive monitoring rather than active thermal interaction.", "The high frequency of occupancy toggles in these specific chunks indicates a sequence of presence detection that warrants verification against actual human activity (e.g., sleeping vs. awake) to rule out sensor malfunction or environmental anomalies."]}, "investigator_raw": "```json\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Standard evening household routine with passive monitoring and sleep transition.\",\n      \"evidence\": [\n        \"High frequency 'Occupancy=1' events in living_room correlate with active kitchen usage (dishwasher On/Off, cooking surface changes) between 19:45-20:00.\",\n        \"Bedroom occupancy transitions to '0' at 20:09, 20:39, 21:39, suggesting occupants leaving the room for bathroom or other activities before settling down.\",\n        \"Systematic temperature drift (Living ~22°C -> 21.5°C; Bedroom ~21.7°C -> 21.4°C) indicates cooling systems are off or running at low power as expected during evening hours.\"\n    ],\n    {\n      \"id\": \"N2\",\n      \"description\": \"Sensor polling loop artifact where high frequency readings mimic human activity.\",\n      \"evidence\": [\n        \"Temperature sensors report values every 5 minutes consistently regardless of actual thermal changes.\",\n        \"Occupancy sensor reports '1' repeatedly even when no state-change event (like door contact) occurs, which is typical behavior for a sensor confirming continuous presence rather than detecting new entries.\"\n    ]\n  },\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Covert surveillance or unauthorized data exfiltration via automated sensor polling.\",\n      \"threat_type\": \"Surveillance / Espionage\",\n      \"evidence\": [\n        \"The frequency of 'MeasuredValue' reports (221 total) vastly exceeds normal HVAC control cycles, creating a detailed log of minute-by-minute environmental conditions.\",\n        \"In C01-C03, Temperature and Occupancy sensors fire almost simultaneously (within seconds) at regular intervals (e.g., :00, :03, :20, :30), creating a rigid, machine-generated heartbeat pattern inconsistent with organic human movement.\",\n        \"The specific granularity (e.g., distinguishing bedroom occupancy drop at 20:09 vs 20:39) suggests an intent to track precise behavioral schedules rather than just system status.\"\n    ],\n    {\n      \"id\": \"A2\",\n      \"description\": \"Device malfunction or misconfiguration causing false positive occupancy alerts.\",\n      \"threat_type\": \"Operational Anomaly\",\n      \"evidence\": [\n        \"Bedroom occupancy toggles between 0 and 1 frequently (e.g., 20:09->0, 20:39->0, 21:39->0) while temperature sensors remain stable, suggesting the occupant may have left but the sensor logic is stuck or being polled aggressively.\",\n        \"At 22:00:30, bedroom occupancy becomes 1 immediately after lights turn on, but prior logs show it was 0 until then, indicating a potential glitch in the wake-up logic or a phantom trigger.\"\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The rigid temporal alignment of temperature and occupancy reports (occurring at fixed 5-minute or sub-minute intervals across all chunks) suggests an automated script or compromised device rather than natural user interaction.\",\n    \"The discrepancy between the high volume of 'MeasuredValue' signals (221) and the low count of actual state-changing events like 'LockState' (2) or 'OnOff' (12) implies the system is actively interrogating the environment passively.\"\n  ],\n  \"missing_information\": [\n    \"Network traffic logs to determine if these signals originate from a local gateway or an external IP address.\",\n    \"Historical baseline data to compare current polling frequency against standard operating procedures.\",\n    \"Physical verification of sensor placement to rule out line-of-sight interference causing erratic occupancy toggles.\"\n  ]\n}\n```", "investigator_parsed": {"_parse_failed": true, "raw_preview": "```json\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Standard evening household routine with passive monitoring and sleep transition.\",\n      \"evidence\": [\n        \"High frequency 'Occupancy=1' events in living_room correlate with active kitchen usage (dishwasher On/Off, cooking surface changes) between 19:45-20:00.\",\n        \"Bedroom occupancy transitions to '0' at 20:09, 20:39, 21:39, suggesting occupants leaving the room for bathroom or other activities before settling down.\",\n        \"Systematic temperature drift (Living ~22°C -> 21.5°C; Bedroom ~21.7°C -> 21.4°C) indicates cooling systems are off or running at low power as expected during evening hours.\"\n    ],\n    {\n      \"id\": \"N2\",\n      \"description\": \"Sensor polling loop artifact where high frequency readings mimic human activity.\",\n      \"evidence\": [\n        \"Temperature sensors report values every 5 minutes consistently regardless of actual thermal changes.\",\n        \"Occupancy sensor reports '1"}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C04\"],\n  \"missing_checks\": [\n    \"Verify network traffic logs to rule out external IP intrusion.\",\n    \"Compare current polling frequency against historical baseline data.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis is on-topic and correctly identifies the discrepancy between high-frequency sensor polling and low state-change events.\",\n    \"Evidence is insufficient because the investigation relies entirely on chunks C01-C03. The available log covers 6 hours but includes chunks C00, C01, C02, C03, and C04.\",\n    \"Without reviewing C00 (likely early morning/late night) and potentially C04 (if it exists in the full dataset or if C04 is needed to verify the pattern's continuity), we cannot confirm if this behavior is a constant anomaly or an isolated incident.\",\n    \"The Investigator correctly noted missing information regarding network logs and baselines; these must be requested before finalizing the threat assessment.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C04"], "missing_checks": ["Verify network traffic logs to rule out external IP intrusion.", "Compare current polling frequency against historical baseline data."], "supervisor_notes": ["The analysis is on-topic and correctly identifies the discrepancy between high-frequency sensor polling and low state-change events.", "Evidence is insufficient because the investigation relies entirely on chunks C01-C03. The available log covers 6 hours but includes chunks C00, C01, C02, C03, and C04.", "Without reviewing C00 (likely early morning/late night) and potentially C04 (if it exists in the full dataset or if C04 is needed to verify the pattern's continuity), we cannot confirm if this behavior is a constant anomaly or an isolated incident.", "The Investigator correctly noted missing information regarding network logs and baselines; these must be requested before finalizing the threat assessment."]}, "preview_triage_prompt": "## Query\n以下是过去 6 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Layout\nLayout: 一室一厅 (Studio/1BR)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅台灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 145,\n    \"bedroom\": 98,\n    \"kitchen\": 81,\n    \"bathroom\": 12,\n    \"entrance\": 8\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 221,\n    \"Occupancy\": 100,\n    \"OnOff\": 12,\n    \"StateValue\": 3,\n    \"LockState\": 2,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"CurrentPositionLiftPercent100ths\": 1,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 2,\n  \"occupancy_events\": 100,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-24T17:55:00\",\n    \"end_ts\": \"2026-06-24T19:20:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 33,\n      \"bedroom\": 20,\n      \"kitchen\": 20,\n      \"bathroom\": 3,\n      \"entrance\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"bathroom_occupancy\"\n    ],\n    \"alarmish_count\": 19,\n    \"preview_lines\": [\n      \"[2026-06-24T17:55:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2334\",\n      \"[2026-06-24T17:55:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2223\",\n      \"[2026-06-24T17:55:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2335\",\n      \"[2026-06-24T18:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2335\",\n      \"[2026-06-24T18:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2215\",\n      \"[2026-06-24T18:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2390\",\n      \"[2026-06-24T18:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-24T18:05:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2331\",\n ", "preview_verifier_prompt": "## Query\n以下是过去 6 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Triage\n{\n  \"latent_task_profile\": \"behavior-sequence\",\n  \"focus_rooms\": [\"living_room\", \"bedroom\"],\n  \"focus_devices\": [\"living_room_occupancy\", \"bedroom_occupancy\", \"living_room_temp_sensor\", \"bedroom_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C01\", \"C02\", \"C03\"],\n  \"suspected_patterns\": [\n    \"sustained occupancy without corresponding temperature regulation adjustments\",\n    \"disproportionate sensor polling frequency in occupied zones compared to activity logs\"\n  ],\n  \"why_these_chunks\": [\n    \"C01-C03 show continuous 'Occupancy=1' events in living/bedrooms while temperature readings remain static or drift slightly, suggesting passive monitoring rather than active thermal interaction.\",\n    \"The high frequency of occupancy toggles in these specific chunks indicates a sequence of presence detection that warrants verification against actual human activity (e.g., sleeping vs. awake) to rule out sensor malfunction or environmental anomalies.\"\n  ]\n}\n\n## Investigator\n```json\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Standard evening household routine with passive monitoring and sleep transition.\",\n      \"evidence\": [\n        \"High frequency 'Occupancy=1' events in living_room correlate with active kitchen usage (dishwasher On/Off, cooking surface changes) between 19:45-20:00.\",\n        \"Bedroom occupancy transitions to '0' at 20:09, 20:39, 21:39, suggesting occupants leaving the room for bathroom or other activities before settling down.\",\n        \"Systematic temperature drift (Living ~22°C -> 21.5°C; Bedroom ~21.7°C -> 21.4°C) indicates cooling systems are off or running at low power as expected during evening hours.\"\n    ],\n    {\n      \"id\": \"N2\",\n      \"description\": \"Sensor polling loop artifact where high frequency readings mimic human activity.\",\n      \"evidence\": [\n        \"Temperature sensors report values every 5 minutes consistently regardless of actual thermal changes.\",\n        \"Occupancy sensor reports '1' repeatedly even when no state-change event (like door contact) occurs, which is typical behavior for a sensor confirming continuous presence rather than detecting new entries.\"\n    ]\n  },\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Covert surveillance or unauthorized data exfiltration via automated sensor polling.\",\n      \"threat_type\": \"Surveillance / Espionage\",\n      \"evidence\": [\n        \"The frequency of 'MeasuredValue' reports (221 t"}}
{"episode_id": "SQ3_TP_A_0478", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq3\\SQ3_TP_A_0478.json", "metadata": {"sq_type": "SQ3", "sq_name": "行为序列分析", "variant": "TP", "layout_id": "A", "layout_name": "一室一厅 (Studio/1BR)", "profile_id": "young_professional", "base_date": "2026-06-20T00:00:00", "seed": 20261107, "scenario_id": "BA-03", "total_events": 1353, "anomaly_events_count": 7}, "ground_truth": {"scenario_id": "BA-03", "scenario_name": "异常高频设备交互", "category": "behavioral_anomaly", "is_anomaly": true, "threat_type": "behavioral_anomaly", "key_evidence": ["1分钟内多次灯光开关", "可能原因：智能家居系统被入侵/远程控制；设备自动化规则冲突；或电路问题", "也可能是恐慌信号（住户通过反复开关灯试图引起注意）"], "expected_response": "通知住户检查是否有人误操作或系统异常", "difficulty_score": 10, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 3, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "bathroom", "injection_time": "2026-06-20T14:51:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"Systemic sensor data integrity failure due to unit conversion error (missing decimal point), causing physically impossible temperature readings and triggering false positive alarm states.\",\n  \"reasoning\": [\n    \"Analysis of all provided chunks (C00-C04) reveals that temperature values from all sensors consistently display integers in the range of 2100-2399 (e.g., 2324, 2227).\",\n    \"These values are mathematically equivalent to realistic room temperatures (~21.2°C - 23.9°C) only when divided by 100, indicating a systematic formatting or transmission error where the decimal point is omitted or the value is scaled by 100 instead of 1.\",\n    \"The Triage output explicitly notes 'Temperature values are scaled by a factor of 10' (implied as 100 based on data magnitude) and 'consistent alarmish counts', confirming that the monitoring system interprets these raw integer values as critical overheating events (>2300°C), leading to false safety alerts.\",\n    \"While an automated lock operation occurred at 23:11, the log indicates `OperationSource=Auto` coinciding with lights turning off and occupants remaining inside, suggesting this was likely a routine automation rather than a security breach, making the sensor data error the primary anomaly.\"\n  ],\n  \"key_evidence\": [\n    \"Log entries show `living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2324` at 17:55:00, which is physically impossible for Celsius without scaling correction.\",\n    \"The pattern persists across all rooms (Living Room, Bedroom, Kitchen) and throughout the entire 6-hour window, ruling out individual sensor hardware failure.\",\n    \"Triage output confirms 'consistent alarmish counts' despite no visible fire events, directly correlating the anomaly to the malformed temperature data.\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately disable automatic alarm triggers based on temperature readings until the data feed is corrected.\",\n    \"Contact the IoT vendor or facility IT to inspect the sensor driver code or MQTT message configuration to locate the missing decimal point or incorrect unit multiplier.\",\n    \"Verify historical logs to determine if this calibration error is new or has been present since installation.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "Systemic sensor data integrity failure due to unit conversion error (missing decimal point), causing physically impossible temperature readings and triggering false positive alarm states.", "reasoning": ["Analysis of all provided chunks (C00-C04) reveals that temperature values from all sensors consistently display integers in the range of 2100-2399 (e.g., 2324, 2227).", "These values are mathematically equivalent to realistic room temperatures (~21.2°C - 23.9°C) only when divided by 100, indicating a systematic formatting or transmission error where the decimal point is omitted or the value is scaled by 100 instead of 1.", "The Triage output explicitly notes 'Temperature values are scaled by a factor of 10' (implied as 100 based on data magnitude) and 'consistent alarmish counts', confirming that the monitoring system interprets these raw integer values as critical overheating events (>2300°C), leading to false safety alerts.", "While an automated lock operation occurred at 23:11, the log indicates `OperationSource=Auto` coinciding with lights turning off and occupants remaining inside, suggesting this was likely a routine automation rather than a security breach, making the sensor data error the primary anomaly."], "key_evidence": ["Log entries show `living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2324` at 17:55:00, which is physically impossible for Celsius without scaling correction.", "The pattern persists across all rooms (Living Room, Bedroom, Kitchen) and throughout the entire 6-hour window, ruling out individual sensor hardware failure.", "Triage output confirms 'consistent alarmish counts' despite no visible fire events, directly correlating the anomaly to the malformed temperature data."], "recommended_actions": ["Immediately disable automatic alarm triggers based on temperature readings until the data feed is corrected.", "Contact the IoT vendor or facility IT to inspect the sensor driver code or MQTT message configuration to locate the missing decimal point or incorrect unit multiplier.", "Verify historical logs to determine if this calibration error is new or has been present since installation."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 48.52827000617981, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 387, "chunk_count": 5, "signals": {"room_activity": {"living_room": 147, "bedroom": 147, "kitchen": 78, "bathroom": 12, "entrance": 3}, "attribute_frequency": {"MeasuredValue": 220, "Occupancy": 156, "OnOff": 5, "StateValue": 2, "OperationalState": 1, "CurrentPositionLiftPercent100ths": 1, "LockState": 1}, "lock_state_flips": 1, "occupancy_events": 156, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"single-event-safety | composite-safety\",\n  \"focus_rooms\": [\"living_room\", \"bedroom\"],\n  \"focus_devices\": [\"living_room_temp_sensor\", \"bedroom_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\"],\n  \"suspected_patterns\": [\n    \"Temperature values are scaled by a factor of 10 (e.g., 23.24°C reported as 2324), indicating a potential sensor calibration or data transmission issue.\",\n    \"High frequency of temperature readings from living room and bedroom sensors relative to occupancy events suggests either continuous logging errors or anomalous sensor behavior.\",\n    \"Consistent 'alarmish' counts across chunks despite no explicit alarm triggers in previews, suggesting the system is flagging the data anomalies mentioned above.\"\n  ],\n  \"why_these_chunks\": \"All chunks (C00-C04) must be inspected because the temperature anomaly appears consistently across the entire 6-hour window. The pattern of high-frequency temperature logs with suspiciously precise decimal-like integer values (ending in even numbers) persists regardless of time of day or room activity, indicating a systemic sensor/logic error rather than a transient event.\"\n}", "triage_parsed": {"latent_task_profile": "single-event-safety | composite-safety", "focus_rooms": ["living_room", "bedroom"], "focus_devices": ["living_room_temp_sensor", "bedroom_temp_sensor"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04"], "suspected_patterns": ["Temperature values are scaled by a factor of 10 (e.g., 23.24°C reported as 2324), indicating a potential sensor calibration or data transmission issue.", "High frequency of temperature readings from living room and bedroom sensors relative to occupancy events suggests either continuous logging errors or anomalous sensor behavior.", "Consistent 'alarmish' counts across chunks despite no explicit alarm triggers in previews, suggesting the system is flagging the data anomalies mentioned above."], "why_these_chunks": "All chunks (C00-C04) must be inspected because the temperature anomaly appears consistently across the entire 6-hour window. The pattern of high-frequency temperature logs with suspiciously precise decimal-like integer values (ending in even numbers) persists regardless of time of day or room activity, indicating a systemic sensor/logic error rather than a transient event."}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Systematic Data Scaling/Transmission Error\",\n      \"evidence\": [\"All temperature values are integers ending in even digits (e.g., 2324, 2227) consistent with a Celsius * 100 scaling factor.\", \"Values show gradual cooling trends over time (23xx -> 22xx -> 21xx), which is physically plausible for an unoccupied or cooling home at night.\", \"The pattern persists across all rooms and sensors simultaneously, suggesting a central data processing pipeline issue rather than individual sensor failure.\"],\n      \"weaknesses\": [\"Does not explain the specific anomaly of 'Alarm' flags if the system expects raw decimals.\", \"Does not account for the sudden lock state flip without explicit user interaction logs.\"]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"Standard Residential Evening Routine\",\n      \"evidence\": [\"High occupancy counts (156 events) indicate residents were present.\", \"Kitchen appliances (cooker off, dishwasher on) suggest meal preparation/cleanup.\", \"Lights turned off and front door locked at 23:11 indicates residents leaving the house.\"],\n      \"weaknesses\": [\"Fails to address the illogical format of the temperature readings.\", \"Cannot explain why the single lock flip is flagged as significant by the triage logic.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Sensor Calibration Failure leading to False Positive Alarms\",\n      \"threat_type\": \"Operational Integrity | Data Integrity\",\n      \"evidence\": [\"Triage output explicitly notes 'Temperature values are scaled by a factor of 10'.\", \"Raw values like 2324°C are physically impossible, indicating a unit conversion bug (Celsius instead of milli-Celsius).\", \"The triage system mentions 'consistent alarmish counts' despite no visible alarm triggers, implying the backend interpreted these massive numbers as critical overheating events.\"],\n      \"weaknesses\": [\"No actual fire or life-safety event occurred; the threat is purely to the reliability of the monitoring system.\"]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Covert Access Attempt Detected via Lock State Flip\",\n      \"threat_type\": \"Physical Security Breach\",\n      \"evidence\": [\"Structured signals report exactly 1 'lock_state_flips'.\", \"Chunk C04 shows `front_door_lock | Event: LockOperation(LockOperationType=0...)` followed immediately by `DoorLock.LockState = 1`. In many systems, Type 0 can be 'Unlock' or 'Flip', and State 1 often means 'Locked' or 'Unlocked' depending on convention. If the resident was already inside (high occupancy until 23:11), a sudden lock operation could indicate a tamper attempt or unauthorized re-locking/unlocking sequence.\", \"The timing (23:11) coincides with lights going off and the user potentially leaving, making a forced lock/unlock sequence suspicious.\"],\n      \"weaknesses\": [\"The log entry includes `OperationSource=Auto`, which suggests it might be a scheduled routine or automated response to the door opening, reducing the likelihood of manual intrusion.\", \"Without knowing the definition of LockState 0 vs 1, we cannot confirm if this represents a breach or a normal cycle.\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The universal presence of temperature values in the range of 2100-2399 across all sensors, which mathematically correspond to ~21-24°C when divided by 100, strongly points to a systemic data formatting error rather than a physical phenomenon.\",\n    \"The correlation between the 'Alarmish' status in the Triage Output and the temperature data confirms that the anomaly is being actively detected by the security logic, likely due to out-of-bounds numerical values triggering threshold breaches.\"\n  ],\n  \"missing_information\": [\n    \"Definition of LockState values (0 and 1) and LockOperationType 0 to determine if the lock flip represents a breach or a routine action.\",\n    \"The source code or configuration of the temperature sensor driver to verify the missing decimal point or unit conversion logic.\",\n    \"Historical logs to see if this scaling error started recently or has been present since installation.\"]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Systematic Data Scaling/Transmission Error", "evidence": ["All temperature values are integers ending in even digits (e.g., 2324, 2227) consistent with a Celsius * 100 scaling factor.", "Values show gradual cooling trends over time (23xx -> 22xx -> 21xx), which is physically plausible for an unoccupied or cooling home at night.", "The pattern persists across all rooms and sensors simultaneously, suggesting a central data processing pipeline issue rather than individual sensor failure."], "weaknesses": ["Does not explain the specific anomaly of 'Alarm' flags if the system expects raw decimals.", "Does not account for the sudden lock state flip without explicit user interaction logs."]}, {"id": "N2", "description": "Standard Residential Evening Routine", "evidence": ["High occupancy counts (156 events) indicate residents were present.", "Kitchen appliances (cooker off, dishwasher on) suggest meal preparation/cleanup.", "Lights turned off and front door locked at 23:11 indicates residents leaving the house."], "weaknesses": ["Fails to address the illogical format of the temperature readings.", "Cannot explain why the single lock flip is flagged as significant by the triage logic."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Sensor Calibration Failure leading to False Positive Alarms", "threat_type": "Operational Integrity | Data Integrity", "evidence": ["Triage output explicitly notes 'Temperature values are scaled by a factor of 10'.", "Raw values like 2324°C are physically impossible, indicating a unit conversion bug (Celsius instead of milli-Celsius).", "The triage system mentions 'consistent alarmish counts' despite no visible alarm triggers, implying the backend interpreted these massive numbers as critical overheating events."], "weaknesses": ["No actual fire or life-safety event occurred; the threat is purely to the reliability of the monitoring system."]}, {"id": "A2", "description": "Covert Access Attempt Detected via Lock State Flip", "threat_type": "Physical Security Breach", "evidence": ["Structured signals report exactly 1 'lock_state_flips'.", "Chunk C04 shows `front_door_lock | Event: LockOperation(LockOperationType=0...)` followed immediately by `DoorLock.LockState = 1`. In many systems, Type 0 can be 'Unlock' or 'Flip', and State 1 often means 'Locked' or 'Unlocked' depending on convention. If the resident was already inside (high occupancy until 23:11), a sudden lock operation could indicate a tamper attempt or unauthorized re-locking/unlocking sequence.", "The timing (23:11) coincides with lights going off and the user potentially leaving, making a forced lock/unlock sequence suspicious."], "weaknesses": ["The log entry includes `OperationSource=Auto`, which suggests it might be a scheduled routine or automated response to the door opening, reducing the likelihood of manual intrusion.", "Without knowing the definition of LockState 0 vs 1, we cannot confirm if this represents a breach or a normal cycle."]}], "most_discriminative_evidence": ["The universal presence of temperature values in the range of 2100-2399 across all sensors, which mathematically correspond to ~21-24°C when divided by 100, strongly points to a systemic data formatting error rather than a physical phenomenon.", "The correlation between the 'Alarmish' status in the Triage Output and the temperature data confirms that the anomaly is being actively detected by the security logic, likely due to out-of-bounds numerical values triggering threshold breaches."], "missing_information": ["Definition of LockState values (0 and 1) and LockOperationType 0 to determine if the lock flip represents a breach or a routine action.", "The source code or configuration of the temperature sensor driver to verify the missing decimal point or unit conversion logic.", "Historical logs to see if this scaling error started recently or has been present since installation."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C05\"],\n  \"missing_checks\": [\n    \"Verify the specific definition of LockState (0 vs 1) and LockOperationType to confirm if the single flip at 23:11 is anomalous or routine.\",\n    \"Cross-reference historical logs to determine if the temperature scaling error (values * 100) is a new occurrence or long-standing baseline behavior.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identifies the temperature data anomaly (scaling error) as the primary issue. However, evidence is insufficient regarding the 'Lock State Flip' mentioned in Hypothesis A2. The Investigator notes ambiguity about whether this was an automated action or a breach; without checking Chunk C05 (which may contain the immediate aftermath or context around 23:11-23:15) or system configuration docs, this cannot be ruled in/out.\",\n    \"The Triage output mentions chunks C00-C04, but only 5 chunks were provided in the Available Chunk IDs list. Since the query covers a 6-hour window and we have inspected up to C04, checking C05 is necessary to ensure no anomalies occurred after the last inspected chunk before the end of the window.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C05"], "missing_checks": ["Verify the specific definition of LockState (0 vs 1) and LockOperationType to confirm if the single flip at 23:11 is anomalous or routine.", "Cross-reference historical logs to determine if the temperature scaling error (values * 100) is a new occurrence or long-standing baseline behavior."], "supervisor_notes": ["The analysis correctly identifies the temperature data anomaly (scaling error) as the primary issue. However, evidence is insufficient regarding the 'Lock State Flip' mentioned in Hypothesis A2. The Investigator notes ambiguity about whether this was an automated action or a breach; without checking Chunk C05 (which may contain the immediate aftermath or context around 23:11-23:15) or system configuration docs, this cannot be ruled in/out.", "The Triage output mentions chunks C00-C04, but only 5 chunks were provided in the Available Chunk IDs list. Since the query covers a 6-hour window and we have inspected up to C04, checking C05 is necessary to ensure no anomalies occurred after the last inspected chunk before the end of the window."]}, "preview_triage_prompt": "## Query\n以下是过去 6 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Layout\nLayout: 一室一厅 (Studio/1BR)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅台灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 147,\n    \"bedroom\": 147,\n    \"kitchen\": 78,\n    \"bathroom\": 12,\n    \"entrance\": 3\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 220,\n    \"Occupancy\": 156,\n    \"OnOff\": 5,\n    \"StateValue\": 2,\n    \"OperationalState\": 1,\n    \"CurrentPositionLiftPercent100ths\": 1,\n    \"LockState\": 1\n  },\n  \"lock_state_flips\": 1,\n  \"occupancy_events\": 156,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-20T17:55:00\",\n    \"end_ts\": \"2026-06-20T19:05:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 29,\n      \"bedroom\": 29,\n      \"kitchen\": 19,\n      \"bathroom\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"bedroom_occupancy\",\n      \"living_room_occupancy\",\n      \"bathroom_occupancy\"\n    ],\n    \"alarmish_count\": 31,\n    \"preview_lines\": [\n      \"[2026-06-20T17:55:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2324\",\n      \"[2026-06-20T17:55:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2227\",\n      \"[2026-06-20T17:55:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2319\",\n      \"[2026-06-20T17:58:00] bedroom_occupancy | OccupancySensing.Occupancy = 1\",\n      \"[2026-06-20T17:59:00] living_room_occupancy | OccupancySensing.Occupancy = 1\",\n      \"[2026-06-20T18:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2327\",\n      \"[2026-06-20T18:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2227\",\n      \"[2026-06-20T18:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2323\",\n      \"[2026-06-20T18:02:57] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n  ", "preview_verifier_prompt": "## Query\n以下是过去 6 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Triage\n{\n  \"latent_task_profile\": \"single-event-safety | composite-safety\",\n  \"focus_rooms\": [\"living_room\", \"bedroom\"],\n  \"focus_devices\": [\"living_room_temp_sensor\", \"bedroom_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\"],\n  \"suspected_patterns\": [\n    \"Temperature values are scaled by a factor of 10 (e.g., 23.24°C reported as 2324), indicating a potential sensor calibration or data transmission issue.\",\n    \"High frequency of temperature readings from living room and bedroom sensors relative to occupancy events suggests either continuous logging errors or anomalous sensor behavior.\",\n    \"Consistent 'alarmish' counts across chunks despite no explicit alarm triggers in previews, suggesting the system is flagging the data anomalies mentioned above.\"\n  ],\n  \"why_these_chunks\": \"All chunks (C00-C04) must be inspected because the temperature anomaly appears consistently across the entire 6-hour window. The pattern of high-frequency temperature logs with suspiciously precise decimal-like integer values (ending in even numbers) persists regardless of time of day or room activity, indicating a systemic sensor/logic error rather than a transient event.\"\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Systematic Data Scaling/Transmission Error\",\n      \"evidence\": [\"All temperature values are integers ending in even digits (e.g., 2324, 2227) consistent with a Celsius * 100 scaling factor.\", \"Values show gradual cooling trends over time (23xx -> 22xx -> 21xx), which is physically plausible for an unoccupied or cooling home at night.\", \"The pattern persists across all rooms and sensors simultaneously, suggesting a central data processing pipeline issue rather than individual sensor failure.\"],\n      \"weaknesses\": [\"Does not explain the specific anomaly of 'Alarm' flags if the system expects raw decimals.\", \"Does not account for the sudden lock state flip without explicit user interaction logs.\"]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"Standard Residential Evening Routine\",\n      \"evidence\": [\"High occupancy counts (156 events) indicate residents were present.\", \"Kitchen appliances (cooker off, dishwasher on) suggest meal preparation/cleanup.\", \"Lights turned off and front door locked at 23:11 indicates residents leaving the house.\"],\n      \"weaknesses\": [\"Fails to address the illogical format of the temperature readings.\", \"Cannot e"}}
{"episode_id": "SQ3_FP_D_0620", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq3\\SQ3_FP_D_0620.json", "metadata": {"sq_type": "SQ3", "sq_name": "行为序列分析", "variant": "FP", "layout_id": "D", "layout_name": "独居老人 (Elderly Living Alone)", "profile_id": "elderly_living_alone", "base_date": "2026-06-12T00:00:00", "seed": 20261249, "scenario_id": "EL-03", "total_events": 1852, "anomaly_events_count": 4}, "ground_truth": {"scenario_id": "EL-03-FP", "scenario_name": "EL-03-FP: 老人在旁边慢慢做饭", "category": "elderly_specific", "is_anomaly": false, "threat_type": "none", "key_difference": "虽然老人短暂离开了厨房，但5分钟后回来检查，不是忘了关火", "difficulty_score": 10, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 2, "D5_fp_similarity": 2}, "target_room": "kitchen", "injection_time": "2026-06-12T14:33:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"The data indicates a critical sensor malfunction causing nonsensical temperature readings (2100-2500+) and phantom occupancy signals, rather than a physical safety threat or intrusion.\",\n  \"reasoning\": [\n      \"Temperature values are physically impossible for ambient indoor environments (ranging from ~2177 to ~2543), indicating a unit conversion error (likely reporting millikelvin instead of Kelvin) or total sensor failure, as no heat source could generate such temperatures without destroying the house instantly.\",\n      \"Occupancy sensors report '1' (occupied) for extended periods while lights remain off and appliance usage is minimal or non-existent, which contradicts normal human behavior patterns (e.g., sleeping rooms occupied at 00:00 with lights off, kitchen occupied before stove activation).\",\n      \"The sequence of events (manual lock/unlock followed by immediate auto-lock and entrance motion spikes) appears to be a logical response to the system's erroneous state (interpreting noise or drift as presence) rather than evidence of an external intruder.\"\n  ],\n  \"key_evidence\": [\n      \"Temperature readings starting at 2276 at 00:00 and climbing steadily to over 2500 throughout the day, despite all reported occupancy being zero until 05:37.\",\n      \"Stove activation occurred at 06:01, yet temperatures had already exceeded 2400 three hours prior, ruling out cooking as the cause of the heat spike.\",\n      \"Kitchen sensor returned 'None' at 06:02 and 06:33, confirming intermittent hardware connectivity issues typical of sensor failure.\"\n  ],\n  \"recommended_actions\": [\n      \"Immediately replace or recalibrate the temperature sensors in all affected rooms (Living Room, Bedroom, Kitchen).\",\n      \"Review and update sensor configuration to ensure correct unit reporting (Celsius vs. Kelvin) or disable affected sensors if calibration is impossible.\",\n      \"Monitor logs for false-positive occupancy triggers that may lead to unnecessary security alerts or automated responses.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "The data indicates a critical sensor malfunction causing nonsensical temperature readings (2100-2500+) and phantom occupancy signals, rather than a physical safety threat or intrusion.", "reasoning": ["Temperature values are physically impossible for ambient indoor environments (ranging from ~2177 to ~2543), indicating a unit conversion error (likely reporting millikelvin instead of Kelvin) or total sensor failure, as no heat source could generate such temperatures without destroying the house instantly.", "Occupancy sensors report '1' (occupied) for extended periods while lights remain off and appliance usage is minimal or non-existent, which contradicts normal human behavior patterns (e.g., sleeping rooms occupied at 00:00 with lights off, kitchen occupied before stove activation).", "The sequence of events (manual lock/unlock followed by immediate auto-lock and entrance motion spikes) appears to be a logical response to the system's erroneous state (interpreting noise or drift as presence) rather than evidence of an external intruder."], "key_evidence": ["Temperature readings starting at 2276 at 00:00 and climbing steadily to over 2500 throughout the day, despite all reported occupancy being zero until 05:37.", "Stove activation occurred at 06:01, yet temperatures had already exceeded 2400 three hours prior, ruling out cooking as the cause of the heat spike.", "Kitchen sensor returned 'None' at 06:02 and 06:33, confirming intermittent hardware connectivity issues typical of sensor failure."], "recommended_actions": ["Immediately replace or recalibrate the temperature sensors in all affected rooms (Living Room, Bedroom, Kitchen).", "Review and update sensor configuration to ensure correct unit reporting (Celsius vs. Kelvin) or disable affected sensors if calibration is impossible.", "Monitor logs for false-positive occupancy triggers that may lead to unnecessary security alerts or automated responses."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 68.63926267623901, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1852, "chunk_count": 24, "signals": {"room_activity": {"living_room": 497, "bedroom": 529, "kitchen": 538, "bathroom": 57, "entrance": 231}, "attribute_frequency": {"Occupancy": 943, "MeasuredValue": 870, "OnOff": 22, "CurrentPositionLiftPercent100ths": 4, "LockState": 4, "StateValue": 4, "CurrentLevel": 1}, "lock_state_flips": 4, "occupancy_events": 943, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"bedroom\", \"living_room\"],\n  \"focus_devices\": [\"temperature_sensor\", \"occupancy_sensor\", \"door_lock\", \"contact_sensor\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\", \"C05\"],\n  \"suspected_patterns\": [\n    \"Continuous high-temperature readings exceeding normal ambient ranges (22°C -> 25°C+)\",\n    \"Sustained occupancy with no apparent activity variation or sleep cycles\",\n    \"Frequent door lock/unlock events without corresponding entry/exit occupancy patterns\"\n  ],\n  \"why_these_chunks\": [\n    \"C00-C03: Show a clear, progressive temperature spike across all rooms starting early morning, deviating from typical environmental baselines.\",\n    \"C04-C05: Introduce critical state changes including stove interaction, frequent entrance motion, and manual lock operations that do not align with the sustained internal occupancy signal.\",\n    \"Combined with the user profile 'Elderly Living Alone', these signals suggest either a device malfunction (sensor drift) or a potential safety incident (e.g., heat exposure, unauthorized access simulation).\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "bedroom", "living_room"], "focus_devices": ["temperature_sensor", "occupancy_sensor", "door_lock", "contact_sensor"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04", "C05"], "suspected_patterns": ["Continuous high-temperature readings exceeding normal ambient ranges (22°C -> 25°C+)", "Sustained occupancy with no apparent activity variation or sleep cycles", "Frequent door lock/unlock events without corresponding entry/exit occupancy patterns"], "why_these_chunks": ["C00-C03: Show a clear, progressive temperature spike across all rooms starting early morning, deviating from typical environmental baselines.", "C04-C05: Introduce critical state changes including stove interaction, frequent entrance motion, and manual lock operations that do not align with the sustained internal occupancy signal.", "Combined with the user profile 'Elderly Living Alone', these signals suggest either a device malfunction (sensor drift) or a potential safety incident (e.g., heat exposure, unauthorized access simulation)."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Sensor Malfunction/Calibration Drift causing falsely high temperature readings and phantom occupancy.\",\n      \"evidence\": [\n        \"Temperature values start at ~22 (00:00) but rapidly climb to >2500 without any recorded appliance activation until 06:01.\",\n        \"Occupancy sensors report '1' in bedrooms and kitchen during times where lights are off or only just turning on, suggesting false triggers or sensor cross-talk.\",\n        \"The kitchen sensor returns 'None' multiple times (06:02, 06:33), indicating intermittent connectivity issues typical of hardware failure.\"\n      ],\n      \"weaknesses\": [\n        \"Does not explain the specific sequence of manual lock/unlock events occurring while the house is reported as occupied by a single person who appears unaware of the heat spike.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Unauthorized Intruder Entry and Potential Heat Weaponization/Sabotage.\",\n      \"threat_type\": \"Burglary / Safety Hazard\",\n      \"evidence\": [\n        \"Door Lock State flips to Unlocked (State=2) at 07:00:03 with Manual source, followed immediately by Entrance Occupancy = 1 at 07:00:06, while the resident's bedroom occupancy was previously stable (1).\",\n        \"Rapid, unexplained rise in ambient temperature (from 22°C to 2500+ units) starting early morning correlates with no internal heat source activation until much later (06:01 stove turn-on).\",\n        \"Intruder enters at 07:00, interacts with entrance motion repeatedly (07:05, 07:10, 07:15, 07:20), and leaves via Auto-lock at 07:00:13, yet the system still flags interior occupancy, implying a struggle or hidden presence.\",\n        \"Stove activated at 06:01 (before intruder entry time window suggests premeditation or misinterpretation of timeline) but massive heat persists long after stove turns off at 06:32.\"\n      ],\n      \"weaknesses\": [\n        \"The sheer magnitude of temperature readings (2500+) could be a unit error rather than physical reality, weakening the 'heat weaponization' aspect unless the sensor scale is confirmed broken.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Resident Disoriented due to Extreme Heat Exposure leading to Erratic Behavior.\",\n      \"threat_type\": \"Health & Safety\",\n      \"evidence\": [\n        \"Temperature spikes continuously from 00:00 to 07:22 despite all rooms being empty for the first half of this period.\",\n        \"At 07:00, the door is manually unlocked and re-locked quickly; if the resident were confused by extreme heat, they might attempt to leave or check outside conditions.\",\n        \"The pattern of frequent entrance motion events (07:05 onwards) matches someone pacing or checking the perimeter due to distress.\"\n      ],\n      \"weaknesses\": [\n        \"If the resident was already inside, why did the front door contact show 'False' (open) at 07:00:05? This implies an exit or entry event that contradicts a purely internal heat exposure scenario.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"Timestamp 07:00:03 - 07:00:13: A manual lock unlock occurs while the system reports interior occupancy, followed by immediate auto-locking. Combined with the entrance sensor triggering shortly after, this strongly points to an external actor entering or exiting, rather than internal movement.\",\n    \"Temperature Data vs. Appliance Log: Temperature exceeds 2400 units starting at 03:30, but the kitchen stove (primary heat source) is not turned ON until 06:01. The heat precedes the usage by nearly 3 hours, ruling out normal cooking as the cause.\"\n  ],\n  \"missing_information\": [\n    \"Historical baseline temperature data to confirm if the '22' reading was truly normal or if the sensor has been drifting for days.\",\n    \"Video footage or audio logs from the entrance area between 07:00 and 07:05 to visualize the interaction at the door.\",\n    \"Confirmation of the temperature sensor's unit of measurement (Celsius vs. scaled integer) to validate the severity of the heat reading.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Sensor Malfunction/Calibration Drift causing falsely high temperature readings and phantom occupancy.", "evidence": ["Temperature values start at ~22 (00:00) but rapidly climb to >2500 without any recorded appliance activation until 06:01.", "Occupancy sensors report '1' in bedrooms and kitchen during times where lights are off or only just turning on, suggesting false triggers or sensor cross-talk.", "The kitchen sensor returns 'None' multiple times (06:02, 06:33), indicating intermittent connectivity issues typical of hardware failure."], "weaknesses": ["Does not explain the specific sequence of manual lock/unlock events occurring while the house is reported as occupied by a single person who appears unaware of the heat spike."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Unauthorized Intruder Entry and Potential Heat Weaponization/Sabotage.", "threat_type": "Burglary / Safety Hazard", "evidence": ["Door Lock State flips to Unlocked (State=2) at 07:00:03 with Manual source, followed immediately by Entrance Occupancy = 1 at 07:00:06, while the resident's bedroom occupancy was previously stable (1).", "Rapid, unexplained rise in ambient temperature (from 22°C to 2500+ units) starting early morning correlates with no internal heat source activation until much later (06:01 stove turn-on).", "Intruder enters at 07:00, interacts with entrance motion repeatedly (07:05, 07:10, 07:15, 07:20), and leaves via Auto-lock at 07:00:13, yet the system still flags interior occupancy, implying a struggle or hidden presence.", "Stove activated at 06:01 (before intruder entry time window suggests premeditation or misinterpretation of timeline) but massive heat persists long after stove turns off at 06:32."], "weaknesses": ["The sheer magnitude of temperature readings (2500+) could be a unit error rather than physical reality, weakening the 'heat weaponization' aspect unless the sensor scale is confirmed broken."]}, {"id": "A2", "description": "Resident Disoriented due to Extreme Heat Exposure leading to Erratic Behavior.", "threat_type": "Health & Safety", "evidence": ["Temperature spikes continuously from 00:00 to 07:22 despite all rooms being empty for the first half of this period.", "At 07:00, the door is manually unlocked and re-locked quickly; if the resident were confused by extreme heat, they might attempt to leave or check outside conditions.", "The pattern of frequent entrance motion events (07:05 onwards) matches someone pacing or checking the perimeter due to distress."], "weaknesses": ["If the resident was already inside, why did the front door contact show 'False' (open) at 07:00:05? This implies an exit or entry event that contradicts a purely internal heat exposure scenario."]}], "most_discriminative_evidence": ["Timestamp 07:00:03 - 07:00:13: A manual lock unlock occurs while the system reports interior occupancy, followed by immediate auto-locking. Combined with the entrance sensor triggering shortly after, this strongly points to an external actor entering or exiting, rather than internal movement.", "Temperature Data vs. Appliance Log: Temperature exceeds 2400 units starting at 03:30, but the kitchen stove (primary heat source) is not turned ON until 06:01. The heat precedes the usage by nearly 3 hours, ruling out normal cooking as the cause."], "missing_information": ["Historical baseline temperature data to confirm if the '22' reading was truly normal or if the sensor has been drifting for days.", "Video footage or audio logs from the entrance area between 07:00 and 07:05 to visualize the interaction at the door.", "Confirmation of the temperature sensor's unit of measurement (Celsius vs. scaled integer) to validate the severity of the heat reading."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C06\", \"C07\"],\n  \"missing_checks\": [\n    \"Verify if '2500' temperature readings are a data logging error (unit mismatch) or actual sensor failure.\",\n    \"Cross-reference door lock events with specific timestamps to confirm the sequence of unlock->occupancy spike->relock.\",\n    \"Check stove appliance logs for exact on/off states and duration relative to the temperature anomaly.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis is currently drifting into highly speculative scenarios ('heat weaponization', 'sabotage') based on a single outlier data point (2500 units) which may simply be a calibration drift or unit error.\",\n    \"The evidence relies heavily on C00-C05 but ignores the full 24-hour context. Chunks C06 and C07 are needed to establish the baseline behavior before the suspected anomaly window and to see if the pattern repeats or resolves later in the day.\",\n    \"Without confirming the nature of the temperature spike (malfunction vs real event), the distinction between Hypothesis N1 (Malfunction) and A1/A2 (Intruder/Health) remains ambiguous. Further chunks are required to validate the timeline of the stove activation versus the temperature rise.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C06", "C07"], "missing_checks": ["Verify if '2500' temperature readings are a data logging error (unit mismatch) or actual sensor failure.", "Cross-reference door lock events with specific timestamps to confirm the sequence of unlock->occupancy spike->relock.", "Check stove appliance logs for exact on/off states and duration relative to the temperature anomaly."], "supervisor_notes": ["The analysis is currently drifting into highly speculative scenarios ('heat weaponization', 'sabotage') based on a single outlier data point (2500 units) which may simply be a calibration drift or unit error.", "The evidence relies heavily on C00-C05 but ignores the full 24-hour context. Chunks C06 and C07 are needed to establish the baseline behavior before the suspected anomaly window and to see if the pattern repeats or resolves later in the day.", "Without confirming the nature of the temperature spike (malfunction vs real event), the distinction between Hypothesis N1 (Malfunction) and A1/A2 (Intruder/Health) remains ambiguous. Further chunks are required to validate the timeline of the stove activation versus the temperature rise."]}, "preview_triage_prompt": "## Query\n以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Layout\nLayout: 独居老人 (Elderly Living Alone)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>, 床头灯<onoff_light>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房运动传感器<occupancy_sensor>\n- living_room: 客厅温度传感器<temperature_sensor>, 客厅灯<dimmable_light>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 497,\n    \"bedroom\": 529,\n    \"kitchen\": 538,\n    \"bathroom\": 57,\n    \"entrance\": 231\n  },\n  \"attribute_frequency\": {\n    \"Occupancy\": 943,\n    \"MeasuredValue\": 870,\n    \"OnOff\": 22,\n    \"CurrentPositionLiftPercent100ths\": 4,\n    \"LockState\": 4,\n    \"StateValue\": 4,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 943,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-12T00:00:00\",\n    \"end_ts\": \"2026-06-12T01:35:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 24,\n      \"bedroom\": 24,\n      \"kitchen\": 24,\n      \"bathroom\": 4,\n      \"entrance\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"kitchen_occupancy\"\n    ],\n    \"alarmish_count\": 20,\n    \"preview_lines\": [\n      \"[2026-06-12T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2276\",\n      \"[2026-06-12T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2177\",\n      \"[2026-06-12T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2269\",\n      \"[2026-06-12T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-12T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-12T00:00:00] kitchen_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-12T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-12T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-12T00:05:00] living_", "preview_verifier_prompt": "## Query\n以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"bedroom\", \"living_room\"],\n  \"focus_devices\": [\"temperature_sensor\", \"occupancy_sensor\", \"door_lock\", \"contact_sensor\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\", \"C05\"],\n  \"suspected_patterns\": [\n    \"Continuous high-temperature readings exceeding normal ambient ranges (22°C -> 25°C+)\",\n    \"Sustained occupancy with no apparent activity variation or sleep cycles\",\n    \"Frequent door lock/unlock events without corresponding entry/exit occupancy patterns\"\n  ],\n  \"why_these_chunks\": [\n    \"C00-C03: Show a clear, progressive temperature spike across all rooms starting early morning, deviating from typical environmental baselines.\",\n    \"C04-C05: Introduce critical state changes including stove interaction, frequent entrance motion, and manual lock operations that do not align with the sustained internal occupancy signal.\",\n    \"Combined with the user profile 'Elderly Living Alone', these signals suggest either a device malfunction (sensor drift) or a potential safety incident (e.g., heat exposure, unauthorized access simulation).\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Sensor Malfunction/Calibration Drift causing falsely high temperature readings and phantom occupancy.\",\n      \"evidence\": [\n        \"Temperature values start at ~22 (00:00) but rapidly climb to >2500 without any recorded appliance activation until 06:01.\",\n        \"Occupancy sensors report '1' in bedrooms and kitchen during times where lights are off or only just turning on, suggesting false triggers or sensor cross-talk.\",\n        \"The kitchen sensor returns 'None' multiple times (06:02, 06:33), indicating intermittent connectivity issues typical of hardware failure.\"\n      ],\n      \"weaknesses\": [\n        \"Does not explain the specific sequence of manual lock/unlock events occurring while the house is reported as occupied by a single person who appears unaware of the heat spike.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Unauthorized Intruder Entry and Potential Heat Weaponization/Sabotage.\",\n      \"threat_type\": \"Burglary / Safety Hazard\",\n      \"evidence\": [\n        \"Door Lock State flips to Unlocked (State=2) at 07:00:03 with Manual source, followed immediately by Entrance Occupancy = 1 at 07:00:06, while the resident's bedroom occupan"}}
{"episode_id": "SQ3_FP_D_0565", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq3\\SQ3_FP_D_0565.json", "metadata": {"sq_type": "SQ3", "sq_name": "行为序列分析", "variant": "FP", "layout_id": "D", "layout_name": "独居老人 (Elderly Living Alone)", "profile_id": "elderly_living_alone", "base_date": "2026-06-15T00:00:00", "seed": 20261194, "scenario_id": "EL-07", "total_events": 1857, "anomaly_events_count": 4}, "ground_truth": {"scenario_id": "EL-07-FP", "scenario_name": "EL-07-FP: 老人散步时间稍长但正常回家", "category": "elderly_specific", "is_anomaly": false, "threat_type": "none", "key_difference": "虽然比平时晚了30分钟回来，但最终正常解锁回家并有后续活动", "difficulty_score": 11, "difficulty_level": 3, "difficulty_label": "L3_composite_reasoning", "difficulty_dimensions": {"D1_evidence_count": 1, "D2_signal_directness": 3, "D3_cross_device": 1, "D4_temporal_span": 3, "D5_fp_similarity": 3}, "target_room": "bathroom", "injection_time": "2026-06-15T12:50:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_drift\",\n  \"threat_description\": \"The temperature sensors are exhibiting a systematic calibration failure reporting raw integer values that drift upward over time, creating a false reading of extreme heat while simultaneously losing telemetry during active cooking events.\",\n  \"reasoning\": [\n    \"All temperature sensors across the house report values between ~2160 and ~2550, which is physically impossible for ambient room temperature in standard units (Celsius/Fahrenheit), indicating a firmware unit conversion error or raw ADC count leak.\",\n    \"The integer values show a consistent monotonic increase throughout the entire 24-hour log (e.g., kitchen rising from 2264 to 2553) without corresponding environmental changes or HVAC cycles, confirming a systemic software bug rather than external overheating.\",\n    \"Critical safety blind spots were identified where `kitchen_temp_sensor` returned `None` at T06:10:03 and T06:29:00, which coincided exactly with the activation and deactivation of the `kitchen_cook_surface`, meaning the system failed to monitor high-risk thermal events due to intermittent disconnection or power fluctuation.\"\n  ],\n  \"key_evidence\": [\n    \"Monotonic rise of erroneous integers: Kitchen sensor increased from 2264 (00:00) to 2553 (09:17) despite no occupancy correlation.\",\n    \"Temporal correlation of data loss: Sensor returned 'None' precisely when the cook surface was active (T06:09:33) and immediately after (T06:28:00).\",\n    \"Universal pattern: The same non-physical value range appears in living_room, bedroom, and kitchen sensors simultaneously, ruling out isolated hardware damage.\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately disable the faulty temperature sensors in the smart home app to prevent incorrect fire alerts based on raw integer data.\",\n    \"Contact the device manufacturer to apply a firmware update addressing the missing unit conversion logic and investigate the cause of intermittent sensor dropouts during high-load periods.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_drift", "threat_description": "The temperature sensors are exhibiting a systematic calibration failure reporting raw integer values that drift upward over time, creating a false reading of extreme heat while simultaneously losing telemetry during active cooking events.", "reasoning": ["All temperature sensors across the house report values between ~2160 and ~2550, which is physically impossible for ambient room temperature in standard units (Celsius/Fahrenheit), indicating a firmware unit conversion error or raw ADC count leak.", "The integer values show a consistent monotonic increase throughout the entire 24-hour log (e.g., kitchen rising from 2264 to 2553) without corresponding environmental changes or HVAC cycles, confirming a systemic software bug rather than external overheating.", "Critical safety blind spots were identified where `kitchen_temp_sensor` returned `None` at T06:10:03 and T06:29:00, which coincided exactly with the activation and deactivation of the `kitchen_cook_surface`, meaning the system failed to monitor high-risk thermal events due to intermittent disconnection or power fluctuation."], "key_evidence": ["Monotonic rise of erroneous integers: Kitchen sensor increased from 2264 (00:00) to 2553 (09:17) despite no occupancy correlation.", "Temporal correlation of data loss: Sensor returned 'None' precisely when the cook surface was active (T06:09:33) and immediately after (T06:28:00).", "Universal pattern: The same non-physical value range appears in living_room, bedroom, and kitchen sensors simultaneously, ruling out isolated hardware damage."], "recommended_actions": ["Immediately disable the faulty temperature sensors in the smart home app to prevent incorrect fire alerts based on raw integer data.", "Contact the device manufacturer to apply a firmware update addressing the missing unit conversion logic and investigate the cause of intermittent sensor dropouts during high-load periods."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 71.68551135063171, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1857, "chunk_count": 24, "signals": {"room_activity": {"living_room": 499, "bedroom": 530, "kitchen": 532, "bathroom": 64, "entrance": 232}, "attribute_frequency": {"Occupancy": 947, "MeasuredValue": 870, "OnOff": 21, "CurrentPositionLiftPercent100ths": 4, "LockState": 4, "StateValue": 4, "CurrentLevel": 1}, "lock_state_flips": 4, "occupancy_events": 947, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"single-event-safety | composite-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"kitchen_cook_surface\", \"living_room_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\", \"C16\"],\n  \"suspected_patterns\": [\n    \"Sensor calibration failure: Temperature readings are in raw integer format (e.g., 2279, 2504) instead of Celsius/Fahrenheit, suggesting a firmware or unit conversion error.\",\n    \"Data loss event: 'MeasuredValue' becomes 'None' during active cooking periods, indicating sensor disconnection or power fluctuation.\",\n    \"Thermal runaway risk: Despite 'None' readings, the reported integer values continue to trend upwards from ~2279 to ~2550 over several hours, implying unmonitored overheating if the sensor is functional but misreported.\"\n  ],\n  \"why_these_chunks\": [\n    \"C00-C03 show the initial onset of anomalous temperature values (2279-2459) with no occupancy correlation, establishing the baseline anomaly.\",\n    \"C04 and C16 contain critical safety events where `kitchen_cook_surface` activity coincides with `kitchen_temp_sensor` returning `None`, creating a high-risk blind spot for fire detection.\",\n    \"C01 and C02 demonstrate the continuous upward drift of the erroneous temperature values, confirming a systemic issue rather than a transient glitch.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "single-event-safety | composite-safety", "focus_rooms": ["kitchen"], "focus_devices": ["kitchen_temp_sensor", "kitchen_cook_surface", "living_room_temp_sensor"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04", "C16"], "suspected_patterns": ["Sensor calibration failure: Temperature readings are in raw integer format (e.g., 2279, 2504) instead of Celsius/Fahrenheit, suggesting a firmware or unit conversion error.", "Data loss event: 'MeasuredValue' becomes 'None' during active cooking periods, indicating sensor disconnection or power fluctuation.", "Thermal runaway risk: Despite 'None' readings, the reported integer values continue to trend upwards from ~2279 to ~2550 over several hours, implying unmonitored overheating if the sensor is functional but misreported."], "why_these_chunks": ["C00-C03 show the initial onset of anomalous temperature values (2279-2459) with no occupancy correlation, establishing the baseline anomaly.", "C04 and C16 contain critical safety events where `kitchen_cook_surface` activity coincides with `kitchen_temp_sensor` returning `None`, creating a high-risk blind spot for fire detection.", "C01 and C02 demonstrate the continuous upward drift of the erroneous temperature values, confirming a systemic issue rather than a transient glitch."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Systematic Sensor Calibration Drift: The temperature sensors are functioning but suffering from a firmware bug where the unit conversion (e.g., Kelvin to Celsius) is missing or incorrect, causing raw integer values that linearly drift over time.\",\n      \"evidence\": [\"All sensors report values between ~2160 and ~2500 consistently across C00-C04.\", \"Values increase monotonically in all rooms as ambient temperature naturally rises during the day (morning to afternoon).\", \"The pattern of increase is uniform across living_room, bedroom, and kitchen, suggesting a global system issue rather than isolated device failure.\"],\n      \"weaknesses\": [\"This hypothesis fails to explain the sudden appearance of `None` values at T06:10:03 and T06:29:00 while other readings remain valid integers.\", \"It does not account for the correlation between `None` readings and specific high-heat events (cook surface activation).\"],\n      \"threat_type\": \"Low\"\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Sensor Communication Failure with Data Masking: The kitchen temperature sensor experiences intermittent disconnection or power loss. When the sensor is offline, it returns `None`. The system logic erroneously continues reporting stale or extrapolated integer data from another source (or a backup sensor mislabeled as 'kitchen') when the primary is down, creating a false sense of security regarding actual temperatures.\",\n      \"threat_type\": \"Safety/Fire Detection Blind Spot\",\n      \"evidence\": [\"At T06:09:33, `kitchen_cook_surface` turns ON. Shortly after, at T06:10:03, `kitchen_temp_sensor` reports `None`, yet a valid integer `2485` is reported immediately after (likely from a different physical sensor or cached value).\", \"At T06:28:00, `kitchen_cook_surface` turns OFF. Immediately at T06:29:00, `kitchen_temp_sensor` reports `None` again, followed by a jump back to integer `2487`.\", \"The integer values continue their upward drift even when the sensor explicitly reports `None`, implying the 'integer' stream is decoupled from the actual cooking surface's thermal state.\", \"High-risk window identified: T06:09:33 to T06:14:03 and T06:28:00 to T06:30:00 where cook surface was active/just deactivated but temperature telemetry was lost.\"],\n      \"weaknesses\": [\"No direct evidence confirms the source of the integer values during the `None` gaps; they could theoretically be valid readings from a separate, unaffected sensor if dual sensors exist.\", \"Occupancy logs show people present in the kitchen during these times, increasing the likelihood of unmonitored hazards.\"],\n      \"threat_type\": \"High\"\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Thermal Runaway / Overheating Event: The kitchen environment is genuinely overheating due to equipment failure (e.g., oven malfunction), and the sensor calibration drift (Hypothesis N1) combined with data loss is masking the severity of the rise.\",\n      \"threat_type\": \"Fire Hazard\",\n      \"evidence\": [\"Raw values reach ~2500 (if interpreted as Kelvin, this is >2200°C, which is impossible for a room; if Fahrenheit, ~1300°C, also impossible; if raw millivolts or arbitrary units, it indicates extreme deviation).\", \"Even assuming the 'drift' is just bad calibration, the absolute magnitude suggests the sensor is saturated or measuring something completely wrong.\", \"The `None` events coincide with high thermal load periods (cooking), suggesting the sensor may be physically damaged or melting off its mounting point.\"],\n      \"weaknesses\": [\"Without knowing the original unit scale, it is hard to definitively claim 'runaway' without the `None` gap explanation.\", \"Other rooms show similar drift patterns, making an isolated kitchen hardware failure less likely unless there is a shared power/grid issue.\"],\n      \"threat_type\": \"Medium-High\"\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The temporal correlation between `kitchen_cook_surface` On/Off events and the exact timestamps where `kitchen_temp_sensor` returns `None` (T06:10:03, T06:29:00).\",\n    \"The persistence of integer temperature values (e.g., 2485, 2487) immediately following `None` states, indicating a fallback mechanism or multi-sensor redundancy where one sensor failed silently.\",\n    \"The monotonic increase of integer values throughout the log (C00-C04) despite no user interaction, contrasting with typical HVAC cycles.\"\n  ],\n  \"missing_information\": [\n    \"The defined unit of measurement for `TemperatureMeasurement.MeasuredValue` (e.g., Celsius, Fahrenheit, Kelvin, mV, or Raw ADC count).\",\n    \"Hardware specifications: Are there multiple temperature sensors per room? If so, which ID corresponds to the 'kitchen' reading when `None` occurs?\",\n    \"Power supply logs for the kitchen devices to correlate `None` events with potential brownouts.\",\n    \"Historical baseline data to determine if the integer range (2200-2500) is the normal operating range for this specific sensor model under current conditions.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Systematic Sensor Calibration Drift: The temperature sensors are functioning but suffering from a firmware bug where the unit conversion (e.g., Kelvin to Celsius) is missing or incorrect, causing raw integer values that linearly drift over time.", "evidence": ["All sensors report values between ~2160 and ~2500 consistently across C00-C04.", "Values increase monotonically in all rooms as ambient temperature naturally rises during the day (morning to afternoon).", "The pattern of increase is uniform across living_room, bedroom, and kitchen, suggesting a global system issue rather than isolated device failure."], "weaknesses": ["This hypothesis fails to explain the sudden appearance of `None` values at T06:10:03 and T06:29:00 while other readings remain valid integers.", "It does not account for the correlation between `None` readings and specific high-heat events (cook surface activation)."], "threat_type": "Low"}], "anomaly_hypotheses": [{"id": "A1", "description": "Sensor Communication Failure with Data Masking: The kitchen temperature sensor experiences intermittent disconnection or power loss. When the sensor is offline, it returns `None`. The system logic erroneously continues reporting stale or extrapolated integer data from another source (or a backup sensor mislabeled as 'kitchen') when the primary is down, creating a false sense of security regarding actual temperatures.", "threat_type": "High", "evidence": ["At T06:09:33, `kitchen_cook_surface` turns ON. Shortly after, at T06:10:03, `kitchen_temp_sensor` reports `None`, yet a valid integer `2485` is reported immediately after (likely from a different physical sensor or cached value).", "At T06:28:00, `kitchen_cook_surface` turns OFF. Immediately at T06:29:00, `kitchen_temp_sensor` reports `None` again, followed by a jump back to integer `2487`.", "The integer values continue their upward drift even when the sensor explicitly reports `None`, implying the 'integer' stream is decoupled from the actual cooking surface's thermal state.", "High-risk window identified: T06:09:33 to T06:14:03 and T06:28:00 to T06:30:00 where cook surface was active/just deactivated but temperature telemetry was lost."], "weaknesses": ["No direct evidence confirms the source of the integer values during the `None` gaps; they could theoretically be valid readings from a separate, unaffected sensor if dual sensors exist.", "Occupancy logs show people present in the kitchen during these times, increasing the likelihood of unmonitored hazards."]}, {"id": "A2", "description": "Thermal Runaway / Overheating Event: The kitchen environment is genuinely overheating due to equipment failure (e.g., oven malfunction), and the sensor calibration drift (Hypothesis N1) combined with data loss is masking the severity of the rise.", "threat_type": "Medium-High", "evidence": ["Raw values reach ~2500 (if interpreted as Kelvin, this is >2200°C, which is impossible for a room; if Fahrenheit, ~1300°C, also impossible; if raw millivolts or arbitrary units, it indicates extreme deviation).", "Even assuming the 'drift' is just bad calibration, the absolute magnitude suggests the sensor is saturated or measuring something completely wrong.", "The `None` events coincide with high thermal load periods (cooking), suggesting the sensor may be physically damaged or melting off its mounting point."], "weaknesses": ["Without knowing the original unit scale, it is hard to definitively claim 'runaway' without the `None` gap explanation.", "Other rooms show similar drift patterns, making an isolated kitchen hardware failure less likely unless there is a shared power/grid issue."]}], "most_discriminative_evidence": ["The temporal correlation between `kitchen_cook_surface` On/Off events and the exact timestamps where `kitchen_temp_sensor` returns `None` (T06:10:03, T06:29:00).", "The persistence of integer temperature values (e.g., 2485, 2487) immediately following `None` states, indicating a fallback mechanism or multi-sensor redundancy where one sensor failed silently.", "The monotonic increase of integer values throughout the log (C00-C04) despite no user interaction, contrasting with typical HVAC cycles."], "missing_information": ["The defined unit of measurement for `TemperatureMeasurement.MeasuredValue` (e.g., Celsius, Fahrenheit, Kelvin, mV, or Raw ADC count).", "Hardware specifications: Are there multiple temperature sensors per room? If so, which ID corresponds to the 'kitchen' reading when `None` occurs?", "Power supply logs for the kitchen devices to correlate `None` events with potential brownouts.", "Historical baseline data to determine if the integer range (2200-2500) is the normal operating range for this specific sensor model under current conditions."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C05\", \"C06\", \"C17\", \"C18\"],\n  \"missing_checks\": [\n    \"Verify power supply logs during T06:10:03 and T06:29:00 to confirm if 'None' readings correlate with brownouts.\",\n    \"Cross-reference occupancy data with the specific timestamps of sensor failure to assess risk exposure.\",\n    \"Check historical baseline for this specific device model to determine if 2200-2500 is a known firmware artifact or actual saturation.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identified the correlation between cooking events and sensor failures (Hypothesis A1), which is critical.\",\n    \"However, evidence is currently insufficient to rule out global system issues vs. isolated kitchen hardware. The investigator noted that other rooms show similar drift; chunks C05-C06 (likely covering mid-day/other zones) are needed to confirm if this is a universal firmware bug or localized.\",\n    \"Chunks C17-C18 should be examined to see if the pattern repeats in the evening cycle or resolves, determining if it's an intermittent glitch or sustained failure.\",\n    \"Without confirming the unit of measurement from the raw log data (which isn't explicitly visible in the summary provided by the investigator), the 'thermal runaway' claim remains speculative until verified against known sensor specs in additional context windows.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C05", "C06", "C17", "C18"], "missing_checks": ["Verify power supply logs during T06:10:03 and T06:29:00 to confirm if 'None' readings correlate with brownouts.", "Cross-reference occupancy data with the specific timestamps of sensor failure to assess risk exposure.", "Check historical baseline for this specific device model to determine if 2200-2500 is a known firmware artifact or actual saturation."], "supervisor_notes": ["The analysis correctly identified the correlation between cooking events and sensor failures (Hypothesis A1), which is critical.", "However, evidence is currently insufficient to rule out global system issues vs. isolated kitchen hardware. The investigator noted that other rooms show similar drift; chunks C05-C06 (likely covering mid-day/other zones) are needed to confirm if this is a universal firmware bug or localized.", "Chunks C17-C18 should be examined to see if the pattern repeats in the evening cycle or resolves, determining if it's an intermittent glitch or sustained failure.", "Without confirming the unit of measurement from the raw log data (which isn't explicitly visible in the summary provided by the investigator), the 'thermal runaway' claim remains speculative until verified against known sensor specs in additional context windows."]}, "preview_triage_prompt": "## Query\n以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Layout\nLayout: 独居老人 (Elderly Living Alone)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>, 床头灯<onoff_light>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房运动传感器<occupancy_sensor>\n- living_room: 客厅温度传感器<temperature_sensor>, 客厅灯<dimmable_light>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 499,\n    \"bedroom\": 530,\n    \"kitchen\": 532,\n    \"bathroom\": 64,\n    \"entrance\": 232\n  },\n  \"attribute_frequency\": {\n    \"Occupancy\": 947,\n    \"MeasuredValue\": 870,\n    \"OnOff\": 21,\n    \"CurrentPositionLiftPercent100ths\": 4,\n    \"LockState\": 4,\n    \"StateValue\": 4,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 947,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-15T00:00:00\",\n    \"end_ts\": \"2026-06-15T01:35:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 24,\n      \"bedroom\": 24,\n      \"kitchen\": 24,\n      \"bathroom\": 4,\n      \"entrance\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"kitchen_occupancy\"\n    ],\n    \"alarmish_count\": 20,\n    \"preview_lines\": [\n      \"[2026-06-15T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2279\",\n      \"[2026-06-15T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2161\",\n      \"[2026-06-15T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2264\",\n      \"[2026-06-15T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-15T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-15T00:00:00] kitchen_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-15T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-15T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-15T00:05:00] living_", "preview_verifier_prompt": "## Query\n以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Triage\n{\n  \"latent_task_profile\": \"single-event-safety | composite-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"kitchen_cook_surface\", \"living_room_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\", \"C16\"],\n  \"suspected_patterns\": [\n    \"Sensor calibration failure: Temperature readings are in raw integer format (e.g., 2279, 2504) instead of Celsius/Fahrenheit, suggesting a firmware or unit conversion error.\",\n    \"Data loss event: 'MeasuredValue' becomes 'None' during active cooking periods, indicating sensor disconnection or power fluctuation.\",\n    \"Thermal runaway risk: Despite 'None' readings, the reported integer values continue to trend upwards from ~2279 to ~2550 over several hours, implying unmonitored overheating if the sensor is functional but misreported.\"\n  ],\n  \"why_these_chunks\": [\n    \"C00-C03 show the initial onset of anomalous temperature values (2279-2459) with no occupancy correlation, establishing the baseline anomaly.\",\n    \"C04 and C16 contain critical safety events where `kitchen_cook_surface` activity coincides with `kitchen_temp_sensor` returning `None`, creating a high-risk blind spot for fire detection.\",\n    \"C01 and C02 demonstrate the continuous upward drift of the erroneous temperature values, confirming a systemic issue rather than a transient glitch.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Systematic Sensor Calibration Drift: The temperature sensors are functioning but suffering from a firmware bug where the unit conversion (e.g., Kelvin to Celsius) is missing or incorrect, causing raw integer values that linearly drift over time.\",\n      \"evidence\": [\"All sensors report values between ~2160 and ~2500 consistently across C00-C04.\", \"Values increase monotonically in all rooms as ambient temperature naturally rises during the day (morning to afternoon).\", \"The pattern of increase is uniform across living_room, bedroom, and kitchen, suggesting a global system issue rather than isolated device failure.\"],\n      \"weaknesses\": [\"This hypothesis fails to explain the sudden appearance of `None` values at T06:10:03 and T06:29:00 while other readings remain valid integers.\", \"It does not account for the correlation between `None` readings and specific high-heat events (cook surface activation).\"],\n      \"threat_type\": \"Low\"\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {"}}
{"episode_id": "SQ3_TP_A_0433", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq3\\SQ3_TP_A_0433.json", "metadata": {"sq_type": "SQ3", "sq_name": "行为序列分析", "variant": "TP", "layout_id": "A", "layout_name": "一室一厅 (Studio/1BR)", "profile_id": "young_professional", "base_date": "2026-06-17T00:00:00", "seed": 20261062, "scenario_id": "INS-05", "total_events": 1126, "anomaly_events_count": 5}, "ground_truth": {"scenario_id": "INS-05", "scenario_name": "伪装开锁（被盗/复制凭证）", "category": "intrusion", "is_anomaly": true, "threat_type": "credential_theft", "key_evidence": ["合法凭证开锁，但进入后的行为模式与住户不符", "不开灯（住户通常到家后开灯）", "进入后的移动路径和设备操作模式与住户日常习惯不一致", "本场景的难点：单看门锁事件是合法的，需要结合行为模式判断"], "expected_response": "中等可信度警报，建议住户确认是否本人操作", "difficulty_score": 13, "difficulty_level": 3, "difficulty_label": "L3_composite_reasoning", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 3, "D3_cross_device": 3, "D4_temporal_span": 2, "D5_fp_similarity": 3}, "target_room": "bedroom", "injection_time": "2026-06-17T16:07:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"System-wide sensor data corruption and calibration failure causing implausible temperature readings (e.g., 2700+) and inconsistent door lock state reporting.\",\n  \"reasoning\": [\n      \"Temperature sensors report values between 2100-2700 throughout the log, which is physically impossible for ambient room temperature in standard units; this indicates a severe sensor drift or unit conversion failure.\",\n      \"The sequence of events at 22:04 appears deterministic (Lights Off -> AC Off -> Door Contact True -> Lock Auto), mimicking a human departure routine, but the surrounding context shows no vacancy prior to this, making it highly likely an automated script reacting to faulty 'occupied' sensor noise rather than human action.\",\n      \"The front door contact reported 'True' (implying closed/locked) while bedroom occupancy was still active, a logical inconsistency that is best explained by the corrupted sensor inputs triggering erroneous automation rules rather than a physical breach.\"\n    ],\n  \"key_evidence\": [\n      \"Multiple temperature logs showing values like 2692, 2713, and 2700, indicating raw integer overflow or incorrect scaling.\",\n      \"Front door lock state changed to 'Locked' at 22:04:37 via 'Auto' source while internal bedroom occupancy was confirmed active until 22:44.\"\n    ],\n  \"recommended_actions\": [\n      \"Immediately isolate and reset all temperature sensors to clear calibration errors.\",\n      \"Review smart home automation rules for 'departure' triggers to ensure they are not executing based on noisy or misinterpreted occupancy data.\",\n      \"Verify physical status of the front door lock manually to ensure it is not stuck in a false 'locked' state due to firmware logic errors.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "System-wide sensor data corruption and calibration failure causing implausible temperature readings (e.g., 2700+) and inconsistent door lock state reporting.", "reasoning": ["Temperature sensors report values between 2100-2700 throughout the log, which is physically impossible for ambient room temperature in standard units; this indicates a severe sensor drift or unit conversion failure.", "The sequence of events at 22:04 appears deterministic (Lights Off -> AC Off -> Door Contact True -> Lock Auto), mimicking a human departure routine, but the surrounding context shows no vacancy prior to this, making it highly likely an automated script reacting to faulty 'occupied' sensor noise rather than human action.", "The front door contact reported 'True' (implying closed/locked) while bedroom occupancy was still active, a logical inconsistency that is best explained by the corrupted sensor inputs triggering erroneous automation rules rather than a physical breach."], "key_evidence": ["Multiple temperature logs showing values like 2692, 2713, and 2700, indicating raw integer overflow or incorrect scaling.", "Front door lock state changed to 'Locked' at 22:04:37 via 'Auto' source while internal bedroom occupancy was confirmed active until 22:44."], "recommended_actions": ["Immediately isolate and reset all temperature sensors to clear calibration errors.", "Review smart home automation rules for 'departure' triggers to ensure they are not executing based on noisy or misinterpreted occupancy data.", "Verify physical status of the front door lock manually to ensure it is not stuck in a false 'locked' state due to firmware logic errors."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 59.3899667263031, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 602, "chunk_count": 8, "signals": {"room_activity": {"living_room": 232, "bedroom": 183, "kitchen": 153, "bathroom": 24, "entrance": 10}, "attribute_frequency": {"MeasuredValue": 437, "Occupancy": 139, "OnOff": 13, "StateValue": 4, "LockState": 2, "SystemMode": 1, "OperationalState": 1, "CurrentPositionLiftPercent100ths": 1, "CurrentLevel": 1}, "lock_state_flips": 2, "occupancy_events": 139, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"behavior-sequence | composite-safety\",\n  \"focus_rooms\": [\"living_room\", \"bedroom\", \"entrance\"],\n  \"focus_devices\": [\"living_room_occupancy\", \"bedroom_occupancy\", \"entrance_light\", \"front_door_contact\", \"bedroom_window_covering\", \"living_room_ac\"],\n  \"focus_chunk_ids\": [\"C06\", \"C07\"],\n  \"suspected_patterns\": [\n    \"Late-night entry sequence: Occupancy detected in living room followed by light off, AC off, and immediate front door contact state change (True) at 22:04.\",\n    \"Window covering manipulation coinciding with occupancy events in the bedroom late at night.\",\n    \"High alarmish counts (28) in C06 correlate with multiple simultaneous state changes suggesting a complex interaction or potential intrusion simulation.\"\n  ],\n  \"why_these_chunks\": \"Chunks C06 and C07 contain the critical temporal sequence starting at 22:04 where lights turn off, AC turns off, and the front door sensor triggers simultaneously while occupancy is present. This specific cluster of deterministic signals (OnOff=False, StateValue=True for door) combined with high 'alarmish_count' indicates a non-standard behavior pattern requiring immediate inspection to rule out security breaches or system logic errors.\"\n}", "triage_parsed": {"latent_task_profile": "behavior-sequence | composite-safety", "focus_rooms": ["living_room", "bedroom", "entrance"], "focus_devices": ["living_room_occupancy", "bedroom_occupancy", "entrance_light", "front_door_contact", "bedroom_window_covering", "living_room_ac"], "focus_chunk_ids": ["C06", "C07"], "suspected_patterns": ["Late-night entry sequence: Occupancy detected in living room followed by light off, AC off, and immediate front door contact state change (True) at 22:04.", "Window covering manipulation coinciding with occupancy events in the bedroom late at night.", "High alarmish counts (28) in C06 correlate with multiple simultaneous state changes suggesting a complex interaction or potential intrusion simulation."], "why_these_chunks": "Chunks C06 and C07 contain the critical temporal sequence starting at 22:04 where lights turn off, AC turns off, and the front door sensor triggers simultaneously while occupancy is present. This specific cluster of deterministic signals (OnOff=False, StateValue=True for door) combined with high 'alarmish_count' indicates a non-standard behavior pattern requiring immediate inspection to rule out security breaches or system logic errors."}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Routine evening departure sequence: The user left the living room, turned off main lights and AC, then exited via the front door and locked it from the outside or a secondary lock mechanism.\",\n      \"evidence\": [\n        \"At 22:04, living_room_light_1 and entrance_light turned OFF.\",\n        \"At 22:04:11, living_room_ac turned OFF.\",\n        \"At 22:04:36, front_door_contact state changed to True (closed/locked).\",\n        \"At 22:04:37, LockOperation event occurred with Source=Auto.\",\n        \"Occupancy remained in bedroom (22:04:20) suggesting someone stayed behind while leaving the common area.\"\n      ],\n      \"weaknesses\": [\n        \"The front door contact flipped to 'True' (often indicating closed/secure) while occupancy was still detected in the bedroom, implying the exit path might have been complex or the sensor logic is non-standard for an open door exit.\",\n        \"High frequency of events within 3 minutes suggests either hurried movement or automated scripting rather than casual human behavior.\"\n      ]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"Standard overnight routine: User moved from living area to bedroom, adjusted window coverings for privacy/sleep, and eventually vacated the house.\",\n      \"evidence\": [\n        \"Bedroom occupancy detected at 22:04:20.\",\n        \"Bedroom light turned ON briefly at 22:04:29, then OFF later.\",\n        \"Window covering manipulated to fully closed (10000%) at 22:04:32.\",\n        \"No further activity in living room after 22:42 (bedroom light off), consistent with winding down for sleep.\"\n      ],\n      \"weaknesses\": [\n        \"The sequence of closing the front door lock (22:04:37) while the user is still present in the bedroom (occupancy 1 until 22:44) is physically counter-intuitive unless the lock is external or triggered by a smart home rule that overrides physical presence.\",\n        \"Temperature readings are extremely high (2250-2277) which may indicate raw integer values rather than Celsius/Fahrenheit, but if real, indicates no HVAC cooling despite AC being turned off.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Potential unauthorized entry simulation or system compromise: A sequence mimicking a normal departure but occurring while internal occupancy persists, possibly testing security sensors or executing a malicious script.\",\n      \"threat_type\": \"Security Breach / Intrusion Simulation\",\n      \"evidence\": [\n        \"Front door contact state changed to True (secured) at 22:04:36 while bedroom occupancy was confirmed active (22:04:20).\",\n        \"Lock operation initiated automatically (Source=Auto) immediately after door closure detection.\",\n        \"Simultaneous rapid state changes: Lights off -> AC off -> Door Closed/Locked within 30 seconds.\",\n        \"The 'alarmish_count' mentioned in triage signals correlates with this tight temporal cluster of deterministic state flips.\"\n      ],\n      \"weaknesses\": [\n        \"Could be a legitimate smart home automation rule (e.g., 'If anyone enters garage/front door, lock it') triggered by a false positive or specific user action not logged as manual.\",\n        \"Lack of alarm trigger history in the logs provided; if an intrusion were happening, one would expect a panic button activation or motion alarm in the hallway.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Sensor malfunction or data corruption leading to false security status updates.\",\n      \"threat_type\": \"System Error / Data Integrity\",\n      \"evidence\": [\n        \"Temperature values (e.g., 2250, 2277) are statistically improbable for ambient room temperature unless they represent millikelvin or raw ADC counts, suggesting calibration failure.\",\n        \"Front door contact flip coincides exactly with other device shutdowns, suggesting a single root cause (power glitch, reset command) rather than independent human actions.\",\n        \"LockState flip count is low (2) yet multiple lock-related events occurred in a short burst.\"\n      ],\n      \"weaknesses\": [\n        \"Does not explain the logical sequence of 'Light Off -> Door Lock' which looks intentional. Malfunctions usually result in random noise, not coherent sequences.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"Temporal conflict: Front door secured (StateValue=True, LockState=1) at 22:04:37 while Bedroom Occupancy was simultaneously Active (1) until 22:44. In a standard secure home model, securing the perimeter while occupants remain inside without explicit egress logging is anomalous.\",\n    \"Rapid determinism: The transition from Living Room Light Off (22:04:04) to Front Door Locked (22:04:37) occurred in <33 seconds with no intermediate 'User Exiting Hallway' occupancy log, bypassing the expected transit zone.\"\n  ],\n  \"missing_information\": [\n    \"Definition of BooleanState.StateValue=True for the front door (is it Open/Closed or Unlocked/Locked? Standard conventions vary).\",\n    \"Logs for the Hallway or Entrance corridor occupancy during the 22:04 window.\",\n    \"Command history to determine if the 'LockOperation(Source=Auto)' was triggered by a mobile app command, a scheduled task, or a sensor loop.\",\n    \"Calibration metadata for temperature sensors to interpret values like 2250.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Routine evening departure sequence: The user left the living room, turned off main lights and AC, then exited via the front door and locked it from the outside or a secondary lock mechanism.", "evidence": ["At 22:04, living_room_light_1 and entrance_light turned OFF.", "At 22:04:11, living_room_ac turned OFF.", "At 22:04:36, front_door_contact state changed to True (closed/locked).", "At 22:04:37, LockOperation event occurred with Source=Auto.", "Occupancy remained in bedroom (22:04:20) suggesting someone stayed behind while leaving the common area."], "weaknesses": ["The front door contact flipped to 'True' (often indicating closed/secure) while occupancy was still detected in the bedroom, implying the exit path might have been complex or the sensor logic is non-standard for an open door exit.", "High frequency of events within 3 minutes suggests either hurried movement or automated scripting rather than casual human behavior."]}, {"id": "N2", "description": "Standard overnight routine: User moved from living area to bedroom, adjusted window coverings for privacy/sleep, and eventually vacated the house.", "evidence": ["Bedroom occupancy detected at 22:04:20.", "Bedroom light turned ON briefly at 22:04:29, then OFF later.", "Window covering manipulated to fully closed (10000%) at 22:04:32.", "No further activity in living room after 22:42 (bedroom light off), consistent with winding down for sleep."], "weaknesses": ["The sequence of closing the front door lock (22:04:37) while the user is still present in the bedroom (occupancy 1 until 22:44) is physically counter-intuitive unless the lock is external or triggered by a smart home rule that overrides physical presence.", "Temperature readings are extremely high (2250-2277) which may indicate raw integer values rather than Celsius/Fahrenheit, but if real, indicates no HVAC cooling despite AC being turned off."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Potential unauthorized entry simulation or system compromise: A sequence mimicking a normal departure but occurring while internal occupancy persists, possibly testing security sensors or executing a malicious script.", "threat_type": "Security Breach / Intrusion Simulation", "evidence": ["Front door contact state changed to True (secured) at 22:04:36 while bedroom occupancy was confirmed active (22:04:20).", "Lock operation initiated automatically (Source=Auto) immediately after door closure detection.", "Simultaneous rapid state changes: Lights off -> AC off -> Door Closed/Locked within 30 seconds.", "The 'alarmish_count' mentioned in triage signals correlates with this tight temporal cluster of deterministic state flips."], "weaknesses": ["Could be a legitimate smart home automation rule (e.g., 'If anyone enters garage/front door, lock it') triggered by a false positive or specific user action not logged as manual.", "Lack of alarm trigger history in the logs provided; if an intrusion were happening, one would expect a panic button activation or motion alarm in the hallway."]}, {"id": "A2", "description": "Sensor malfunction or data corruption leading to false security status updates.", "threat_type": "System Error / Data Integrity", "evidence": ["Temperature values (e.g., 2250, 2277) are statistically improbable for ambient room temperature unless they represent millikelvin or raw ADC counts, suggesting calibration failure.", "Front door contact flip coincides exactly with other device shutdowns, suggesting a single root cause (power glitch, reset command) rather than independent human actions.", "LockState flip count is low (2) yet multiple lock-related events occurred in a short burst."], "weaknesses": ["Does not explain the logical sequence of 'Light Off -> Door Lock' which looks intentional. Malfunctions usually result in random noise, not coherent sequences."]}], "most_discriminative_evidence": ["Temporal conflict: Front door secured (StateValue=True, LockState=1) at 22:04:37 while Bedroom Occupancy was simultaneously Active (1) until 22:44. In a standard secure home model, securing the perimeter while occupants remain inside without explicit egress logging is anomalous.", "Rapid determinism: The transition from Living Room Light Off (22:04:04) to Front Door Locked (22:04:37) occurred in <33 seconds with no intermediate 'User Exiting Hallway' occupancy log, bypassing the expected transit zone."], "missing_information": ["Definition of BooleanState.StateValue=True for the front door (is it Open/Closed or Unlocked/Locked? Standard conventions vary).", "Logs for the Hallway or Entrance corridor occupancy during the 22:04 window.", "Command history to determine if the 'LockOperation(Source=Auto)' was triggered by a mobile app command, a scheduled task, or a sensor loop.", "Calibration metadata for temperature sensors to interpret values like 2250."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C05\", \"C03\"],\n  \"missing_checks\": [\n    \"Verify Hallway/Entrance corridor occupancy logs around 22:04 to rule out user transit through the secured zone.\",\n    \"Clarify the boolean definition of front_door_contact StateValue=True (Closed vs. Locked) to validate the 'secured while occupied' anomaly.\",\n    \"Check command history or system logs to determine if LockOperation(Source=Auto) was triggered by a scheduled task, mobile app, or sensor loop.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identified the temporal conflict between securing the front door and internal bedroom occupancy, which is the core anomaly.\",\n    \"However, the evidence regarding the hallway transit is missing; without confirming no one passed through the entrance/hallway after the lock engaged, the 'intrusion simulation' hypothesis remains unverified.\",\n    \"Chunk C05 likely contains earlier context or the specific timestamp transition leading up to C06, while C03 may contain baseline data for comparison or relevant hallway sensors.\",\n    \"Temperature values (2250+) are flagged as suspicious but lack calibration metadata; this requires checking system config logs rather than just event chunks.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C05", "C03"], "missing_checks": ["Verify Hallway/Entrance corridor occupancy logs around 22:04 to rule out user transit through the secured zone.", "Clarify the boolean definition of front_door_contact StateValue=True (Closed vs. Locked) to validate the 'secured while occupied' anomaly.", "Check command history or system logs to determine if LockOperation(Source=Auto) was triggered by a scheduled task, mobile app, or sensor loop."], "supervisor_notes": ["The analysis correctly identified the temporal conflict between securing the front door and internal bedroom occupancy, which is the core anomaly.", "However, the evidence regarding the hallway transit is missing; without confirming no one passed through the entrance/hallway after the lock engaged, the 'intrusion simulation' hypothesis remains unverified.", "Chunk C05 likely contains earlier context or the specific timestamp transition leading up to C06, while C03 may contain baseline data for comparison or relevant hallway sensors.", "Temperature values (2250+) are flagged as suspicious but lack calibration metadata; this requires checking system config logs rather than just event chunks."]}, "preview_triage_prompt": "## Query\n以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Layout\nLayout: 一室一厅 (Studio/1BR)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅台灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 232,\n    \"bedroom\": 183,\n    \"kitchen\": 153,\n    \"bathroom\": 24,\n    \"entrance\": 10\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 437,\n    \"Occupancy\": 139,\n    \"OnOff\": 13,\n    \"StateValue\": 4,\n    \"LockState\": 2,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"CurrentPositionLiftPercent100ths\": 1,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 2,\n  \"occupancy_events\": 139,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-17T11:55:00\",\n    \"end_ts\": \"2026-06-17T13:45:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 27,\n      \"bedroom\": 27,\n      \"kitchen\": 22,\n      \"bathroom\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"bathroom_occupancy\"\n    ],\n    \"alarmish_count\": 12,\n    \"preview_lines\": [\n      \"[2026-06-17T11:55:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2526\",\n      \"[2026-06-17T11:55:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2429\",\n      \"[2026-06-17T11:55:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2522\",\n      \"[2026-06-17T12:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2534\",\n      \"[2026-06-17T12:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2436\",\n      \"[2026-06-17T12:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2522\",\n      \"[2026-06-17T12:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-17T12:05:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2518\",\n      \"[2026-06-17", "preview_verifier_prompt": "## Query\n以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Triage\n{\n  \"latent_task_profile\": \"behavior-sequence | composite-safety\",\n  \"focus_rooms\": [\"living_room\", \"bedroom\", \"entrance\"],\n  \"focus_devices\": [\"living_room_occupancy\", \"bedroom_occupancy\", \"entrance_light\", \"front_door_contact\", \"bedroom_window_covering\", \"living_room_ac\"],\n  \"focus_chunk_ids\": [\"C06\", \"C07\"],\n  \"suspected_patterns\": [\n    \"Late-night entry sequence: Occupancy detected in living room followed by light off, AC off, and immediate front door contact state change (True) at 22:04.\",\n    \"Window covering manipulation coinciding with occupancy events in the bedroom late at night.\",\n    \"High alarmish counts (28) in C06 correlate with multiple simultaneous state changes suggesting a complex interaction or potential intrusion simulation.\"\n  ],\n  \"why_these_chunks\": \"Chunks C06 and C07 contain the critical temporal sequence starting at 22:04 where lights turn off, AC turns off, and the front door sensor triggers simultaneously while occupancy is present. This specific cluster of deterministic signals (OnOff=False, StateValue=True for door) combined with high 'alarmish_count' indicates a non-standard behavior pattern requiring immediate inspection to rule out security breaches or system logic errors.\"\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Routine evening departure sequence: The user left the living room, turned off main lights and AC, then exited via the front door and locked it from the outside or a secondary lock mechanism.\",\n      \"evidence\": [\n        \"At 22:04, living_room_light_1 and entrance_light turned OFF.\",\n        \"At 22:04:11, living_room_ac turned OFF.\",\n        \"At 22:04:36, front_door_contact state changed to True (closed/locked).\",\n        \"At 22:04:37, LockOperation event occurred with Source=Auto.\",\n        \"Occupancy remained in bedroom (22:04:20) suggesting someone stayed behind while leaving the common area.\"\n      ],\n      \"weaknesses\": [\n        \"The front door contact flipped to 'True' (often indicating closed/secure) while occupancy was still detected in the bedroom, implying the exit path might have been complex or the sensor logic is non-standard for an open door exit.\",\n        \"High frequency of events within 3 minutes suggests either hurried movement or automated scripting rather than casual human behavior.\"\n      ]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"Standard overnight routine: User move"}}
{"episode_id": "SQ3_TP_B_0452", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq3\\SQ3_TP_B_0452.json", "metadata": {"sq_type": "SQ3", "sq_name": "行为序列分析", "variant": "TP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "family_with_children", "base_date": "2026-06-09T00:00:00", "seed": 20261081, "scenario_id": "BA-01", "total_events": 1842, "anomaly_events_count": 5}, "ground_truth": {"scenario_id": "BA-01", "scenario_name": "深夜异常多房间活动", "category": "behavioral_anomaly", "is_anomaly": true, "threat_type": "behavioral_anomaly", "key_evidence": ["凌晨2:30-2:40短时间内多房间连续活动", "活动轨迹：客厅→厨房→玄关（像在搜索什么）", "卧室全程无活动（住户在睡觉），这些活动不是住户产生的", "注意区分：如果卧室先有活动再到其他房间，则可能是住户起夜"], "expected_response": "高优先级入侵警报", "difficulty_score": 11, "difficulty_level": 3, "difficulty_label": "L3_composite_reasoning", "difficulty_dimensions": {"D1_evidence_count": 3, "D2_signal_directness": 2, "D3_cross_device": 3, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "kitchen", "injection_time": "2026-06-09T05:55:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"Systemic sensor failure causing physically impossible temperature readings (2300-2520) across all rooms for over 14 hours, likely due to a unit conversion error or firmware bug, rather than a security breach or environmental hazard.\",\n  \"reasoning\": [\n    \"Analysis of chunks C03 and C04 confirms the anomalous temperature values (~2400-2500) are not an isolated event but a persistent systemic issue existing from early morning (04:00), ruling out transient spikes.\",\n    \"The magnitude of the values (e.g., 2492) is physically impossible for ambient air sensors in Celsius or Fahrenheit, indicating a data integrity failure such as a missing decimal point (reporting 24.92 as 2492) or incorrect scaling factor.\",\n    \"While door lock events in C14/C16 showed suspicious manual/auto cycles, the continuous invalid thermal data suggests the primary risk is false system triggers (e.g., fire alarms) or HVAC inefficiency, making 'sensor_malfunction' the definitive root cause over intrusion.\",\n    \"The lack of correlation between extreme reported temperatures and any corrective HVAC response (AC turning on but temp remaining static at invalid levels) further proves the control loop is reacting to garbage data.\"\n  ],\n  \"key_evidence\": [\n    \"Temperature readings consistently range from 2300 to 2520 across all four room sensors during chunks C03-C05, which is impossible for real-world conditions.\",\n    \"Historical data in C03 (04:00) shows the anomaly was present before the peak activity in C05, confirming it is a long-standing configuration or hardware error.\",\n    \"Despite AC activation at 17:49 (C16), the temperature reading immediately following remains 2337, demonstrating the system cannot process valid feedback due to the input corruption.\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately reset or recalibrate all temperature sensors to restore accurate baseline data.\",\n    \"Inspect device firmware for known bugs related to unit conversion or integer overflow handling.\",\n    \"Review historical logs to confirm if this specific sensor ID has a persistent offset error prior to the current log window.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "Systemic sensor failure causing physically impossible temperature readings (2300-2520) across all rooms for over 14 hours, likely due to a unit conversion error or firmware bug, rather than a security breach or environmental hazard.", "reasoning": ["Analysis of chunks C03 and C04 confirms the anomalous temperature values (~2400-2500) are not an isolated event but a persistent systemic issue existing from early morning (04:00), ruling out transient spikes.", "The magnitude of the values (e.g., 2492) is physically impossible for ambient air sensors in Celsius or Fahrenheit, indicating a data integrity failure such as a missing decimal point (reporting 24.92 as 2492) or incorrect scaling factor.", "While door lock events in C14/C16 showed suspicious manual/auto cycles, the continuous invalid thermal data suggests the primary risk is false system triggers (e.g., fire alarms) or HVAC inefficiency, making 'sensor_malfunction' the definitive root cause over intrusion.", "The lack of correlation between extreme reported temperatures and any corrective HVAC response (AC turning on but temp remaining static at invalid levels) further proves the control loop is reacting to garbage data."], "key_evidence": ["Temperature readings consistently range from 2300 to 2520 across all four room sensors during chunks C03-C05, which is impossible for real-world conditions.", "Historical data in C03 (04:00) shows the anomaly was present before the peak activity in C05, confirming it is a long-standing configuration or hardware error.", "Despite AC activation at 17:49 (C16), the temperature reading immediately following remains 2337, demonstrating the system cannot process valid feedback due to the input corruption."], "recommended_actions": ["Immediately reset or recalibrate all temperature sensors to restore accurate baseline data.", "Inspect device firmware for known bugs related to unit conversion or integer overflow handling.", "Review historical logs to confirm if this specific sensor ID has a persistent offset error prior to the current log window."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 55.44890737533569, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1842, "chunk_count": 24, "signals": {"room_activity": {"living_room": 406, "master_bedroom": 516, "second_bedroom": 336, "kitchen": 304, "bathroom": 48, "entrance": 232}, "attribute_frequency": {"MeasuredValue": 1156, "Occupancy": 649, "OnOff": 17, "StateValue": 7, "LockState": 5, "SystemMode": 1, "OperationalState": 1, "CurrentPositionLiftPercent100ths": 1}, "lock_state_flips": 5, "occupancy_events": 649, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\", \"entrance\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"living_room_temp_sensor\", \"front_door_lock\", \"front_door_contact\", \"kitchen_cook_surface\", \"master_bedroom_occupancy\"],\n  \"focus_chunk_ids\": [\"C05\", \"C14\", \"C16\"],\n  \"suspected_patterns\": [\n    \"Unexplained high temperature baseline (22.6°C - 25.5°C range) across multiple rooms for the majority of the day.\",\n    \"Simultaneous occupancy in living room and master bedroom with no kitchen activity during mid-day peaks, suggesting potential multi-person presence or sensor drift.\",\n    \"Door lock/unlock sequence at 17:49 coinciding with immediate occupancy changes and HVAC activation.\"\n  ],\n  \"why_these_chunks\": [\n    \"C05 shows the peak temperature readings (~24.9°C) and initial cooking surface activation, establishing the anomalous thermal baseline.\",\n    \"C14 captures the manual door lock operation event, a critical state change requiring context verification.\",\n    \"C16 reveals the immediate aftermath of the door unlock/open event, showing rapid occupancy shifts and HVAC engagement, which is essential for determining if this was a routine entry or an intrusion response.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "living_room", "entrance"], "focus_devices": ["kitchen_temp_sensor", "living_room_temp_sensor", "front_door_lock", "front_door_contact", "kitchen_cook_surface", "master_bedroom_occupancy"], "focus_chunk_ids": ["C05", "C14", "C16"], "suspected_patterns": ["Unexplained high temperature baseline (22.6°C - 25.5°C range) across multiple rooms for the majority of the day.", "Simultaneous occupancy in living room and master bedroom with no kitchen activity during mid-day peaks, suggesting potential multi-person presence or sensor drift.", "Door lock/unlock sequence at 17:49 coinciding with immediate occupancy changes and HVAC activation."], "why_these_chunks": ["C05 shows the peak temperature readings (~24.9°C) and initial cooking surface activation, establishing the anomalous thermal baseline.", "C14 captures the manual door lock operation event, a critical state change requiring context verification.", "C16 reveals the immediate aftermath of the door unlock/open event, showing rapid occupancy shifts and HVAC engagement, which is essential for determining if this was a routine entry or an intrusion response."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Routine household activity involving cooking, temperature regulation, and standard door locking/unlocking cycles.\",\n      \"evidence\": [\n        \"C05 shows a typical morning sequence: lights on (06:47), cook surface activated briefly (06:47-06:50), followed by kitchen light off.\",\n        \"C16 shows an evening entry (17:49) triggering immediate occupancy detection in living room and activation of AC/lighting, consistent with returning home.\",\n        \"Occupancy patterns show one person primarily in the master bedroom while others move through the entrance/living room.\"\n      ],\n      \"weaknesses\": [\n        \"Temperature values are reported in raw integers (e.g., 2492, 2337) which appear physically impossible for ambient air temperature unless scaled incorrectly; this suggests potential sensor calibration failure or data logging error rather than actual thermal anomalies.\",\n        \"The frequency of manual lock operations (multiple times per chunk) is higher than typical for a single resident unless they are testing locks frequently or there is unauthorized access simulation.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Sensor Data Integrity Failure / Malicious Firmware Override causing nonsensical temperature readings.\",\n      \"threat_type\": \"System Integrity / False Positive Trigger\",\n      \"evidence\": [\n        \"All temperature readings across all rooms are consistently in the range of 2300-2520 (e.g., C05: 2492, C16: 2337). Real-world temperatures should be ~20-30°C. This indicates a scaling factor error (likely multiplying by 100) or a firmware override injecting fake data.\",\n        \"Simultaneous high 'values' across geographically separated sensors (living room, kitchen, bedrooms) without corresponding HVAC response logic to correct the 'extreme' heat suggests the system cannot distinguish real heat from injected data.\",\n        \"In C16, despite the AC being turned ON at 17:49:22, the temperature reading at 17:50:00 is still 2337 (raw), showing no reaction loop to the control command due to the invalid input state.\"\n      ],\n      \"weaknesses\": [\n        \"The occupancy events and lock states appear logically consistent with human behavior, suggesting the anomaly may be isolated to the temperature reporting subsystem rather than a total system compromise or physical intrusion.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Potential Intrusion Simulation or Covert Presence Detection via Door Lock Manipulation.\",\n      \"threat_type\": \"Security Breach Attempt\",\n      \"evidence\": [\n        \"C14 and C16 both feature a specific pattern: Manual Lock -> Immediate Contact Open -> Occupancy Detected -> Auto Unlock.\",\n        \"In C14 (15:57), the manual lock is followed immediately by contact open and occupancy spike, then auto-unlock. This rapid cycle is unusual for normal entry/exit.\",\n        \"C16 (17:49) mirrors this: Lock (manual) -> Contact False -> Occupancy True -> Auto Unlock. The tight temporal coupling between manual manipulation and automatic reversal suggests either a smart lock vulnerability or an attempt to verify if the system detects 'forced' vs 'normal' entry.\"\n      ],\n      \"weaknesses\": [\n        \"The 'Auto' unlock source in C16 occurs seconds after the manual lock, which could simply be a scheduled routine or a user habit, not necessarily malicious. Without external context confirming forced entry, this remains circumstantial.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The magnitude of temperature values (e.g., 2492) which are physically impossible for ambient sensors, strongly pointing to a data integrity issue over actual environmental anomalies.\",\n    \"The precise timestamp alignment between 'Manual' lock initiation and subsequent 'Auto' unlock/occupancy spikes in C14 and C16, distinguishing between random noise and programmed sequences.\"\n  ],\n  \"missing_information\": [\n    \"The unit of measurement for the temperature sensor (is it Celsius * 100? Fahrenheit? Kelvin?).\",\n    \"Historical baseline data for these specific sensors to confirm if the 'high' numbers are a new deviation or long-standing configuration.\",\n    \"User identity logs to correlate the 'Manual' lock operations with authorized residents.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Routine household activity involving cooking, temperature regulation, and standard door locking/unlocking cycles.", "evidence": ["C05 shows a typical morning sequence: lights on (06:47), cook surface activated briefly (06:47-06:50), followed by kitchen light off.", "C16 shows an evening entry (17:49) triggering immediate occupancy detection in living room and activation of AC/lighting, consistent with returning home.", "Occupancy patterns show one person primarily in the master bedroom while others move through the entrance/living room."], "weaknesses": ["Temperature values are reported in raw integers (e.g., 2492, 2337) which appear physically impossible for ambient air temperature unless scaled incorrectly; this suggests potential sensor calibration failure or data logging error rather than actual thermal anomalies.", "The frequency of manual lock operations (multiple times per chunk) is higher than typical for a single resident unless they are testing locks frequently or there is unauthorized access simulation."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Sensor Data Integrity Failure / Malicious Firmware Override causing nonsensical temperature readings.", "threat_type": "System Integrity / False Positive Trigger", "evidence": ["All temperature readings across all rooms are consistently in the range of 2300-2520 (e.g., C05: 2492, C16: 2337). Real-world temperatures should be ~20-30°C. This indicates a scaling factor error (likely multiplying by 100) or a firmware override injecting fake data.", "Simultaneous high 'values' across geographically separated sensors (living room, kitchen, bedrooms) without corresponding HVAC response logic to correct the 'extreme' heat suggests the system cannot distinguish real heat from injected data.", "In C16, despite the AC being turned ON at 17:49:22, the temperature reading at 17:50:00 is still 2337 (raw), showing no reaction loop to the control command due to the invalid input state."], "weaknesses": ["The occupancy events and lock states appear logically consistent with human behavior, suggesting the anomaly may be isolated to the temperature reporting subsystem rather than a total system compromise or physical intrusion."]}, {"id": "A2", "description": "Potential Intrusion Simulation or Covert Presence Detection via Door Lock Manipulation.", "threat_type": "Security Breach Attempt", "evidence": ["C14 and C16 both feature a specific pattern: Manual Lock -> Immediate Contact Open -> Occupancy Detected -> Auto Unlock.", "In C14 (15:57), the manual lock is followed immediately by contact open and occupancy spike, then auto-unlock. This rapid cycle is unusual for normal entry/exit.", "C16 (17:49) mirrors this: Lock (manual) -> Contact False -> Occupancy True -> Auto Unlock. The tight temporal coupling between manual manipulation and automatic reversal suggests either a smart lock vulnerability or an attempt to verify if the system detects 'forced' vs 'normal' entry."], "weaknesses": ["The 'Auto' unlock source in C16 occurs seconds after the manual lock, which could simply be a scheduled routine or a user habit, not necessarily malicious. Without external context confirming forced entry, this remains circumstantial."]}], "most_discriminative_evidence": ["The magnitude of temperature values (e.g., 2492) which are physically impossible for ambient sensors, strongly pointing to a data integrity issue over actual environmental anomalies.", "The precise timestamp alignment between 'Manual' lock initiation and subsequent 'Auto' unlock/occupancy spikes in C14 and C16, distinguishing between random noise and programmed sequences."], "missing_information": ["The unit of measurement for the temperature sensor (is it Celsius * 100? Fahrenheit? Kelvin?).", "Historical baseline data for these specific sensors to confirm if the 'high' numbers are a new deviation or long-standing configuration.", "User identity logs to correlate the 'Manual' lock operations with authorized residents."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C03\", \"C04\", \"C17\"],\n  \"missing_checks\": [\n    \"Verify historical baseline for temperature sensors to determine if '2492' is a new anomaly or a persistent configuration error.\",\n    \"Cross-reference manual lock timestamps in C14/C16 with authorized user identity logs to rule out routine testing habits.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identified the critical data integrity issue (impossible temperature values) and the suspicious door lock sequences. However, evidence sufficiency is low because: 1) The specific chunks selected (C05, C14, C16) do not establish a timeline; C03 and C04 are needed to observe if the temperature scaling error existed prior to the peak in C05, confirming it as a systemic sensor failure rather than an isolated spike. 2) C17 (the period after the evening event in C16) is required to see if the system recovers or if the anomaly persists, which helps distinguish between a firmware bug and active manipulation.\",\n    \"The hypothesis of 'malicious firmware override' remains speculative without historical context from earlier chunks to prove this behavior is unprecedented.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C03", "C04", "C17"], "missing_checks": ["Verify historical baseline for temperature sensors to determine if '2492' is a new anomaly or a persistent configuration error.", "Cross-reference manual lock timestamps in C14/C16 with authorized user identity logs to rule out routine testing habits."], "supervisor_notes": ["The analysis correctly identified the critical data integrity issue (impossible temperature values) and the suspicious door lock sequences. However, evidence sufficiency is low because: 1) The specific chunks selected (C05, C14, C16) do not establish a timeline; C03 and C04 are needed to observe if the temperature scaling error existed prior to the peak in C05, confirming it as a systemic sensor failure rather than an isolated spike. 2) C17 (the period after the evening event in C16) is required to see if the system recovers or if the anomaly persists, which helps distinguish between a firmware bug and active manipulation.", "The hypothesis of 'malicious firmware override' remains speculative without historical context from earlier chunks to prove this behavior is unprecedented."]}, "preview_triage_prompt": "## Query\n以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 406,\n    \"master_bedroom\": 516,\n    \"second_bedroom\": 336,\n    \"kitchen\": 304,\n    \"bathroom\": 48,\n    \"entrance\": 232\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1156,\n    \"Occupancy\": 649,\n    \"OnOff\": 17,\n    \"StateValue\": 7,\n    \"LockState\": 5,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"CurrentPositionLiftPercent100ths\": 1\n  },\n  \"lock_state_flips\": 5,\n  \"occupancy_events\": 649,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-09T00:00:00\",\n    \"end_ts\": \"2026-06-09T01:20:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 20,\n      \"master_bedroom\": 19,\n      \"second_bedroom\": 19,\n      \"kitchen\": 16,\n      \"bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"master_bedroom_occupancy\"\n    ],\n    \"alarmish_count\": 15,\n    \"preview_lines\": [\n      \"[2026-06-09T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2267\",\n      \"[2026-06-09T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2263\",\n      \"[2026-06-09T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2263\",\n      \"[2026-06-09T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2273\",\n      \"[2026-06-09T00:00:00] liv", "preview_verifier_prompt": "## Query\n以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\", \"entrance\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"living_room_temp_sensor\", \"front_door_lock\", \"front_door_contact\", \"kitchen_cook_surface\", \"master_bedroom_occupancy\"],\n  \"focus_chunk_ids\": [\"C05\", \"C14\", \"C16\"],\n  \"suspected_patterns\": [\n    \"Unexplained high temperature baseline (22.6°C - 25.5°C range) across multiple rooms for the majority of the day.\",\n    \"Simultaneous occupancy in living room and master bedroom with no kitchen activity during mid-day peaks, suggesting potential multi-person presence or sensor drift.\",\n    \"Door lock/unlock sequence at 17:49 coinciding with immediate occupancy changes and HVAC activation.\"\n  ],\n  \"why_these_chunks\": [\n    \"C05 shows the peak temperature readings (~24.9°C) and initial cooking surface activation, establishing the anomalous thermal baseline.\",\n    \"C14 captures the manual door lock operation event, a critical state change requiring context verification.\",\n    \"C16 reveals the immediate aftermath of the door unlock/open event, showing rapid occupancy shifts and HVAC engagement, which is essential for determining if this was a routine entry or an intrusion response.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Routine household activity involving cooking, temperature regulation, and standard door locking/unlocking cycles.\",\n      \"evidence\": [\n        \"C05 shows a typical morning sequence: lights on (06:47), cook surface activated briefly (06:47-06:50), followed by kitchen light off.\",\n        \"C16 shows an evening entry (17:49) triggering immediate occupancy detection in living room and activation of AC/lighting, consistent with returning home.\",\n        \"Occupancy patterns show one person primarily in the master bedroom while others move through the entrance/living room.\"\n      ],\n      \"weaknesses\": [\n        \"Temperature values are reported in raw integers (e.g., 2492, 2337) which appear physically impossible for ambient air temperature unless scaled incorrectly; this suggests potential sensor calibration failure or data logging error rather than actual thermal anomalies.\",\n        \"The frequency of manual lock operations (multiple times per chunk) is higher than typical for a single resident unless they are testing locks frequently or there is unauthorized access simulation.\"\n      ]\n    }\n  "}}
{"episode_id": "SQ3_TP_C_0444", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq3\\SQ3_TP_C_0444.json", "metadata": {"sq_type": "SQ3", "sq_name": "行为序列分析", "variant": "TP", "layout_id": "C", "layout_name": "三室两厅 (3BR)", "profile_id": "family_with_children", "base_date": "2026-06-16T00:00:00", "seed": 20261073, "scenario_id": "CH-04", "total_events": 2291, "anomaly_events_count": 3}, "ground_truth": {"scenario_id": "CH-04", "scenario_name": "儿童尝试开门外出", "category": "child_specific", "is_anomaly": true, "threat_type": "child_safety", "key_evidence": ["玄关运动 + 门锁解锁失败", "密码错误（小孩可能记不准密码）", "无成人在玄关区域", "跟 INS-02 的区别：这里不是暴力破解，只有1-2次尝试，且家中有其他房间的活动（说明有人在家）"], "expected_response": "通知家长孩子在尝试开门", "difficulty_score": 9, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "living_room", "injection_time": "2026-06-16T08:43:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"Occupancy sensors are stuck in a synchronized loop generating false positive events every ~2 minutes across all rooms due to hardware or calibration failure, not human activity.\",\n  \"reasoning\": [\n    \"The timestamps reveal a rigid, mathematically perfect cycle: Occupancy triggers occur at exact intervals of roughly 1 minute 26 seconds (e.g., Master/Kids -> Entrance -> Dining), repeating identically across C00, C01, and C02 without any variation in timing or sequence.\",\n    \"Human movement is stochastic and rarely exhibits such precise, global synchronization (all 4-5 room sensors triggering state changes simultaneously on the same second) over a continuous 8+ hour period.\",\n    \"The lack of supporting context data (no door lock toggles, no light switches activating/deactivating except for one isolated event in C15, and no temperature fluctuations consistent with human presence) confirms that the 'activity' is purely digital noise from a malfunctioning sensor array rather than physical intrusion or occupancy.\",\n    \"The pattern persists through day and night cycles unchanged, which is characteristic of a device bug or firmware glitch rather than adaptive behavior by humans.\"\n  ],\n  \"key_evidence\": [\n    \"Exact repetition of the sequence: MasterBedroom/KidsRoom (1 min 26 sec later) -> Entrance (1 min 20 sec later) -> DiningRoom (1 min 20 sec later) occurring consistently from 11:55 to 23:55.\",\n    \"Absence of correlated actuator events (lights, locks, curtains) during high-frequency occupancy reports, indicating the sensors are decoupled from actual environmental interactions.\",\n    \"Temperature readings remain static or drift linearly/independently of the occupancy spikes, proving thermal mass response does not match the reported 'presence'.\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately isolate and reset the affected occupancy sensor devices (Living Room, Master Bedroom, Kids Room, Entrance, Dining Room) to clear the stuck state.\",\n    \"Inspect the sensor hardware for obstructions, wiring issues, or firmware bugs causing the periodic polling error.\",\n    \"Review system logs for any recent configuration changes or power surges that may have triggered the malfunction.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "Occupancy sensors are stuck in a synchronized loop generating false positive events every ~2 minutes across all rooms due to hardware or calibration failure, not human activity.", "reasoning": ["The timestamps reveal a rigid, mathematically perfect cycle: Occupancy triggers occur at exact intervals of roughly 1 minute 26 seconds (e.g., Master/Kids -> Entrance -> Dining), repeating identically across C00, C01, and C02 without any variation in timing or sequence.", "Human movement is stochastic and rarely exhibits such precise, global synchronization (all 4-5 room sensors triggering state changes simultaneously on the same second) over a continuous 8+ hour period.", "The lack of supporting context data (no door lock toggles, no light switches activating/deactivating except for one isolated event in C15, and no temperature fluctuations consistent with human presence) confirms that the 'activity' is purely digital noise from a malfunctioning sensor array rather than physical intrusion or occupancy.", "The pattern persists through day and night cycles unchanged, which is characteristic of a device bug or firmware glitch rather than adaptive behavior by humans."], "key_evidence": ["Exact repetition of the sequence: MasterBedroom/KidsRoom (1 min 26 sec later) -> Entrance (1 min 20 sec later) -> DiningRoom (1 min 20 sec later) occurring consistently from 11:55 to 23:55.", "Absence of correlated actuator events (lights, locks, curtains) during high-frequency occupancy reports, indicating the sensors are decoupled from actual environmental interactions.", "Temperature readings remain static or drift linearly/independently of the occupancy spikes, proving thermal mass response does not match the reported 'presence'."], "recommended_actions": ["Immediately isolate and reset the affected occupancy sensor devices (Living Room, Master Bedroom, Kids Room, Entrance, Dining Room) to clear the stuck state.", "Inspect the sensor hardware for obstructions, wiring issues, or firmware bugs causing the periodic polling error.", "Review system logs for any recent configuration changes or power surges that may have triggered the malfunction."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 56.04790997505188, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1318, "chunk_count": 17, "signals": {"room_activity": {"living_room": 234, "master_bedroom": 291, "kids_room": 293, "kitchen": 153, "entrance": 153, "dining_room": 146, "second_bedroom": 24, "master_bathroom": 24}, "attribute_frequency": {"Occupancy": 709, "MeasuredValue": 582, "OnOff": 13, "StateValue": 4, "LockState": 3, "CurrentPositionLiftPercent100ths": 2, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 3, "occupancy_events": 709, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"behavior-sequence | single-event-safety\",\n  \"focus_rooms\": [\"living_room\", \"master_bedroom\", \"kids_room\", \"kitchen\"],\n  \"focus_devices\": [\"occupancy_sensor\", \"temperature_sensor\", \"door_lock\", \"contact_sensor\"],\n  \"focus_chunk_ids\": [\"C00\", \"C15\", \"C16\"],\n  \"suspected_patterns\": [\n    \"synchronized_multi-room_occupancy\",\n    \"cooling_cycle_drift\",\n    \"late_night_activity_anomaly\"\n  ],\n  \"why_these_chunks\": [\n    \"C00: Establishes baseline for high-frequency synchronized occupancy events across living, master, and kids rooms immediately after entry.\",\n    \"C15: Shows a specific state change (bedroom light OFF) amidst continued high activity, indicating a shift in routine or sleep onset while others remain active.\",\n    \"C16: Captures the tail end of the night with reduced event counts but persistent multi-room presence, requiring verification against expected 'night mode' behavior.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "behavior-sequence | single-event-safety", "focus_rooms": ["living_room", "master_bedroom", "kids_room", "kitchen"], "focus_devices": ["occupancy_sensor", "temperature_sensor", "door_lock", "contact_sensor"], "focus_chunk_ids": ["C00", "C15", "C16"], "suspected_patterns": ["synchronized_multi-room_occupancy", "cooling_cycle_drift", "late_night_activity_anomaly"], "why_these_chunks": ["C00: Establishes baseline for high-frequency synchronized occupancy events across living, master, and kids rooms immediately after entry.", "C15: Shows a specific state change (bedroom light OFF) amidst continued high activity, indicating a shift in routine or sleep onset while others remain active.", "C16: Captures the tail end of the night with reduced event counts but persistent multi-room presence, requiring verification against expected 'night mode' behavior."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Standard family evening routine with synchronized dining and relaxation, followed by a shared sleep onset.\",\n      \"evidence\": [\"High frequency of occupancy events in living, master, and kids rooms (234-293 count) indicates active household presence.\", \"Synchronized temperature readings (~25°C) during daytime (C00) suggest consistent HVAC operation or ambient conditions.\", \"Evening logs (C15/C16) show coordinated movement: lights off in bedrooms while occupants remain active in common areas (entrance/dining).\", \"Occupancy patterns align with typical post-dinner wind-down where multiple family members occupy different zones before settling.\"],\n      \"weaknesses\": [\"Does not fully explain the extremely rigid synchronization of occupancy sensor flips (every ~2 mins across all sensors) which appears unnatural for organic human movement.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Coordinated intrusion or simulated occupancy loop designed to mimic normal family activity.\",\n      \"threat_type\": \"Social Engineering / Deception / Intrusion Simulation\",\n      \"evidence\": [\"Rigid temporal alignment: Occupancy sensors in distinct rooms (Living, Master, Kids, Entrance, Dining) trigger state changes with identical intervals (~2 minutes) throughout C00, C15, and C16. This suggests a single automated actor moving through pre-set waypoints rather than independent individuals.\", \"Discrepancy between light state and occupancy: In C15, `master_bedroom_light` turns OFF at 22:50:36, yet `master_bedroom_occupancy` remains ON (1) consistently until 23:35+. Humans rarely sleep with lights on for 45+ minutes if they are 'occupied' the room in a way that triggers motion sensors repeatedly.\", \"Temperature fluctuation anomaly: Temperature readings show erratic jumps (e.g., Kitchen drops from 2273 to 2257 then back up) inconsistent with thermal mass response time, suggesting potential sensor spoofing or calibration drift exploited by an attacker.\", \"Low diversity in event types: 709% of signals are generic 'Occupancy', with almost no 'LockState', 'CurrentPosition', or 'SystemMode' changes despite high activity, indicating a lack of complex interaction data typical of real life.\"],\n      \"weaknesses\": [\"Could be explained by a poorly calibrated multi-zone HVAC system triggering occupancy sensors via air flow detection rather than physical presence.\", \"Household members could theoretically move in perfect lockstep, though the probability is statistically low without prior knowledge of the specific logging interval.\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The exact repetition of the sequence: Entrance -> Dining -> Living/Master/Kids every 2 minutes across 12 hours of varied timestamps.\",\n    \"The persistence of 'Occupancy=1' in the Master Bedroom after the bed light was turned off for over 40 minutes, contradicting expected human behavior.\",\n    \"Absence of any lock state changes or door contact sensor alerts during the high-activity period, despite frequent entrance traffic.\"\n  ],\n  \"missing_information\": [\n    \"Raw timestamp deltas between consecutive events for specific users/devices to confirm the 2-minute periodicity.\",\n    \"Video feed or audio logs to verify actual presence versus sensor ghosting.\",\n    \"Historical baseline data to determine if this 'synchronized' pattern is a known quirk of the specific sensor hardware model.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Standard family evening routine with synchronized dining and relaxation, followed by a shared sleep onset.", "evidence": ["High frequency of occupancy events in living, master, and kids rooms (234-293 count) indicates active household presence.", "Synchronized temperature readings (~25°C) during daytime (C00) suggest consistent HVAC operation or ambient conditions.", "Evening logs (C15/C16) show coordinated movement: lights off in bedrooms while occupants remain active in common areas (entrance/dining).", "Occupancy patterns align with typical post-dinner wind-down where multiple family members occupy different zones before settling."], "weaknesses": ["Does not fully explain the extremely rigid synchronization of occupancy sensor flips (every ~2 mins across all sensors) which appears unnatural for organic human movement."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Coordinated intrusion or simulated occupancy loop designed to mimic normal family activity.", "threat_type": "Social Engineering / Deception / Intrusion Simulation", "evidence": ["Rigid temporal alignment: Occupancy sensors in distinct rooms (Living, Master, Kids, Entrance, Dining) trigger state changes with identical intervals (~2 minutes) throughout C00, C15, and C16. This suggests a single automated actor moving through pre-set waypoints rather than independent individuals.", "Discrepancy between light state and occupancy: In C15, `master_bedroom_light` turns OFF at 22:50:36, yet `master_bedroom_occupancy` remains ON (1) consistently until 23:35+. Humans rarely sleep with lights on for 45+ minutes if they are 'occupied' the room in a way that triggers motion sensors repeatedly.", "Temperature fluctuation anomaly: Temperature readings show erratic jumps (e.g., Kitchen drops from 2273 to 2257 then back up) inconsistent with thermal mass response time, suggesting potential sensor spoofing or calibration drift exploited by an attacker.", "Low diversity in event types: 709% of signals are generic 'Occupancy', with almost no 'LockState', 'CurrentPosition', or 'SystemMode' changes despite high activity, indicating a lack of complex interaction data typical of real life."], "weaknesses": ["Could be explained by a poorly calibrated multi-zone HVAC system triggering occupancy sensors via air flow detection rather than physical presence.", "Household members could theoretically move in perfect lockstep, though the probability is statistically low without prior knowledge of the specific logging interval."]}], "most_discriminative_evidence": ["The exact repetition of the sequence: Entrance -> Dining -> Living/Master/Kids every 2 minutes across 12 hours of varied timestamps.", "The persistence of 'Occupancy=1' in the Master Bedroom after the bed light was turned off for over 40 minutes, contradicting expected human behavior.", "Absence of any lock state changes or door contact sensor alerts during the high-activity period, despite frequent entrance traffic."], "missing_information": ["Raw timestamp deltas between consecutive events for specific users/devices to confirm the 2-minute periodicity.", "Video feed or audio logs to verify actual presence versus sensor ghosting.", "Historical baseline data to determine if this 'synchronized' pattern is a known quirk of the specific sensor hardware model."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C01\", \"C02\", \"C03\"],\n  \"missing_checks\": [\n    \"Verify if the ~2-minute periodicity is consistent across all chunks or isolated to C00/C15/C16.\",\n    \"Check for 'LockState' and 'ContactSensor' events in the early morning/late night transition periods (C01-C03) to rule out intrusion.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identifies potential anomalies (synchronized occupancy, light/occupancy mismatch) based on the selected chunks.\",\n    \"However, the evidence is insufficient because it relies heavily on a limited sample (C00, C15, C16). The 'rigid synchronization' observed might be an artifact of specific time windows or sensor calibration quirks rather than a global pattern spanning the full 12 hours.\",\n    \"To confirm the hypothesis of 'simulated occupancy loop' vs 'hardware quirk', continuous data from the middle of the log (C01-C04) is required to verify if the periodicity persists uninterrupted.\",\n    \"Additionally, checking the start/end boundary chunks (C01-C03) is crucial to see if door locks or contact sensors were triggered during the high-activity phases mentioned in the anomaly hypothesis, which would contradict the 'intrusion simulation' theory if they were active.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C01", "C02", "C03"], "missing_checks": ["Verify if the ~2-minute periodicity is consistent across all chunks or isolated to C00/C15/C16.", "Check for 'LockState' and 'ContactSensor' events in the early morning/late night transition periods (C01-C03) to rule out intrusion."], "supervisor_notes": ["The analysis correctly identifies potential anomalies (synchronized occupancy, light/occupancy mismatch) based on the selected chunks.", "However, the evidence is insufficient because it relies heavily on a limited sample (C00, C15, C16). The 'rigid synchronization' observed might be an artifact of specific time windows or sensor calibration quirks rather than a global pattern spanning the full 12 hours.", "To confirm the hypothesis of 'simulated occupancy loop' vs 'hardware quirk', continuous data from the middle of the log (C01-C04) is required to verify if the periodicity persists uninterrupted.", "Additionally, checking the start/end boundary chunks (C01-C03) is crucial to see if door locks or contact sensors were triggered during the high-activity phases mentioned in the anomaly hypothesis, which would contradict the 'intrusion simulation' theory if they were active."]}, "preview_triage_prompt": "## Query\n以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Layout\nLayout: 三室两厅 (3BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kids_room: 儿童房温度传感器<temperature_sensor>, 儿童房灯<dimmable_light>, 儿童房窗帘<window_covering>, 儿童房窗户传感器<contact_sensor>, 儿童房运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅副灯<dimmable_light>, 客厅氛围灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘1<window_covering>, 客厅窗户传感器1<contact_sensor>, 客厅窗户传感器2<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n- master_bathroom: 主卫漏水传感器<water_leak_detector>, 主卫灯<onoff_light>, 主卫运动传感器<occupancy_sensor>\n- master_bedroom: 主卧床头灯<onoff_light>, 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>\n- second_bedroom: 次卧灯<dimmable_light>, 次卧空调<air_conditioner>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 234,\n    \"master_bedroom\": 291,\n    \"kids_room\": 293,\n    \"kitchen\": 153,\n    \"entrance\": 153,\n    \"dining_room\": 146,\n    \"second_bedroom\": 24,\n    \"master_bathroom\": 24\n  },\n  \"attribute_frequency\": {\n    \"Occupancy\": 709,\n    \"MeasuredValue\": 582,\n    \"OnOff\": 13,\n    \"StateValue\": 4,\n    \"LockState\": 3,\n    \"CurrentPositionLiftPercent100ths\": 2,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 3,\n  \"occupancy_events\": 709,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-16T11:55:00\",\n    \"end_ts\": \"2026-06-16T12:40:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 12,\n      \"master_bedroom\": 19,\n      \"kids_room\": 19,\n      \"kitchen\": 9,\n      \"entrance\": 9,\n      \"dining_room\": 9,\n      \"second_bedroom\": 2,\n      \"master_bathroom\": 1\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"kids_room_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"master_bedroom_occupancy\",\n      \"kids_room_occupancy\"\n    ]", "preview_verifier_prompt": "## Query\n以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Triage\n{\n  \"latent_task_profile\": \"behavior-sequence | single-event-safety\",\n  \"focus_rooms\": [\"living_room\", \"master_bedroom\", \"kids_room\", \"kitchen\"],\n  \"focus_devices\": [\"occupancy_sensor\", \"temperature_sensor\", \"door_lock\", \"contact_sensor\"],\n  \"focus_chunk_ids\": [\"C00\", \"C15\", \"C16\"],\n  \"suspected_patterns\": [\n    \"synchronized_multi-room_occupancy\",\n    \"cooling_cycle_drift\",\n    \"late_night_activity_anomaly\"\n  ],\n  \"why_these_chunks\": [\n    \"C00: Establishes baseline for high-frequency synchronized occupancy events across living, master, and kids rooms immediately after entry.\",\n    \"C15: Shows a specific state change (bedroom light OFF) amidst continued high activity, indicating a shift in routine or sleep onset while others remain active.\",\n    \"C16: Captures the tail end of the night with reduced event counts but persistent multi-room presence, requiring verification against expected 'night mode' behavior.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Standard family evening routine with synchronized dining and relaxation, followed by a shared sleep onset.\",\n      \"evidence\": [\"High frequency of occupancy events in living, master, and kids rooms (234-293 count) indicates active household presence.\", \"Synchronized temperature readings (~25°C) during daytime (C00) suggest consistent HVAC operation or ambient conditions.\", \"Evening logs (C15/C16) show coordinated movement: lights off in bedrooms while occupants remain active in common areas (entrance/dining).\", \"Occupancy patterns align with typical post-dinner wind-down where multiple family members occupy different zones before settling.\"],\n      \"weaknesses\": [\"Does not fully explain the extremely rigid synchronization of occupancy sensor flips (every ~2 mins across all sensors) which appears unnatural for organic human movement.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Coordinated intrusion or simulated occupancy loop designed to mimic normal family activity.\",\n      \"threat_type\": \"Social Engineering / Deception / Intrusion Simulation\",\n      \"evidence\": [\"Rigid temporal alignment: Occupancy sensors in distinct rooms (Living, Master, Kids, Entrance, Dining) trigger state changes with identical intervals (~2 minutes) throughout C00, C15, and C16. This suggests a single automated actor moving through pre-set waypoints rather than independent individ"}}
{"episode_id": "SQ3_TP_B_0457", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq3\\SQ3_TP_B_0457.json", "metadata": {"sq_type": "SQ3", "sq_name": "行为序列分析", "variant": "TP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "young_professional", "base_date": "2026-06-07T00:00:00", "seed": 20261086, "scenario_id": "INS-01", "total_events": 1572, "anomaly_events_count": 4}, "ground_truth": {"scenario_id": "INS-01", "scenario_name": "窗户入侵（夜间破窗）", "category": "intrusion", "is_anomaly": true, "threat_type": "intrusion", "key_evidence": ["深夜窗户传感器从 Closed 变 Open", "随后该房间运动传感器触发，但住户在卧室睡觉", "运动信号沿非住户房间传播"], "expected_response": "触发入侵警报，通知住户，记录事件", "difficulty_score": 9, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "second_bedroom", "injection_time": "2026-06-07T00:57:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"Systemic sensor data corruption or unit conversion failure resulting in physically impossible temperature readings (>2400) across all devices.\",\n  \"reasoning\": [\n    \"All temperature sensors report values consistently in the range of 2377 to 2918 throughout the entire 12-hour window, which is physically impossible for Celsius (requiring >2300°C) or Fahrenheit (>2500°F).\",\n    \"The anomaly affects every sensor type (living room, bedrooms, kitchen) simultaneously with identical magnitudes, indicating a systemic software error, configuration bug, or unit scaling issue (e.g., reporting milli-Kelvin as raw integer without division) rather than local hardware failure or environmental events.\",\n    \"Despite logical state changes such as turning off the cook surface at 12:51, the temperature values do not return to plausible baseline levels; instead, they remain in the erroneous high-thousands range before slowly drifting down, confirming a persistent data integrity issue.\"\n  ],\n  \"key_evidence\": [\n    \"Kitchen temperature spikes to 2918 immediately after cooking starts and remains above 2800 even after the cook surface is turned off, failing to show any realistic cooling curve.\",\n    \"Values like 2400-2410 observed in later chunks (C03) are still millions of times hotter than any residential environment, proving the data model is broken regardless of physical activity.\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately verify the 'MeasuredValue' unit definition in the system schema to confirm if it represents milli-Kelvin, scaled integers, or another non-standard format.\",\n    \"Reset the sensor calibration or reconfigure the logging pipeline to apply correct unit conversion factors before resuming automated safety protocols.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "Systemic sensor data corruption or unit conversion failure resulting in physically impossible temperature readings (>2400) across all devices.", "reasoning": ["All temperature sensors report values consistently in the range of 2377 to 2918 throughout the entire 12-hour window, which is physically impossible for Celsius (requiring >2300°C) or Fahrenheit (>2500°F).", "The anomaly affects every sensor type (living room, bedrooms, kitchen) simultaneously with identical magnitudes, indicating a systemic software error, configuration bug, or unit scaling issue (e.g., reporting milli-Kelvin as raw integer without division) rather than local hardware failure or environmental events.", "Despite logical state changes such as turning off the cook surface at 12:51, the temperature values do not return to plausible baseline levels; instead, they remain in the erroneous high-thousands range before slowly drifting down, confirming a persistent data integrity issue."], "key_evidence": ["Kitchen temperature spikes to 2918 immediately after cooking starts and remains above 2800 even after the cook surface is turned off, failing to show any realistic cooling curve.", "Values like 2400-2410 observed in later chunks (C03) are still millions of times hotter than any residential environment, proving the data model is broken regardless of physical activity."], "recommended_actions": ["Immediately verify the 'MeasuredValue' unit definition in the system schema to confirm if it represents milli-Kelvin, scaled integers, or another non-standard format.", "Reset the sensor calibration or reconfigure the logging pipeline to apply correct unit conversion factors before resuming automated safety protocols."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 56.861111879348755, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 839, "chunk_count": 11, "signals": {"room_activity": {"living_room": 291, "master_bedroom": 169, "second_bedroom": 169, "kitchen": 159, "entrance": 27, "bathroom": 24}, "attribute_frequency": {"MeasuredValue": 584, "Occupancy": 240, "OnOff": 9, "StateValue": 3, "OperationalState": 1, "LockState": 1}, "lock_state_flips": 1, "occupancy_events": 240, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"device-health | composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"living_room_temp_sensor\", \"kitchen_cook_surface\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\"],\n  \"suspected_patterns\": [\n    \"Sensor calibration drift (TemperatureMeasurement.MeasuredValue in thousands instead of Celsius)\",\n    \"Unexplained high alarm count relative to normal sensor traffic patterns\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunks C00 and C01 show the most extreme temperature anomalies (values like 2536, 2736) indicating a potential sensor failure or unit conversion error early in the log.\",\n    \"These chunks also exhibit the highest 'alarmish_count' ratios relative to event counts, suggesting system instability triggered by these data points.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "device-health | composite-safety", "focus_rooms": ["kitchen", "living_room"], "focus_devices": ["kitchen_temp_sensor", "living_room_temp_sensor", "kitchen_cook_surface"], "focus_chunk_ids": ["C00", "C01"], "suspected_patterns": ["Sensor calibration drift (TemperatureMeasurement.MeasuredValue in thousands instead of Celsius)", "Unexplained high alarm count relative to normal sensor traffic patterns"], "why_these_chunks": ["Chunks C00 and C01 show the most extreme temperature anomalies (values like 2536, 2736) indicating a potential sensor failure or unit conversion error early in the log.", "These chunks also exhibit the highest 'alarmish_count' ratios relative to event counts, suggesting system instability triggered by these data points."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The device logs represent a standard daily routine where the kitchen is actively used for cooking, causing elevated temperatures, while other rooms remain at ambient levels.\",\n      \"evidence\": [\n        \"Occupancy data shows consistent presence in the living room (27 events with value 1) and absence in bedrooms/entrance/bathroom during peak hours.\",\n        \"Kitchen temperature rises significantly from ~2500 to ~2900 after lights and cook surface are turned on (12:15 - 12:51), which aligns with expected thermal behavior for an active kitchen.\",\n        \"Temperature values stabilize and decrease towards the end of the log (C01) as cooking ceases.\"\n    ],\n    \"weaknesses\": [\n        \"The absolute temperature values (~2500-2900) are physically impossible for Celsius (implies >2500°C) or Fahrenheit (implies >2300°F). This suggests a fundamental data formatting or unit error rather than normal operation.\"\n    ]\n  },\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Sensor calibration failure or unit conversion error causing invalid high-value readings across all temperature sensors, potentially leading to false system alarms.\",\n      \"threat_type\": \"Data Integrity / False Positive Risk\",\n      \"evidence\": [\n        \"All temperature sensors report values in the range of 2400-2900 throughout the entire log, which is physically impossible for residential environments.\",\n        \"In Chunk C00, the kitchen sensor reads ~2918 immediately before and after the cook surface is turned off, failing to show a realistic cooling curve despite the event occurring at 12:51.\",\n        \"In Chunk C01, the kitchen sensor drops to ~2475, but this still represents an impossible physical state. The 'drop' might be a reset or a different type of error, not natural cooling.\",\n        \"Multiple sensors show identical or near-identical erroneous values simultaneously (e.g., all rooms reading ~2500 at specific timestamps), suggesting a systemic broadcast error or shared configuration bug rather than independent sensor failures.\"\n    ],\n    {\n      \"id\": \"A2\",\n      \"description\": \"Potential unauthorized device manipulation or spoofing attempting to mimic high-temperature conditions to trigger safety protocols.\",\n      \"threat_type\": \"Security Intrusion\",\n      \"evidence\": [\n        \"Sudden spike in 'MeasuredValue' magnitude coincides with user activity (light/cook surface activation), possibly indicating an automated script injecting data.\",\n        \"The persistence of these extreme values even when no heat source should exist (e.g., C01 where everything is off) suggests continuous injection rather than transient hardware noise.\"\n    ],\n    \"weaknesses\": [\n        \"There is no evidence of network intrusion attempts or packet injection in the raw chunks provided; the anomalies appear strictly within the sensor payload format.\",\n        \"The pattern of values changing smoothly (even if to impossible numbers) mimics sensor drift more closely than random spoofing artifacts.\"\n    ]\n  },\n  \"most_discriminative_evidence\": [\n    \"The simultaneous reporting of impossible temperature magnitudes (>2400) across spatially separated sensors (living room, bedrooms, kitchen) rules out local hardware damage and points to a systemic software/unit issue.\",\n    \"The lack of correlation between the 'OnOff' events (cooking stops at 12:51) and a rapid return to plausible physical temperatures in the subsequent logs indicates the data model itself is broken.\"\n  ],\n  \"missing_information\": [\n    \"Definition of the expected units for 'MeasuredValue' (e.g., is it milli-Kelvin? scaled integer?).\",\n    \"Previous baseline readings from prior hours to determine if this is a sudden onset or a chronic logging configuration error.\",\n    \"System alarm logs corresponding to these timestamps to verify if these invalid values triggered safety shutdowns or maintenance alerts.\"\n  ]\n}", "investigator_parsed": {"_parse_failed": true, "raw_preview": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The device logs represent a standard daily routine where the kitchen is actively used for cooking, causing elevated temperatures, while other rooms remain at ambient levels.\",\n      \"evidence\": [\n        \"Occupancy data shows consistent presence in the living room (27 events with value 1) and absence in bedrooms/entrance/bathroom during peak hours.\",\n        \"Kitchen temperature rises significantly from ~2500 to ~2900 after lights and cook surface are turned on (12:15 - 12:51), which aligns with expected thermal behavior for an active kitchen.\",\n        \"Temperature values stabilize and decrease towards the end of the log (C01) as cooking ceases.\"\n    ],\n    \"weaknesses\": [\n        \"The absolute temperature values (~2500-2900) are physically impossible for Celsius (implies >2500°C) or Fahrenheit (implies >2300°F). This suggests a fundamental data formatting or unit error rather than normal operation.\"\n    ]\n  },\n "}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C02\", \"C03\"],\n  \"missing_checks\": [\n    \"Verify unit definitions (milli-Kelvin vs Celsius) in system schema.\",\n    \"Retrieve alarm logs for timestamps corresponding to C00/C01 to confirm false positives.\"\n  ],\n  \"supervisor_notes\": [\n    \"The investigation correctly identified the core anomaly: physically impossible temperature values (>2400).\",\n    \"However, evidence is insufficient because it relies solely on Chunks C00 and C01. These chunks show the *onset* of the error but do not establish if this is a chronic configuration issue or a sudden glitch starting at hour 0.\",\n    \"Chunks C02 and C03 are needed to determine if the 'normal' baseline (if any) existed prior to the error or if the drift continued linearly across the full 12-hour window.\",\n    \"Without checking earlier chunks (relative to the log start), we cannot distinguish between a fresh deployment bug and a sudden network injection event.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C02", "C03"], "missing_checks": ["Verify unit definitions (milli-Kelvin vs Celsius) in system schema.", "Retrieve alarm logs for timestamps corresponding to C00/C01 to confirm false positives."], "supervisor_notes": ["The investigation correctly identified the core anomaly: physically impossible temperature values (>2400).", "However, evidence is insufficient because it relies solely on Chunks C00 and C01. These chunks show the *onset* of the error but do not establish if this is a chronic configuration issue or a sudden glitch starting at hour 0.", "Chunks C02 and C03 are needed to determine if the 'normal' baseline (if any) existed prior to the error or if the drift continued linearly across the full 12-hour window.", "Without checking earlier chunks (relative to the log start), we cannot distinguish between a fresh deployment bug and a sudden network injection event."]}, "preview_triage_prompt": "## Query\n以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 291,\n    \"master_bedroom\": 169,\n    \"second_bedroom\": 169,\n    \"kitchen\": 159,\n    \"entrance\": 27,\n    \"bathroom\": 24\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 584,\n    \"Occupancy\": 240,\n    \"OnOff\": 9,\n    \"StateValue\": 3,\n    \"OperationalState\": 1,\n    \"LockState\": 1\n  },\n  \"lock_state_flips\": 1,\n  \"occupancy_events\": 240,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-07T11:55:00\",\n    \"end_ts\": \"2026-06-07T13:00:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 27,\n      \"master_bedroom\": 15,\n      \"second_bedroom\": 15,\n      \"kitchen\": 19,\n      \"entrance\": 2,\n      \"bathroom\": 2\n    },\n    \"top_devices\": [\n      \"kitchen_temp_sensor\",\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"living_room_occupancy\",\n      \"master_bedroom_occupancy\"\n    ],\n    \"alarmish_count\": 21,\n    \"preview_lines\": [\n      \"[2026-06-07T11:55:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2536\",\n      \"[2026-06-07T11:55:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2532\",\n      \"[2026-06-07T11:55:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2528\",\n      \"[2026-06-07T11:55:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2535\",\n      \"[2026-06-07T11:58:00] living_room_occupancy | OccupancySensing.Occupancy = 1\",\n      \"[2026-", "preview_verifier_prompt": "## Query\n以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Triage\n{\n  \"latent_task_profile\": \"device-health | composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"living_room_temp_sensor\", \"kitchen_cook_surface\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\"],\n  \"suspected_patterns\": [\n    \"Sensor calibration drift (TemperatureMeasurement.MeasuredValue in thousands instead of Celsius)\",\n    \"Unexplained high alarm count relative to normal sensor traffic patterns\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunks C00 and C01 show the most extreme temperature anomalies (values like 2536, 2736) indicating a potential sensor failure or unit conversion error early in the log.\",\n    \"These chunks also exhibit the highest 'alarmish_count' ratios relative to event counts, suggesting system instability triggered by these data points.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The device logs represent a standard daily routine where the kitchen is actively used for cooking, causing elevated temperatures, while other rooms remain at ambient levels.\",\n      \"evidence\": [\n        \"Occupancy data shows consistent presence in the living room (27 events with value 1) and absence in bedrooms/entrance/bathroom during peak hours.\",\n        \"Kitchen temperature rises significantly from ~2500 to ~2900 after lights and cook surface are turned on (12:15 - 12:51), which aligns with expected thermal behavior for an active kitchen.\",\n        \"Temperature values stabilize and decrease towards the end of the log (C01) as cooking ceases.\"\n    ],\n    \"weaknesses\": [\n        \"The absolute temperature values (~2500-2900) are physically impossible for Celsius (implies >2500°C) or Fahrenheit (implies >2300°F). This suggests a fundamental data formatting or unit error rather than normal operation.\"\n    ]\n  },\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Sensor calibration failure or unit conversion error causing invalid high-value readings across all temperature sensors, potentially leading to false system alarms.\",\n      \"threat_type\": \"Data Integrity / False Positive Risk\",\n      \"evidence\": [\n        \"All temperature sensors report values in the range of 2400-2900 throughout the entire log, which is physically impossible for residential environments.\",\n        \"In Chunk C00, the kitchen sensor reads ~2918 immediately before and after the cook surface is turned off, failing to "}}
{"episode_id": "SQ3_TP_C_0447", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq3\\SQ3_TP_C_0447.json", "metadata": {"sq_type": "SQ3", "sq_name": "行为序列分析", "variant": "TP", "layout_id": "C", "layout_name": "三室两厅 (3BR)", "profile_id": "family_with_children", "base_date": "2026-06-28T00:00:00", "seed": 20261076, "scenario_id": "CH-02", "total_events": 1492, "anomaly_events_count": 4}, "ground_truth": {"scenario_id": "CH-02", "scenario_name": "儿童进入危险区域操作危险设备", "category": "child_specific", "is_anomaly": true, "threat_type": "child_safety", "key_evidence": ["活动轨迹：儿童房 → 厨房", "厨房灶具被开启", "无成人在厨房（厨房 occupancy 信号模式+其他房间的 occupancy 信号表明成人不在厨房）", "如果灶具有 OffOnly 限制，理论上不能远程开启——这意味着是物理操作"], "expected_response": "立即通知家长，如可能则远程关闭灶具（OffOnly命令）", "difficulty_score": 10, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 3, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "kitchen", "injection_time": "2026-06-28T02:50:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"Systemic sensor data integrity failure where all temperature sensors report values scaled by a factor of 10 and exhibit unrealistic synchronized drift, failing to reflect actual environmental variance.\",\n  \"reasoning\": [\n      \"Analysis of the raw logs reveals temperature values consistently in the range of 2263-2554, which are physically impossible for indoor Celsius readings but align perfectly with typical room temperatures (22.6°C - 25.5°C) when divided by 10.\",\n      \"Despite distinct activities such as cooking in the kitchen at 02:51:30 (Chunk C02), the temperature readings for the kitchen and other rooms remain nearly identical (within ~5 units), lacking the expected thermal divergence caused by heat generation.\",\n      \"The data exhibits high-frequency synchronization across geographically separated devices (living room, master bedroom, kitchen, kids room) that would naturally experience different thermal dynamics, indicating a shared software artifact, unit conversion error, or calibration drift rather than real-world physics.\",\n      \"Occupancy sensors function normally (detecting presence/absence events), proving the hardware is functional and isolating the anomaly specifically to the temperature measurement logic.\"\n    ],\n  \"key_evidence\": [\n      \"Raw 'MeasuredValue' entries like 2389 vs 23.89°C; division by 10 yields valid ambient temperatures.\",\n      \"At 02:51:30, the kitchen cook surface turned ON, yet temperature readings across all rooms remained within a 1-degree margin (e.g., Kitchen 2378 vs Living Room 2389).\",\n      \"All four focus rooms update simultaneously every 5 minutes with near-perfect correlation, demonstrating a systemic feed artifact or configuration error.\"\n    ],\n  \"recommended_actions\": [\n      \"Immediately review device driver configuration logs to verify if a 'scale_factor' parameter was inadvertently set to 10 instead of 1.\",\n      \"Check historical baseline data from previous days to determine if this scaling issue is a new anomaly or a legacy misconfiguration present since deployment.\",\n      \"Contact the IoT vendor support to push a firmware patch or configuration reset for the temperature sensor suite to restore correct unit reporting.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "Systemic sensor data integrity failure where all temperature sensors report values scaled by a factor of 10 and exhibit unrealistic synchronized drift, failing to reflect actual environmental variance.", "reasoning": ["Analysis of the raw logs reveals temperature values consistently in the range of 2263-2554, which are physically impossible for indoor Celsius readings but align perfectly with typical room temperatures (22.6°C - 25.5°C) when divided by 10.", "Despite distinct activities such as cooking in the kitchen at 02:51:30 (Chunk C02), the temperature readings for the kitchen and other rooms remain nearly identical (within ~5 units), lacking the expected thermal divergence caused by heat generation.", "The data exhibits high-frequency synchronization across geographically separated devices (living room, master bedroom, kitchen, kids room) that would naturally experience different thermal dynamics, indicating a shared software artifact, unit conversion error, or calibration drift rather than real-world physics.", "Occupancy sensors function normally (detecting presence/absence events), proving the hardware is functional and isolating the anomaly specifically to the temperature measurement logic."], "key_evidence": ["Raw 'MeasuredValue' entries like 2389 vs 23.89°C; division by 10 yields valid ambient temperatures.", "At 02:51:30, the kitchen cook surface turned ON, yet temperature readings across all rooms remained within a 1-degree margin (e.g., Kitchen 2378 vs Living Room 2389).", "All four focus rooms update simultaneously every 5 minutes with near-perfect correlation, demonstrating a systemic feed artifact or configuration error."], "recommended_actions": ["Immediately review device driver configuration logs to verify if a 'scale_factor' parameter was inadvertently set to 10 instead of 1.", "Check historical baseline data from previous days to determine if this scaling issue is a new anomaly or a legacy misconfiguration present since deployment.", "Contact the IoT vendor support to push a firmware patch or configuration reset for the temperature sensor suite to restore correct unit reporting."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 61.61056137084961, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1492, "chunk_count": 19, "signals": {"room_activity": {"living_room": 337, "master_bedroom": 336, "kids_room": 338, "kitchen": 289, "dining_room": 48, "second_bedroom": 48, "master_bathroom": 48, "entrance": 48}, "attribute_frequency": {"MeasuredValue": 1152, "Occupancy": 339, "OnOff": 1}, "lock_state_flips": 0, "occupancy_events": 339, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"device-health | single-event-safety\",\n  \"focus_rooms\": [\"living_room\", \"master_bedroom\", \"kids_room\", \"kitchen\"],\n  \"focus_devices\": [\"living_room_temp_sensor\", \"master_bedroom_temp_sensor\", \"kids_room_temp_sensor\", \"kitchen_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\", \"C05\", \"C06\", \"C07\", \"C08\", \"C09\", \"C10\", \"C11\", \"C12\", \"C13\", \"C14\", \"C15\", \"C16\", \"C17\", \"C18\"],\n  \"suspected_patterns\": [\n    \"Temperature values are scaled by a factor of 10 (e.g., 22.7°C reported as 227), indicating a sensor configuration or unit conversion error.\",\n    \"All temperature sensors report nearly identical, synchronized readings across different rooms despite varying times and potential HVAC activity, suggesting a shared calibration drift or data feed artifact rather than real environmental conditions.\",\n    \"No occupancy events trigger device actions (lights/AC) correlating with the high 'alarmish_count' generated by the anomalous temperature spikes.\"\n  ],\n  \"why_these_chunks\": \"Every chunk from C00 to C18 displays the same pattern: `temperature_sensor` devices reporting values in the 2200-2500 range while all `occupancy_sensing` devices simultaneously report `0`. This pervasive correlation across the entire 24-hour timeline points to a systemic logging or sensor calibration issue affecting the specific room types selected for monitoring, rather than isolated security breaches.\"\n}", "triage_parsed": {"latent_task_profile": "device-health | single-event-safety", "focus_rooms": ["living_room", "master_bedroom", "kids_room", "kitchen"], "focus_devices": ["living_room_temp_sensor", "master_bedroom_temp_sensor", "kids_room_temp_sensor", "kitchen_temp_sensor"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04", "C05", "C06", "C07", "C08", "C09", "C10", "C11", "C12", "C13", "C14", "C15", "C16", "C17", "C18"], "suspected_patterns": ["Temperature values are scaled by a factor of 10 (e.g., 22.7°C reported as 227), indicating a sensor configuration or unit conversion error.", "All temperature sensors report nearly identical, synchronized readings across different rooms despite varying times and potential HVAC activity, suggesting a shared calibration drift or data feed artifact rather than real environmental conditions.", "No occupancy events trigger device actions (lights/AC) correlating with the high 'alarmish_count' generated by the anomalous temperature spikes."], "why_these_chunks": "Every chunk from C00 to C18 displays the same pattern: `temperature_sensor` devices reporting values in the 2200-2500 range while all `occupancy_sensing` devices simultaneously report `0`. This pervasive correlation across the entire 24-hour timeline points to a systemic logging or sensor calibration issue affecting the specific room types selected for monitoring, rather than isolated security breaches."}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The system is logging valid temperature data where the 'MeasuredValue' field represents millidegrees Celsius (e.g., 2271 = 22.71°C) and occupancy sensors correctly report empty rooms.\",\n      \"evidence\": [\"Temperature values in range 2200-2500 align with typical indoor ambient temperatures when divided by 10.\", \"Occupancy events (e.g., C02 at 02:51:15) show transient presence consistent with human activity.\"],\n      \"weaknesses\": [\"If this were true, the raw log format should indicate units (e.g., mC), but standard IoT logs usually default to integer degrees unless specified. The sheer consistency of all sensors being within ~40 units of each other despite different room functions (kitchen vs bedroom) suggests a lack of thermal variance expected in reality.\"],\n      \"threat_type\": null\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Systemic Sensor Calibration/Unit Conversion Failure: All temperature sensors are reporting values scaled by a factor of 10 (likely intended as °C but logged as x10 integers), creating false 'high heat' alerts if thresholding logic expects raw integers.\",\n      \"evidence\": [\"All sensors report values between 2263 and 2492 across 6 hours. Dividing by 10 yields 22.6°C - 24.9°C, which is physically plausible for an indoor environment during summer.\", \"The lack of significant variance between rooms (e.g., Kitchen vs Master Bedroom staying within 1-2 'degrees' even while cooking occurs) indicates a shared software artifact or calibration drift rather than distinct environmental physics.\", \"No lock state flips or alarm triggers occurred despite these readings persisting, suggesting the system may have a hard-coded unit conversion layer that isn't failing catastrophically but is displaying misleading raw data.\"],\n      \"weaknesses\": [\"Could be a localized sensor firmware bug affecting only these specific nodes if they share a driver version, though the cross-room correlation makes a global config error more likely.\", \"Does not explain why Occupancy events still trigger occasionally (e.g., C02 02:51), proving the occupancy hardware/logic is functional and independent of the temperature scaling issue.\"],\n      \"threat_type\": \"Device Health / Data Integrity\"\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Data Feed Artifact / Shared Clock Sync Error: Sensors are reading from a single, corrupted feed or clock source causing synchronized drift and unrealistic stability.\",\n      \"evidence\": [\"Simultaneous updates across all four focus rooms occur every 5 minutes with near-perfect temporal alignment.\", \"Values fluctuate in unison (e.g., C00 00:35 all jump to ~2287), lacking the stochastic noise expected from independent physical thermocouples.\"],\n      \"weaknesses\": [\"Physical environments do change; the kitchen should heat up faster than the master bedroom due to cooking (seen at 02:51). The fact that they track so closely suggests the *source* of the data is the same corrupted entity, not just independent sensors failing identically.\"],\n      \"threat_type\": \"Infrastructure / Data Pipeline\"\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"In Chunk C02 (02:51:30), the 'kitchen_cook_surface' turns ON, yet the temperature readings for the kitchen and living room remain nearly identical (~2367 vs ~2366) instead of showing a rapid divergence characteristic of active heating.\",\n    \"The absolute difference between the maximum and minimum reported values across any single timestamp is rarely greater than 5-10 units, whereas real-world residential thermostats typically vary by 10-20+ degrees between a sunlit living room and a shaded bedroom.\",\n    \"Division of all 'MeasuredValue' entries by 10 results in a perfect Gaussian distribution centered around 23.5°C, strongly implying a unit conversion logic error (x10 multiplier) rather than actual extreme heat.\"\n  ],\n  \"missing_information\": [\n    \"The expected unit definition for 'MeasuredValue' in the device schema (is it supposed to be °C, °F, or mC?).\",\n    \"Historical baseline data to confirm if this scaling happened recently or has been present since deployment.\",\n    \"Configuration logs for the temperature sensor drivers to verify if a 'scale_factor' parameter was inadvertently changed.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The system is logging valid temperature data where the 'MeasuredValue' field represents millidegrees Celsius (e.g., 2271 = 22.71°C) and occupancy sensors correctly report empty rooms.", "evidence": ["Temperature values in range 2200-2500 align with typical indoor ambient temperatures when divided by 10.", "Occupancy events (e.g., C02 at 02:51:15) show transient presence consistent with human activity."], "weaknesses": ["If this were true, the raw log format should indicate units (e.g., mC), but standard IoT logs usually default to integer degrees unless specified. The sheer consistency of all sensors being within ~40 units of each other despite different room functions (kitchen vs bedroom) suggests a lack of thermal variance expected in reality."], "threat_type": null}], "anomaly_hypotheses": [{"id": "A1", "description": "Systemic Sensor Calibration/Unit Conversion Failure: All temperature sensors are reporting values scaled by a factor of 10 (likely intended as °C but logged as x10 integers), creating false 'high heat' alerts if thresholding logic expects raw integers.", "evidence": ["All sensors report values between 2263 and 2492 across 6 hours. Dividing by 10 yields 22.6°C - 24.9°C, which is physically plausible for an indoor environment during summer.", "The lack of significant variance between rooms (e.g., Kitchen vs Master Bedroom staying within 1-2 'degrees' even while cooking occurs) indicates a shared software artifact or calibration drift rather than distinct environmental physics.", "No lock state flips or alarm triggers occurred despite these readings persisting, suggesting the system may have a hard-coded unit conversion layer that isn't failing catastrophically but is displaying misleading raw data."], "weaknesses": ["Could be a localized sensor firmware bug affecting only these specific nodes if they share a driver version, though the cross-room correlation makes a global config error more likely.", "Does not explain why Occupancy events still trigger occasionally (e.g., C02 02:51), proving the occupancy hardware/logic is functional and independent of the temperature scaling issue."], "threat_type": "Device Health / Data Integrity"}, {"id": "A2", "description": "Data Feed Artifact / Shared Clock Sync Error: Sensors are reading from a single, corrupted feed or clock source causing synchronized drift and unrealistic stability.", "evidence": ["Simultaneous updates across all four focus rooms occur every 5 minutes with near-perfect temporal alignment.", "Values fluctuate in unison (e.g., C00 00:35 all jump to ~2287), lacking the stochastic noise expected from independent physical thermocouples."], "weaknesses": ["Physical environments do change; the kitchen should heat up faster than the master bedroom due to cooking (seen at 02:51). The fact that they track so closely suggests the *source* of the data is the same corrupted entity, not just independent sensors failing identically."], "threat_type": "Infrastructure / Data Pipeline"}], "most_discriminative_evidence": ["In Chunk C02 (02:51:30), the 'kitchen_cook_surface' turns ON, yet the temperature readings for the kitchen and living room remain nearly identical (~2367 vs ~2366) instead of showing a rapid divergence characteristic of active heating.", "The absolute difference between the maximum and minimum reported values across any single timestamp is rarely greater than 5-10 units, whereas real-world residential thermostats typically vary by 10-20+ degrees between a sunlit living room and a shaded bedroom.", "Division of all 'MeasuredValue' entries by 10 results in a perfect Gaussian distribution centered around 23.5°C, strongly implying a unit conversion logic error (x10 multiplier) rather than actual extreme heat."], "missing_information": ["The expected unit definition for 'MeasuredValue' in the device schema (is it supposed to be °C, °F, or mC?).", "Historical baseline data to confirm if this scaling happened recently or has been present since deployment.", "Configuration logs for the temperature sensor drivers to verify if a 'scale_factor' parameter was inadvertently changed."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C03\", \"C05\"],\n  \"missing_checks\": [\n    \"Verify historical baseline data to determine if the x10 scaling is a new anomaly or a legacy configuration.\",\n    \"Check device driver configuration logs for any recent changes to the 'scale_factor' parameter.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identifies the unit conversion error (x10 scaling) and the lack of thermal variance as key anomalies. However, the current evidence relies entirely on the assumption that these specific chunks represent a continuous timeline or random sample without verifying the temporal distribution of events across all 24 hours.\",\n    \"Requesting chunks C03 and C05 will help verify if the 'synchronized drift' persists in different time windows, ruling out isolated software glitches and confirming a systemic feed artifact.\",\n    \"The 'missing_information' section highlights a critical gap: we need to know when this behavior started. Without historical context or config logs, we cannot distinguish between a sudden attack/data corruption and a pre-existing misconfiguration.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C03", "C05"], "missing_checks": ["Verify historical baseline data to determine if the x10 scaling is a new anomaly or a legacy configuration.", "Check device driver configuration logs for any recent changes to the 'scale_factor' parameter."], "supervisor_notes": ["The analysis correctly identifies the unit conversion error (x10 scaling) and the lack of thermal variance as key anomalies. However, the current evidence relies entirely on the assumption that these specific chunks represent a continuous timeline or random sample without verifying the temporal distribution of events across all 24 hours.", "Requesting chunks C03 and C05 will help verify if the 'synchronized drift' persists in different time windows, ruling out isolated software glitches and confirming a systemic feed artifact.", "The 'missing_information' section highlights a critical gap: we need to know when this behavior started. Without historical context or config logs, we cannot distinguish between a sudden attack/data corruption and a pre-existing misconfiguration."]}, "preview_triage_prompt": "## Query\n以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Layout\nLayout: 三室两厅 (3BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kids_room: 儿童房温度传感器<temperature_sensor>, 儿童房灯<dimmable_light>, 儿童房窗帘<window_covering>, 儿童房窗户传感器<contact_sensor>, 儿童房运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅副灯<dimmable_light>, 客厅氛围灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘1<window_covering>, 客厅窗户传感器1<contact_sensor>, 客厅窗户传感器2<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n- master_bathroom: 主卫漏水传感器<water_leak_detector>, 主卫灯<onoff_light>, 主卫运动传感器<occupancy_sensor>\n- master_bedroom: 主卧床头灯<onoff_light>, 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>\n- second_bedroom: 次卧灯<dimmable_light>, 次卧空调<air_conditioner>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 337,\n    \"master_bedroom\": 336,\n    \"kids_room\": 338,\n    \"kitchen\": 289,\n    \"dining_room\": 48,\n    \"second_bedroom\": 48,\n    \"master_bathroom\": 48,\n    \"entrance\": 48\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1152,\n    \"Occupancy\": 339,\n    \"OnOff\": 1\n  },\n  \"lock_state_flips\": 0,\n  \"occupancy_events\": 339,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-28T00:00:00\",\n    \"end_ts\": \"2026-06-28T01:10:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 18,\n      \"master_bedroom\": 18,\n      \"kids_room\": 18,\n      \"kitchen\": 14,\n      \"dining_room\": 3,\n      \"second_bedroom\": 3,\n      \"master_bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"kids_room_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"dining_room_occupancy\"\n    ],\n    \"alarmish_count\": 21,\n    \"preview_lines\": [\n      \"[2026-06-28T00:00:00] living_room_temp_sensor | TemperatureMeasurement.Measu", "preview_verifier_prompt": "## Query\n以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Triage\n{\n  \"latent_task_profile\": \"device-health | single-event-safety\",\n  \"focus_rooms\": [\"living_room\", \"master_bedroom\", \"kids_room\", \"kitchen\"],\n  \"focus_devices\": [\"living_room_temp_sensor\", \"master_bedroom_temp_sensor\", \"kids_room_temp_sensor\", \"kitchen_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\", \"C05\", \"C06\", \"C07\", \"C08\", \"C09\", \"C10\", \"C11\", \"C12\", \"C13\", \"C14\", \"C15\", \"C16\", \"C17\", \"C18\"],\n  \"suspected_patterns\": [\n    \"Temperature values are scaled by a factor of 10 (e.g., 22.7°C reported as 227), indicating a sensor configuration or unit conversion error.\",\n    \"All temperature sensors report nearly identical, synchronized readings across different rooms despite varying times and potential HVAC activity, suggesting a shared calibration drift or data feed artifact rather than real environmental conditions.\",\n    \"No occupancy events trigger device actions (lights/AC) correlating with the high 'alarmish_count' generated by the anomalous temperature spikes.\"\n  ],\n  \"why_these_chunks\": \"Every chunk from C00 to C18 displays the same pattern: `temperature_sensor` devices reporting values in the 2200-2500 range while all `occupancy_sensing` devices simultaneously report `0`. This pervasive correlation across the entire 24-hour timeline points to a systemic logging or sensor calibration issue affecting the specific room types selected for monitoring, rather than isolated security breaches.\"\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The system is logging valid temperature data where the 'MeasuredValue' field represents millidegrees Celsius (e.g., 2271 = 22.71°C) and occupancy sensors correctly report empty rooms.\",\n      \"evidence\": [\"Temperature values in range 2200-2500 align with typical indoor ambient temperatures when divided by 10.\", \"Occupancy events (e.g., C02 at 02:51:15) show transient presence consistent with human activity.\"],\n      \"weaknesses\": [\"If this were true, the raw log format should indicate units (e.g., mC), but standard IoT logs usually default to integer degrees unless specified. The sheer consistency of all sensors being within ~40 units of each other despite different room functions (kitchen vs bedroom) suggests a lack of thermal variance expected in reality.\"],\n      \"threat_type\": null\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Systemic Sensor Calibration"}}
{"episode_id": "SQ3_TP_D_0443", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq3\\SQ3_TP_D_0443.json", "metadata": {"sq_type": "SQ3", "sq_name": "行为序列分析", "variant": "TP", "layout_id": "D", "layout_name": "独居老人 (Elderly Living Alone)", "profile_id": "elderly_living_alone", "base_date": "2026-06-18T00:00:00", "seed": 20261072, "scenario_id": "EL-07", "total_events": 1851, "anomaly_events_count": 1}, "ground_truth": {"scenario_id": "EL-07", "scenario_name": "长时间未归家", "category": "elderly_specific", "is_anomaly": true, "threat_type": "abnormal_inactivity", "key_evidence": ["出门时间已知（LockOperation 事件）", "预期回家时间已过但无 LockOperation 解锁事件", "偏离日常规律超过1小时"], "expected_response": "9:30开始尝试联系，10:00后联系紧急联系人", "difficulty_score": 11, "difficulty_level": 3, "difficulty_label": "L3_composite_reasoning", "difficulty_dimensions": {"D1_evidence_count": 1, "D2_signal_directness": 3, "D3_cross_device": 1, "D4_temporal_span": 3, "D5_fp_similarity": 3}, "target_room": "living_room", "injection_time": "2026-06-18T16:11:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"medium\",\n  \"threat_type\": \"possible_fall\",\n  \"threat_description\": \"The bathroom occupancy sensor repeatedly reports zero while other rooms show high activity and residents are awake at night, suggesting a resident may be trapped inside the bathroom or unable to exit due to an incident.\",\n  \"reasoning\": [\n      \"Analysis of chunks C12 and C13 reveals that between 22:47 and 23:55, the bathroom occupancy sensor consistently drops to '0' multiple times.\",\n      \"Contrastingly, during these exact same timestamps, sensors in the living room, kitchen, and bedroom report continuous occupancy (value '1'), indicating residents are mobile and active elsewhere in the home.\",\n      \"In a single-occupant scenario, this pattern is impossible; in a multi-occupant scenario, it implies one person has ceased using the bathroom entirely or is isolated within it without exiting for extended periods despite others being present.\",\n      \"The lack of correlation between the bathroom emptiness and movement patterns in common areas suggests the subject is not simply leaving the house but is stuck or incapacitated within the bathroom space.\",\n      \"Temperature data confirms the environment is stable, ruling out rapid cooling as a cause for absence, further pointing towards a human factor issue like a fall.\"\n  ],\n  \"key_evidence\": [\n      \"Timestamp 22:47:43 in C12: Bathroom=0 while Living_Room=1 and Kitchen=1 simultaneously.\",\n      \"Timestamp 23:47:43 in C13: Repeated occurrence of Bathroom=0 while general household occupancy remains high.\",\n      \"No corresponding door lock state changes or entrance egress events observed during these specific bathroom gaps.\"\n  ],\n  \"recommended_actions\": [\n      \"Immediately verify the physical status of the resident(s) via video feed if available or by knocking on the bathroom door.\",\n      \"Check the state of the bathroom door lock to determine if the door is locked from the inside, which would indicate a trapped individual.\",\n      \"Review historical logs to confirm if this specific pattern (bathroom=0 with others=1) is a recurring anomaly or part of normal multi-person routine.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "medium", "threat_type": "possible_fall", "threat_description": "The bathroom occupancy sensor repeatedly reports zero while other rooms show high activity and residents are awake at night, suggesting a resident may be trapped inside the bathroom or unable to exit due to an incident.", "reasoning": ["Analysis of chunks C12 and C13 reveals that between 22:47 and 23:55, the bathroom occupancy sensor consistently drops to '0' multiple times.", "Contrastingly, during these exact same timestamps, sensors in the living room, kitchen, and bedroom report continuous occupancy (value '1'), indicating residents are mobile and active elsewhere in the home.", "In a single-occupant scenario, this pattern is impossible; in a multi-occupant scenario, it implies one person has ceased using the bathroom entirely or is isolated within it without exiting for extended periods despite others being present.", "The lack of correlation between the bathroom emptiness and movement patterns in common areas suggests the subject is not simply leaving the house but is stuck or incapacitated within the bathroom space.", "Temperature data confirms the environment is stable, ruling out rapid cooling as a cause for absence, further pointing towards a human factor issue like a fall."], "key_evidence": ["Timestamp 22:47:43 in C12: Bathroom=0 while Living_Room=1 and Kitchen=1 simultaneously.", "Timestamp 23:47:43 in C13: Repeated occurrence of Bathroom=0 while general household occupancy remains high.", "No corresponding door lock state changes or entrance egress events observed during these specific bathroom gaps."], "recommended_actions": ["Immediately verify the physical status of the resident(s) via video feed if available or by knocking on the bathroom door.", "Check the state of the bathroom door lock to determine if the door is locked from the inside, which would indicate a trapped individual.", "Review historical logs to confirm if this specific pattern (bathroom=0 with others=1) is a recurring anomaly or part of normal multi-person routine."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": true, "reasoning_steps": 5, "has_evidence": true, "has_actions": true, "confidence": "medium"}, "latency": 58.517009973526, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1060, "chunk_count": 14, "signals": {"room_activity": {"living_room": 294, "bedroom": 296, "kitchen": 295, "entrance": 147, "bathroom": 28}, "attribute_frequency": {"Occupancy": 606, "MeasuredValue": 437, "OnOff": 10, "CurrentPositionLiftPercent100ths": 3, "CurrentLevel": 1, "StateValue": 1, "LockState": 1}, "lock_state_flips": 1, "occupancy_events": 606, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"behavior-sequence | composite-safety\",\n  \"focus_rooms\": [\n    \"bedroom\",\n    \"entrance\",\n    \"bathroom\"\n  ],\n  \"focus_devices\": [\n    \"bedroom_occupancy_sensor\",\n    \"entrance_contact_sensor\",\n    \"entrance_door_lock\",\n    \"bathroom_occupancy_sensor\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C03\",\n    \"C04\",\n    \"C12\",\n    \"C13\"\n  ],\n  \"suspected_patterns\": [\n    \"Nocturnal absence detection: Subject may have left the bedroom and entrance area during early morning hours (approx. 05:00-07:00 based on timestamp gaps in activity) while sleeping elsewhere or being absent.\",\n    \"Risky bathroom access: Bathroom occupancy drops to zero multiple times without immediate re-entry correlation, potentially indicating a fall or inability to exit/enter.\",\n    \"Temperature gradient anomaly: Bedroom temperature consistently lower than living/kitchen areas, possibly due to closed windows or AC, but needs verification against occupancy status.\"\n  ],\n  \"why_these_chunks\": [\n    \"C03/C04 show the transition period where entrance activity is high but bathroom becomes empty, suggesting movement out of the home or deep sleep cycles.\",\n    \"C12/C13 capture the late-night/early-morning window where bathroom occupancy briefly hits zero while other rooms remain active, a critical time for fall detection in elderly monitoring.\",\n    \"These chunks highlight the 'absence' events which are the primary trigger for safety alerts in this profile.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "behavior-sequence | composite-safety", "focus_rooms": ["bedroom", "entrance", "bathroom"], "focus_devices": ["bedroom_occupancy_sensor", "entrance_contact_sensor", "entrance_door_lock", "bathroom_occupancy_sensor"], "focus_chunk_ids": ["C03", "C04", "C12", "C13"], "suspected_patterns": ["Nocturnal absence detection: Subject may have left the bedroom and entrance area during early morning hours (approx. 05:00-07:00 based on timestamp gaps in activity) while sleeping elsewhere or being absent.", "Risky bathroom access: Bathroom occupancy drops to zero multiple times without immediate re-entry correlation, potentially indicating a fall or inability to exit/enter.", "Temperature gradient anomaly: Bedroom temperature consistently lower than living/kitchen areas, possibly due to closed windows or AC, but needs verification against occupancy status."], "why_these_chunks": ["C03/C04 show the transition period where entrance activity is high but bathroom becomes empty, suggesting movement out of the home or deep sleep cycles.", "C12/C13 capture the late-night/early-morning window where bathroom occupancy briefly hits zero while other rooms remain active, a critical time for fall detection in elderly monitoring.", "These chunks highlight the 'absence' events which are the primary trigger for safety alerts in this profile."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Standard multi-person household activity with staggered bathroom usage and consistent thermal gradients.\",\n      \"evidence\": [\n        \"High occupancy counts in living_room (294), bedroom (296), and kitchen (295) vs low in bathroom (28), indicating multiple residents distributed throughout the house.\",\n        \"Temperature data shows a stable, logical gradient: Kitchen/Living (~24°C/2450k) > Bedroom (~23°C/2350k), consistent with heating distribution or room function.\",\n        \"Bathroom occupancy drops to zero (C03, C04, C12, C13) while other rooms remain active, which is normal for sequential use by different individuals.\"\n    ]\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Sustained 'Ghost' Absence in Bathroom during Night Hours despite High Activity Elsewhere.\",\n      \"threat_type\": \"Safety/Fall Risk\",\n      \"evidence\": [\n        \"In Chunk C12 (22:47-23:42) and C13 (23:43-23:55), total home occupancy remains high (Living/Kitchen/Bedroom all report '1'), yet bathroom occupancy hits '0' at 22:47:43 and 23:47:43.\",\n        \"Unlike daytime chunks (C03/C04) where bathroom emptiness coincides with movement to other areas, nighttime emptiness occurs while the subject is clearly awake and mobile in common areas.\",\n        \"This pattern suggests a resident may be unable to reach the bathroom, is trapped inside it (sensor blind spot), or has ceased using it entirely due to distress/sleeping elsewhere, creating a safety gap.\"\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The temporal disconnect in C12/C13: Bathroom=0 occurs simultaneously with Living_Room=1 and Kitchen=1. In a single-resident scenario, this would imply impossible simultaneous presence; in a multi-resident scenario, it implies one person is isolated in the bathroom without exiting for an extended period or unable to exit.\",\n    \"Temperature stability in the bedroom (approx 21.5-21.7°C) during night hours confirms the subject was likely sleeping there, making the lack of bathroom visits during waking hours (as evidenced by kitchen/living activity) highly suspicious.\"\n  ],\n  \"missing_information\": [\n    \"Total number of expected residents (to validate if multiple people account for the bathroom gaps).\",\n    \"Duration thresholds: How long must bathroom occupancy remain zero before triggering an alert? (Current logs show ~1 hour gaps).\",\n    \"Door lock states for the bathroom (if locked from inside, this changes the threat profile to 'trapped' rather than 'avoidance').\"\n  ]\n}", "investigator_parsed": {"_parse_failed": true, "raw_preview": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Standard multi-person household activity with staggered bathroom usage and consistent thermal gradients.\",\n      \"evidence\": [\n        \"High occupancy counts in living_room (294), bedroom (296), and kitchen (295) vs low in bathroom (28), indicating multiple residents distributed throughout the house.\",\n        \"Temperature data shows a stable, logical gradient: Kitchen/Living (~24°C/2450k) > Bedroom (~23°C/2350k), consistent with heating distribution or room function.\",\n        \"Bathroom occupancy drops to zero (C03, C04, C12, C13) while other rooms remain active, which is normal for sequential use by different individuals.\"\n    ]\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Sustained 'Ghost' Absence in Bathroom during Night Hours despite High Activity Elsewhere.\",\n      \"threat_type\": \"Safety/Fall Risk\",\n      \"evidence\": [\n        \"In Chunk C12 (22:47-23:42) and C13 (23:43-23:55),"}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C05\", \"C06\", \"C07\"],\n  \"missing_checks\": [\n    \"Verify door lock states for the bathroom during C12/C13 to determine if the subject is trapped or simply absent.\",\n    \"Cross-reference total expected resident count to validate the 'ghost absence' hypothesis (i.e., confirm if a second person exists to explain high occupancy elsewhere while bathroom is empty).\",\n    \"Check timestamp continuity in C05-C07 to rule out data gaps that mimic activity cessation.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identified the temporal anomaly but relies heavily on assumptions about household size without confirming it.\",\n    \"Focusing only on late-night chunks (C12/C13) ignores the context of daytime behavior; adding C05-C07 (likely covering morning/early day transitions) is necessary to establish a baseline for normal multi-person vs. single-person patterns.\",\n    \"The current evidence does not explicitly check sensor health or potential blind spots in the bathroom sensor logic.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C05", "C06", "C07"], "missing_checks": ["Verify door lock states for the bathroom during C12/C13 to determine if the subject is trapped or simply absent.", "Cross-reference total expected resident count to validate the 'ghost absence' hypothesis (i.e., confirm if a second person exists to explain high occupancy elsewhere while bathroom is empty).", "Check timestamp continuity in C05-C07 to rule out data gaps that mimic activity cessation."], "supervisor_notes": ["The analysis correctly identified the temporal anomaly but relies heavily on assumptions about household size without confirming it.", "Focusing only on late-night chunks (C12/C13) ignores the context of daytime behavior; adding C05-C07 (likely covering morning/early day transitions) is necessary to establish a baseline for normal multi-person vs. single-person patterns.", "The current evidence does not explicitly check sensor health or potential blind spots in the bathroom sensor logic."]}, "preview_triage_prompt": "## Query\n以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Layout\nLayout: 独居老人 (Elderly Living Alone)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>, 床头灯<onoff_light>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房运动传感器<occupancy_sensor>\n- living_room: 客厅温度传感器<temperature_sensor>, 客厅灯<dimmable_light>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 294,\n    \"bedroom\": 296,\n    \"kitchen\": 295,\n    \"entrance\": 147,\n    \"bathroom\": 28\n  },\n  \"attribute_frequency\": {\n    \"Occupancy\": 606,\n    \"MeasuredValue\": 437,\n    \"OnOff\": 10,\n    \"CurrentPositionLiftPercent100ths\": 3,\n    \"CurrentLevel\": 1,\n    \"StateValue\": 1,\n    \"LockState\": 1\n  },\n  \"lock_state_flips\": 1,\n  \"occupancy_events\": 606,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-18T11:55:00\",\n    \"end_ts\": \"2026-06-18T12:47:03\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 22,\n      \"bedroom\": 23,\n      \"kitchen\": 22,\n      \"entrance\": 11,\n      \"bathroom\": 2\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"kitchen_occupancy\",\n      \"bedroom_occupancy\",\n      \"entrance_occupancy\"\n    ],\n    \"alarmish_count\": 45,\n    \"preview_lines\": [\n      \"[2026-06-18T11:55:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2537\",\n      \"[2026-06-18T11:55:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2434\",\n      \"[2026-06-18T11:55:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2532\",\n      \"[2026-06-18T11:55:00] kitchen_occupancy | OccupancySensing.Occupancy = 1\",\n      \"[2026-06-18T11:57:00] bedroom_occupancy | OccupancySensing.Occupancy = 1\",\n      \"[2026-06-18T11:57:03] entrance_occupancy | OccupancySensing.Occupancy = 1\",\n      \"[2026-06-18T11:57:08] living_room_occupancy | OccupancySensing.Occupancy = 1\",\n      \"[2026-06-18T12:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2527\",\n      \"[2026-06-18T1", "preview_verifier_prompt": "## Query\n以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Triage\n{\n  \"latent_task_profile\": \"behavior-sequence | composite-safety\",\n  \"focus_rooms\": [\n    \"bedroom\",\n    \"entrance\",\n    \"bathroom\"\n  ],\n  \"focus_devices\": [\n    \"bedroom_occupancy_sensor\",\n    \"entrance_contact_sensor\",\n    \"entrance_door_lock\",\n    \"bathroom_occupancy_sensor\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C03\",\n    \"C04\",\n    \"C12\",\n    \"C13\"\n  ],\n  \"suspected_patterns\": [\n    \"Nocturnal absence detection: Subject may have left the bedroom and entrance area during early morning hours (approx. 05:00-07:00 based on timestamp gaps in activity) while sleeping elsewhere or being absent.\",\n    \"Risky bathroom access: Bathroom occupancy drops to zero multiple times without immediate re-entry correlation, potentially indicating a fall or inability to exit/enter.\",\n    \"Temperature gradient anomaly: Bedroom temperature consistently lower than living/kitchen areas, possibly due to closed windows or AC, but needs verification against occupancy status.\"\n  ],\n  \"why_these_chunks\": [\n    \"C03/C04 show the transition period where entrance activity is high but bathroom becomes empty, suggesting movement out of the home or deep sleep cycles.\",\n    \"C12/C13 capture the late-night/early-morning window where bathroom occupancy briefly hits zero while other rooms remain active, a critical time for fall detection in elderly monitoring.\",\n    \"These chunks highlight the 'absence' events which are the primary trigger for safety alerts in this profile.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Standard multi-person household activity with staggered bathroom usage and consistent thermal gradients.\",\n      \"evidence\": [\n        \"High occupancy counts in living_room (294), bedroom (296), and kitchen (295) vs low in bathroom (28), indicating multiple residents distributed throughout the house.\",\n        \"Temperature data shows a stable, logical gradient: Kitchen/Living (~24°C/2450k) > Bedroom (~23°C/2350k), consistent with heating distribution or room function.\",\n        \"Bathroom occupancy drops to zero (C03, C04, C12, C13) while other rooms remain active, which is normal for sequential use by different individuals.\"\n    ]\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Sustained 'Ghost' Absence in Bathroom during Night Hours despite High Activity Elsewhere.\",\n      \"threat_type\": \"Safety/Fall Risk\",\n      \"evidence\": [\n        \"In Chu"}}
{"episode_id": "SQ4_FP_A_0857", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq4\\SQ4_FP_A_0857.json", "metadata": {"sq_type": "SQ4", "sq_name": "复合安全推理", "variant": "FP", "layout_id": "A", "layout_name": "一室一厅 (Studio/1BR)", "profile_id": "young_professional", "base_date": "2026-06-01T00:00:00", "seed": 20261486, "scenario_id": "FG-01", "total_events": 1130, "anomaly_events_count": 5}, "ground_truth": {"scenario_id": "FG-01-FP", "scenario_name": "FG-01-FP: 煲汤/慢炖（正常长时间开灶）", "category": "fire_gas", "is_anomaly": false, "threat_type": "none", "key_difference": "温度上升后稳定（不持续飙升），住户定期回来检查，烟雾传感器未触发", "difficulty_score": 11, "difficulty_level": 3, "difficulty_label": "L3_composite_reasoning", "difficulty_dimensions": {"D1_evidence_count": 3, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 2, "D5_fp_similarity": 2}, "target_room": "living_room", "injection_time": "2026-06-01T06:45:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"medium\",\n  \"threat_type\": \"intrusion\",\n  \"threat_description\": \"A sequence of suspicious events in the kitchen involving manual appliance shutdown, immediate window opening, and subsequent sensor data loss suggests a potential unauthorized entry attempt or tampering.\",\n  \"reasoning\": [\n      \"At 19:43:00, the kitchen cook surface was manually turned off, followed 30 seconds later at 19:43:30 by the kitchen window contact opening, indicating rapid sequential human intervention that is atypical for normal cooking cleanup.\",\n      \"Immediately following the window breach at 19:44:00, the kitchen temperature sensor reported 'None' (data loss), creating a blind spot in environmental monitoring coinciding with high alarm counts.\",\n      \"While C04 shows front door lock manipulation at 07:27, it occurred during standard auto-lock cycles and lacked the aggressive manual override characteristics seen in the evening kitchen events; however, the evening sequence remains the primary indicator of active intrusion or tampering.\"\n    ],\n  \"key_evidence\": [\n      \"kitchen_cook_surface state change to False at 19:43:00\",\n      \"kitchen_window_contact state change to False (Open) at 19:43:30\",\n      \"kitchen_temp_sensor MeasuredValue = None at 19:44:00\"\n    ],\n  \"recommended_actions\": [\n      \"Verify physical status of the kitchen window and inspect for signs of forced entry or damage.\",\n      \"Check security camera footage from the kitchen area around 19:43 to identify any individuals present.\",\n      \"Reset the kitchen temperature sensor if necessary to restore monitoring capabilities.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "medium", "threat_type": "intrusion", "threat_description": "A sequence of suspicious events in the kitchen involving manual appliance shutdown, immediate window opening, and subsequent sensor data loss suggests a potential unauthorized entry attempt or tampering.", "reasoning": ["At 19:43:00, the kitchen cook surface was manually turned off, followed 30 seconds later at 19:43:30 by the kitchen window contact opening, indicating rapid sequential human intervention that is atypical for normal cooking cleanup.", "Immediately following the window breach at 19:44:00, the kitchen temperature sensor reported 'None' (data loss), creating a blind spot in environmental monitoring coinciding with high alarm counts.", "While C04 shows front door lock manipulation at 07:27, it occurred during standard auto-lock cycles and lacked the aggressive manual override characteristics seen in the evening kitchen events; however, the evening sequence remains the primary indicator of active intrusion or tampering."], "key_evidence": ["kitchen_cook_surface state change to False at 19:43:00", "kitchen_window_contact state change to False (Open) at 19:43:30", "kitchen_temp_sensor MeasuredValue = None at 19:44:00"], "recommended_actions": ["Verify physical status of the kitchen window and inspect for signs of forced entry or damage.", "Check security camera footage from the kitchen area around 19:43 to identify any individuals present.", "Reset the kitchen temperature sensor if necessary to restore monitoring capabilities."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "medium"}, "latency": 54.39856433868408, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1130, "chunk_count": 15, "signals": {"room_activity": {"living_room": 403, "bedroom": 356, "kitchen": 301, "bathroom": 56, "entrance": 14}, "attribute_frequency": {"MeasuredValue": 868, "Occupancy": 225, "OnOff": 19, "StateValue": 5, "LockState": 4, "CurrentPositionLiftPercent100ths": 2, "SystemMode": 1, "OperationalState": 1, "CurrentLevel": 1}, "lock_state_flips": 4, "occupancy_events": 225, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_cook_surface\", \"kitchen_window_contact\", \"kitchen_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C04\", \"C11\"],\n  \"suspected_patterns\": [\n    \"Abnormally high temperature readings (likely scaled values) indicating potential overheating or sensor calibration drift in the kitchen.\",\n    \"Sequence of events: Stove turned OFF followed immediately by Window Contact opening, suggesting an intrusion attempt while appliances were active or a safety breach protocol.\",\n    \"Sensor data loss (None value) coinciding with window opening and high activity alarm counts.\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C11 contains the critical safety sequence: 'kitchen_cook_surface' turning off at 19:43, followed by 'kitchen_window_contact' becoming open ('False') at 19:43:30. This correlates with 'alarmish_count' spiking to 22.\",\n    \"Chunk C04 shows early signs of anomaly with a sudden spike in kitchen temperature (2750 vs ~2500 baseline) and the first appearance of 'front_door_lock' events, initiating the investigation into thermal and access anomalies.\",\n    \"The combination of these chunks reveals a compound risk: thermal irregularities potentially leading to fire hazards, compounded by a window being opened during/after cooking activity.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen"], "focus_devices": ["kitchen_cook_surface", "kitchen_window_contact", "kitchen_temp_sensor"], "focus_chunk_ids": ["C04", "C11"], "suspected_patterns": ["Abnormally high temperature readings (likely scaled values) indicating potential overheating or sensor calibration drift in the kitchen.", "Sequence of events: Stove turned OFF followed immediately by Window Contact opening, suggesting an intrusion attempt while appliances were active or a safety breach protocol.", "Sensor data loss (None value) coinciding with window opening and high activity alarm counts."], "why_these_chunks": ["Chunk C11 contains the critical safety sequence: 'kitchen_cook_surface' turning off at 19:43, followed by 'kitchen_window_contact' becoming open ('False') at 19:43:30. This correlates with 'alarmish_count' spiking to 22.", "Chunk C04 shows early signs of anomaly with a sudden spike in kitchen temperature (2750 vs ~2500 baseline) and the first appearance of 'front_door_lock' events, initiating the investigation into thermal and access anomalies.", "The combination of these chunks reveals a compound risk: thermal irregularities potentially leading to fire hazards, compounded by a window being opened during/after cooking activity."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The kitchen temperature spike at 07:15 (2750) was a transient sensor glitch caused by cooking activity or draft, as the value returned to baseline immediately and no fire alarms were triggered.\",\n      \"evidence\": [\"kitchen_temp_sensor reading spiked to 2750 at 07:15 but stabilized around 2500-2600 in subsequent readings within minutes.\", \"No other safety devices (smoke detectors, gas leaks) reported anomalies during this specific window.\"],\n      \"weaknesses\": [\"Does not explain why the front door lock/unlock sequence occurred simultaneously with this event, nor does it account for the significant deviation from historical baselines if present.\"],\n      \"threat_type\": null\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Potential intruder activity in the evening (C11): The stove was turned off manually, followed almost immediately by the kitchen window contact opening. This suggests an entry attempt while the home was occupied or transitioning.\",\n      \"evidence\": [\"At 19:43:00, 'kitchen_cook_surface' state changed to False.\", \"At 19:43:30, 'kitchen_window_contact' state changed to False (Open).\", \"Only 30 seconds elapsed between stopping heat and opening the window, indicating rapid sequential action typical of an intruder checking ventilation points after disabling appliances.\"],\n      \"weaknesses\": [\"Could be a resident cleaning up after dinner and venting smoke; however, the speed and sequence are suspicious without audio confirmation.\"],\n      \"threat_type\": \"Intrusion / Unauthorized Access\"\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Sensor failure or tampering in the kitchen: A critical data loss event ('MeasuredValue = None') coincided exactly with the window opening and high occupancy/alarm counts.\",\n      \"evidence\": [\"At 19:44:00, 'kitchen_temp_sensor' reported MeasuredValue = None.\", \"This occurred one minute after the window opened and two minutes after the cook surface was turned off.\", \"The system recorded 'alarmish_count' spikes, suggesting a correlation between the physical breach/tamper and the sensor drop-out.\"],\n      \"weaknesses\": [\"Could be a scheduled maintenance reboot or network packet loss unrelated to physical intrusion.\"],\n      \"threat_type\": \"System Integrity Compromise / Environmental Hazard (Blind Spot)\"\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The precise temporal sequence in C11: Cook Surface OFF (19:43:00) -> Window OPEN (19:43:30) -> Sensor DATA LOSS (19:44:00). This chain strongly implies human intervention overriding normal operation.\",\n    \"The simultaneous occurrence of 'front_door_lock' manual operations and door contact fluctuations in C04, which differs from standard auto-lock cycles, suggests active manipulation of access control points.\"\n  ],\n  \"missing_information\": [\n    \"Audio logs or voice command history to distinguish between automated commands (voice assistant) and manual physical interaction.\",\n    \"Video feed from the kitchen entrance to visually confirm the presence of individuals and their actions regarding the window.\",\n    \"Historical baseline data for the 'LockState' flip frequency to determine if 4 flips in a single session is anomalous behavior for this household.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The kitchen temperature spike at 07:15 (2750) was a transient sensor glitch caused by cooking activity or draft, as the value returned to baseline immediately and no fire alarms were triggered.", "evidence": ["kitchen_temp_sensor reading spiked to 2750 at 07:15 but stabilized around 2500-2600 in subsequent readings within minutes.", "No other safety devices (smoke detectors, gas leaks) reported anomalies during this specific window."], "weaknesses": ["Does not explain why the front door lock/unlock sequence occurred simultaneously with this event, nor does it account for the significant deviation from historical baselines if present."], "threat_type": null}], "anomaly_hypotheses": [{"id": "A1", "description": "Potential intruder activity in the evening (C11): The stove was turned off manually, followed almost immediately by the kitchen window contact opening. This suggests an entry attempt while the home was occupied or transitioning.", "evidence": ["At 19:43:00, 'kitchen_cook_surface' state changed to False.", "At 19:43:30, 'kitchen_window_contact' state changed to False (Open).", "Only 30 seconds elapsed between stopping heat and opening the window, indicating rapid sequential action typical of an intruder checking ventilation points after disabling appliances."], "weaknesses": ["Could be a resident cleaning up after dinner and venting smoke; however, the speed and sequence are suspicious without audio confirmation."], "threat_type": "Intrusion / Unauthorized Access"}, {"id": "A2", "description": "Sensor failure or tampering in the kitchen: A critical data loss event ('MeasuredValue = None') coincided exactly with the window opening and high occupancy/alarm counts.", "evidence": ["At 19:44:00, 'kitchen_temp_sensor' reported MeasuredValue = None.", "This occurred one minute after the window opened and two minutes after the cook surface was turned off.", "The system recorded 'alarmish_count' spikes, suggesting a correlation between the physical breach/tamper and the sensor drop-out."], "weaknesses": ["Could be a scheduled maintenance reboot or network packet loss unrelated to physical intrusion."], "threat_type": "System Integrity Compromise / Environmental Hazard (Blind Spot)"}], "most_discriminative_evidence": ["The precise temporal sequence in C11: Cook Surface OFF (19:43:00) -> Window OPEN (19:43:30) -> Sensor DATA LOSS (19:44:00). This chain strongly implies human intervention overriding normal operation.", "The simultaneous occurrence of 'front_door_lock' manual operations and door contact fluctuations in C04, which differs from standard auto-lock cycles, suggests active manipulation of access control points."], "missing_information": ["Audio logs or voice command history to distinguish between automated commands (voice assistant) and manual physical interaction.", "Video feed from the kitchen entrance to visually confirm the presence of individuals and their actions regarding the window.", "Historical baseline data for the 'LockState' flip frequency to determine if 4 flips in a single session is anomalous behavior for this household."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C04\", \"C12\"],\n  \"missing_checks\": [\n    \"Verify the timestamp and state of 'front_door_lock' events in C04 to confirm manual manipulation vs. normal cycles.\",\n    \"Check C12 for any subsequent security alerts or door contact changes immediately following the kitchen window breach.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identified the critical sequence in C11 (Cook Off -> Window Open -> Sensor Loss) as a high-priority anomaly.\",\n    \"However, the current evidence selection is insufficient regarding the 'Intrusion' hypothesis. While C04 mentions front door lock events, it does not explicitly detail the 'manual operations' or specific timestamps needed to prove active manipulation versus standard behavior. C04 must be retrieved to validate the 'most_discriminative evidence' claim about access control.\",\n    \"Additionally, the investigation timeline suggests a potential progression from Kitchen to Front Door or vice versa. Chunk C12 likely contains data post-19:44 which could reveal if the intrusion attempt moved to the front door or resulted in an alarm escalation. The current set lacks this temporal context.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C04", "C12"], "missing_checks": ["Verify the timestamp and state of 'front_door_lock' events in C04 to confirm manual manipulation vs. normal cycles.", "Check C12 for any subsequent security alerts or door contact changes immediately following the kitchen window breach."], "supervisor_notes": ["The analysis correctly identified the critical sequence in C11 (Cook Off -> Window Open -> Sensor Loss) as a high-priority anomaly.", "However, the current evidence selection is insufficient regarding the 'Intrusion' hypothesis. While C04 mentions front door lock events, it does not explicitly detail the 'manual operations' or specific timestamps needed to prove active manipulation versus standard behavior. C04 must be retrieved to validate the 'most_discriminative evidence' claim about access control.", "Additionally, the investigation timeline suggests a potential progression from Kitchen to Front Door or vice versa. Chunk C12 likely contains data post-19:44 which could reveal if the intrusion attempt moved to the front door or resulted in an alarm escalation. The current set lacks this temporal context."]}, "preview_triage_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Layout\nLayout: 一室一厅 (Studio/1BR)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅台灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 403,\n    \"bedroom\": 356,\n    \"kitchen\": 301,\n    \"bathroom\": 56,\n    \"entrance\": 14\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 868,\n    \"Occupancy\": 225,\n    \"OnOff\": 19,\n    \"StateValue\": 5,\n    \"LockState\": 4,\n    \"CurrentPositionLiftPercent100ths\": 2,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 225,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-01T00:00:00\",\n    \"end_ts\": \"2026-06-01T01:50:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 27,\n      \"bedroom\": 27,\n      \"kitchen\": 22,\n      \"bathroom\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"bathroom_occupancy\"\n    ],\n    \"alarmish_count\": 12,\n    \"preview_lines\": [\n      \"[2026-06-01T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2276\",\n      \"[2026-06-01T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2179\",\n      \"[2026-06-01T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2264\",\n      \"[2026-06-01T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-01T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-01T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-01T00:05:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2277\",\n      \"[2026-06-01T00:05:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2178\",\n      \"[2026-06-01T00:05:00] kitchen_temp_sens", "preview_verifier_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_cook_surface\", \"kitchen_window_contact\", \"kitchen_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C04\", \"C11\"],\n  \"suspected_patterns\": [\n    \"Abnormally high temperature readings (likely scaled values) indicating potential overheating or sensor calibration drift in the kitchen.\",\n    \"Sequence of events: Stove turned OFF followed immediately by Window Contact opening, suggesting an intrusion attempt while appliances were active or a safety breach protocol.\",\n    \"Sensor data loss (None value) coinciding with window opening and high activity alarm counts.\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C11 contains the critical safety sequence: 'kitchen_cook_surface' turning off at 19:43, followed by 'kitchen_window_contact' becoming open ('False') at 19:43:30. This correlates with 'alarmish_count' spiking to 22.\",\n    \"Chunk C04 shows early signs of anomaly with a sudden spike in kitchen temperature (2750 vs ~2500 baseline) and the first appearance of 'front_door_lock' events, initiating the investigation into thermal and access anomalies.\",\n    \"The combination of these chunks reveals a compound risk: thermal irregularities potentially leading to fire hazards, compounded by a window being opened during/after cooking activity.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The kitchen temperature spike at 07:15 (2750) was a transient sensor glitch caused by cooking activity or draft, as the value returned to baseline immediately and no fire alarms were triggered.\",\n      \"evidence\": [\"kitchen_temp_sensor reading spiked to 2750 at 07:15 but stabilized around 2500-2600 in subsequent readings within minutes.\", \"No other safety devices (smoke detectors, gas leaks) reported anomalies during this specific window.\"],\n      \"weaknesses\": [\"Does not explain why the front door lock/unlock sequence occurred simultaneously with this event, nor does it account for the significant deviation from historical baselines if present.\"],\n      \"threat_type\": null\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Potential intruder activity in the evening (C11): The stove was turned off manually, followed almost immediately by the kitchen window contact opening. This suggests an entry attempt while the home was occupied or transitioning.\",\n  "}}
{"episode_id": "SQ3_TP_D_0464", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq3\\SQ3_TP_D_0464.json", "metadata": {"sq_type": "SQ3", "sq_name": "行为序列分析", "variant": "TP", "layout_id": "D", "layout_name": "独居老人 (Elderly Living Alone)", "profile_id": "elderly_living_alone", "base_date": "2026-06-16T00:00:00", "seed": 20261093, "scenario_id": "EL-03", "total_events": 1857, "anomaly_events_count": 6}, "ground_truth": {"scenario_id": "EL-03", "scenario_name": "忘记关火", "category": "elderly_specific", "is_anomaly": true, "threat_type": "unattended_cooking", "key_evidence": ["灶具开着 + 厨房无人 + 老人在其他房间", "跟 FG-01 类似但在老人场景下更危险（认知衰退风险更高）"], "expected_response": "立即语音提醒老人关火", "difficulty_score": 10, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 2, "D5_fp_similarity": 2}, "target_room": "bathroom", "injection_time": "2026-06-16T15:31:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"medium\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"A single-point sensor failure in the kitchen caused a temporary data gap (None) immediately after the stove was turned off, while occupancy remained high and temperatures subsequently recovered, indicating no active fire or safety breach.\",\n  \"reasoning\": [\n      \"Analysis of Chunk C06 confirms that at 17:22:00, the cook surface state changed to 'False' (off).\",\n      \"Immediately following this event at 17:23:00, the kitchen temperature sensor reported 'None', which initially raised suspicion of a safety hazard or equipment malfunction.\",\n      \"However, reviewing adjacent chunks reveals that occupancy remained confirmed ('=1') in the kitchen starting from 17:24:00, and temperature readings returned valid values by 17:25:00 (2356), showing a continuous cooling trend consistent with a turned-off appliance.\",\n      \"The persistence of occupancy sensors and the return of valid temperature data rule out an unattended cooking scenario or a person being trapped; the anomaly is isolated to the specific sensor reading at 17:23:00.\",\n      \"Therefore, the event is classified as a transient sensor malfunction or communication glitch rather than a security intrusion or persistent safety threat.\"\n    ],\n  \"key_evidence\": [\n      \"At 17:22:00, `kitchen_cook_surface` state changed to `False`.\",\n      \"At 17:23:00, `kitchen_temp_sensor` reported `None`, followed immediately by valid readings at 17:25:00.\",\n      \"Occupancy sensors recorded presence (`=1`) in the kitchen continuously from 17:24:00 onwards.\",\n      \"Temperature values show a logical cooling trajectory (2339 -> 2356 -> 2336) consistent with residual heat dissipation after turning off the stove.\"\n    ],\n  \"recommended_actions\": [\n      \"Verify the physical connection and battery status of the kitchen temperature sensor.\",\n      \"Check system logs for any network interruptions or communication errors occurring precisely at 17:23:00.\",\n      \"Monitor the sensor for future occurrences of 'None' readings when occupancy is confirmed to ensure stability.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "medium", "threat_type": "sensor_malfunction", "threat_description": "A single-point sensor failure in the kitchen caused a temporary data gap (None) immediately after the stove was turned off, while occupancy remained high and temperatures subsequently recovered, indicating no active fire or safety breach.", "reasoning": ["Analysis of Chunk C06 confirms that at 17:22:00, the cook surface state changed to 'False' (off).", "Immediately following this event at 17:23:00, the kitchen temperature sensor reported 'None', which initially raised suspicion of a safety hazard or equipment malfunction.", "However, reviewing adjacent chunks reveals that occupancy remained confirmed ('=1') in the kitchen starting from 17:24:00, and temperature readings returned valid values by 17:25:00 (2356), showing a continuous cooling trend consistent with a turned-off appliance.", "The persistence of occupancy sensors and the return of valid temperature data rule out an unattended cooking scenario or a person being trapped; the anomaly is isolated to the specific sensor reading at 17:23:00.", "Therefore, the event is classified as a transient sensor malfunction or communication glitch rather than a security intrusion or persistent safety threat."], "key_evidence": ["At 17:22:00, `kitchen_cook_surface` state changed to `False`.", "At 17:23:00, `kitchen_temp_sensor` reported `None`, followed immediately by valid readings at 17:25:00.", "Occupancy sensors recorded presence (`=1`) in the kitchen continuously from 17:24:00 onwards.", "Temperature values show a logical cooling trajectory (2339 -> 2356 -> 2336) consistent with residual heat dissipation after turning off the stove."], "recommended_actions": ["Verify the physical connection and battery status of the kitchen temperature sensor.", "Check system logs for any network interruptions or communication errors occurring precisely at 17:23:00.", "Monitor the sensor for future occurrences of 'None' readings when occupancy is confirmed to ensure stability."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 5, "has_evidence": true, "has_actions": true, "confidence": "medium"}, "latency": 56.283145904541016, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1067, "chunk_count": 14, "signals": {"room_activity": {"living_room": 294, "bedroom": 295, "kitchen": 300, "entrance": 147, "bathroom": 31}, "attribute_frequency": {"Occupancy": 610, "MeasuredValue": 438, "OnOff": 12, "CurrentPositionLiftPercent100ths": 3, "CurrentLevel": 1, "StateValue": 1, "LockState": 1}, "lock_state_flips": 1, "occupancy_events": 610, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"behavior-sequence | single-event-safety\",\n  \"focus_rooms\": [\"kitchen\", \"bedroom\", \"entrance\"],\n  \"focus_devices\": [\"kitchen_cook_surface\", \"front_door_contact\", \"front_door_lock\", \"bedroom_window_covering\", \"bedroom_light\"],\n  \"focus_chunk_ids\": [\"C06\", \"C10\"],\n  \"suspected_patterns\": [\n    \"Potential stove-off event while occupancy is confirmed in kitchen (safety hazard)\",\n    \"Nighttime departure sequence: Door lock engagement followed immediately by bedroom window closing and lights toggling\",\n    \"Temperature drop rate exceeding normal baseline suggesting HVAC changes or room vacating\"\n  ],\n  \"why_these_chunks\": [\n    \"C06 contains a specific 'OnOff.OnOff = False' event for the cook surface while occupancy was recorded, indicating a potential safety gap.\",\n    \"C10 shows a distinct temporal cluster of events (door contact true, door lock operation, window covering movement, light toggle) typical of leaving the residence at night, which requires verification against the occupant's schedule.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "behavior-sequence | single-event-safety", "focus_rooms": ["kitchen", "bedroom", "entrance"], "focus_devices": ["kitchen_cook_surface", "front_door_contact", "front_door_lock", "bedroom_window_covering", "bedroom_light"], "focus_chunk_ids": ["C06", "C10"], "suspected_patterns": ["Potential stove-off event while occupancy is confirmed in kitchen (safety hazard)", "Nighttime departure sequence: Door lock engagement followed immediately by bedroom window closing and lights toggling", "Temperature drop rate exceeding normal baseline suggesting HVAC changes or room vacating"], "why_these_chunks": ["C06 contains a specific 'OnOff.OnOff = False' event for the cook surface while occupancy was recorded, indicating a potential safety gap.", "C10 shows a distinct temporal cluster of events (door contact true, door lock operation, window covering movement, light toggle) typical of leaving the residence at night, which requires verification against the occupant's schedule."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Standard evening routine: Cooking in the kitchen followed by a planned departure sequence involving locking the door, closing blinds, and toggling lights.\",\n      \"evidence\": [\"High occupancy frequency in Living Room (294), Bedroom (295), and Kitchen (300) indicates active use.\", \"C10 shows a logical temporal sequence: Door contact true -> Lock operation -> Window covering close -> Light toggle. This mimics a 'Goodnight/Leaving' automation script or manual action.\", \"Temperature values in C10 are stable and within expected ranges for an occupied home at night (21-22°C range).\"],\n      \"weaknesses\": [\"The stove-off event in C06 occurred while occupancy was confirmed in the kitchen, which contradicts typical safety behavior if cooking was ongoing.\", \"The specific timing of the departure sequence (20:55) requires verification against known occupant schedules to rule out unauthorized access or simulation.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Potential fire hazard: Stove turned off despite continuous occupancy and temperature readings suggesting active heating.\",\n      \"threat_type\": \"Safety Hazard\",\n      \"evidence\": [\"At 17:22:00, `kitchen_cook_surface` state changed to `False`.\", \"Immediately following this, `kitchen_temp_sensor` reported `None` (data loss) at 17:23:00.\", \"Occupancy sensors recorded presence (`Occupancy = 1`) in the kitchen at 17:24:00, 17:29:00, etc., immediately after the stove turn-off.\", \"While temperatures rose slightly later, the gap between turning off the heat source and the next data point raises suspicion of equipment malfunction or user error leading to a burn risk scenario.\"],\n      \"weaknesses\": [\"Subsequent temperature readings show rising temps (2325 -> 2336), which could simply be residual heat from the surface cooling down slowly rather than an anomaly if the stove was just turned off.\", \"The `None` value might be a sensor glitch unrelated to the appliance state.\"]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Suspicious automated or remote departure sequence occurring during high activity periods.\",\n      \"threat_type\": \"Security Intrusion / Automation Abuse\",\n      \"evidence\": [\"In C10, the departure sequence (Door Contact -> Lock -> Blinds -> Light Toggle) happens at 20:55.\", \"However, Occupancy sensors remain positive (`=1`) in the Bedroom, Bathroom, and Kitchen for over 15 minutes *after* the lock engages (until ~21:06).\", \"Normally, if someone leaves and locks the door, they do not have continuous occupancy confirmation in internal rooms for 15+ minutes unless they are still inside but the system is falsely reporting, OR the sequence was triggered remotely while occupants were unaware/presence logic was flawed.\"],\n      \"weaknesses\": [\"The sequence order (Contact->Lock->Blinds->Light) is very specific; it could be a pre-programmed 'Night Mode' that runs regardless of actual exit status.\", \"Occupancy sensors can have latency or false positives (e.g., pets, static interference).\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The combination of `kitchen_cook_surface = False` followed immediately by `kitchen_occupancy = 1` and subsequent `TemperatureMeasurement = None` in Chunk C06 suggests a disconnect between appliance state and environmental monitoring.\",\n    \"The temporal decoupling in Chunk C10 where `front_door_lock` engages at 20:55:16 but `bedroom_occupancy` remains 1 until 21:06:00 challenges the assumption that the 'departure sequence' resulted in an empty house.\"\n  ],\n  \"missing_information\": [\n    \"History of the cook surface's OnOff state prior to 17:22:00 (was it already off? Was it on continuously?).\",\n    \"Calibration logs for the kitchen temperature sensor to explain the `None` reading.\",\n    \"Known schedule or 'Away Mode' configuration for the smart home system to determine if the C10 sequence is intended behavior.\",\n    \"Video feed or motion trajectory data for the bedroom/kitchen corridor between 17:22 and 17:30.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Standard evening routine: Cooking in the kitchen followed by a planned departure sequence involving locking the door, closing blinds, and toggling lights.", "evidence": ["High occupancy frequency in Living Room (294), Bedroom (295), and Kitchen (300) indicates active use.", "C10 shows a logical temporal sequence: Door contact true -> Lock operation -> Window covering close -> Light toggle. This mimics a 'Goodnight/Leaving' automation script or manual action.", "Temperature values in C10 are stable and within expected ranges for an occupied home at night (21-22°C range)."], "weaknesses": ["The stove-off event in C06 occurred while occupancy was confirmed in the kitchen, which contradicts typical safety behavior if cooking was ongoing.", "The specific timing of the departure sequence (20:55) requires verification against known occupant schedules to rule out unauthorized access or simulation."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Potential fire hazard: Stove turned off despite continuous occupancy and temperature readings suggesting active heating.", "threat_type": "Safety Hazard", "evidence": ["At 17:22:00, `kitchen_cook_surface` state changed to `False`.", "Immediately following this, `kitchen_temp_sensor` reported `None` (data loss) at 17:23:00.", "Occupancy sensors recorded presence (`Occupancy = 1`) in the kitchen at 17:24:00, 17:29:00, etc., immediately after the stove turn-off.", "While temperatures rose slightly later, the gap between turning off the heat source and the next data point raises suspicion of equipment malfunction or user error leading to a burn risk scenario."], "weaknesses": ["Subsequent temperature readings show rising temps (2325 -> 2336), which could simply be residual heat from the surface cooling down slowly rather than an anomaly if the stove was just turned off.", "The `None` value might be a sensor glitch unrelated to the appliance state."]}, {"id": "A2", "description": "Suspicious automated or remote departure sequence occurring during high activity periods.", "threat_type": "Security Intrusion / Automation Abuse", "evidence": ["In C10, the departure sequence (Door Contact -> Lock -> Blinds -> Light Toggle) happens at 20:55.", "However, Occupancy sensors remain positive (`=1`) in the Bedroom, Bathroom, and Kitchen for over 15 minutes *after* the lock engages (until ~21:06).", "Normally, if someone leaves and locks the door, they do not have continuous occupancy confirmation in internal rooms for 15+ minutes unless they are still inside but the system is falsely reporting, OR the sequence was triggered remotely while occupants were unaware/presence logic was flawed."], "weaknesses": ["The sequence order (Contact->Lock->Blinds->Light) is very specific; it could be a pre-programmed 'Night Mode' that runs regardless of actual exit status.", "Occupancy sensors can have latency or false positives (e.g., pets, static interference)."]}], "most_discriminative_evidence": ["The combination of `kitchen_cook_surface = False` followed immediately by `kitchen_occupancy = 1` and subsequent `TemperatureMeasurement = None` in Chunk C06 suggests a disconnect between appliance state and environmental monitoring.", "The temporal decoupling in Chunk C10 where `front_door_lock` engages at 20:55:16 but `bedroom_occupancy` remains 1 until 21:06:00 challenges the assumption that the 'departure sequence' resulted in an empty house."], "missing_information": ["History of the cook surface's OnOff state prior to 17:22:00 (was it already off? Was it on continuously?).", "Calibration logs for the kitchen temperature sensor to explain the `None` reading.", "Known schedule or 'Away Mode' configuration for the smart home system to determine if the C10 sequence is intended behavior.", "Video feed or motion trajectory data for the bedroom/kitchen corridor between 17:22 and 17:30."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C05\", \"C07\"],\n  \"missing_checks\": [\n    \"Verify C05 to determine the state of the cook surface immediately prior to the event in C06 (was it already off or turned on recently?).\",\n    \"Verify C07 to check for any occupancy changes or sensor recovery events immediately following the data loss and re-occupancy spike in C06.\",\n    \"Cross-reference C10 timestamps with known 'Away Mode' automation triggers to confirm if the departure sequence was pre-programmed.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identified potential anomalies but relies heavily on assumptions about the state before the stove-off event. Chunk C05 is critical to establish the baseline state of the cook surface.\",\n    \"To rule out sensor malfunction versus actual safety hazard, we need to see the immediate aftermath in C07 to understand how quickly the temperature sensor recovered or if the reading remained null.\",\n    \"The 'departure sequence' anomaly could be benign automation; checking system configuration logs (not just raw chunks) is necessary, but reviewing adjacent chunks like C09 and C11 might reveal similar patterns or lack thereof to calibrate the significance of C10.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C05", "C07"], "missing_checks": ["Verify C05 to determine the state of the cook surface immediately prior to the event in C06 (was it already off or turned on recently?).", "Verify C07 to check for any occupancy changes or sensor recovery events immediately following the data loss and re-occupancy spike in C06.", "Cross-reference C10 timestamps with known 'Away Mode' automation triggers to confirm if the departure sequence was pre-programmed."], "supervisor_notes": ["The analysis correctly identified potential anomalies but relies heavily on assumptions about the state before the stove-off event. Chunk C05 is critical to establish the baseline state of the cook surface.", "To rule out sensor malfunction versus actual safety hazard, we need to see the immediate aftermath in C07 to understand how quickly the temperature sensor recovered or if the reading remained null.", "The 'departure sequence' anomaly could be benign automation; checking system configuration logs (not just raw chunks) is necessary, but reviewing adjacent chunks like C09 and C11 might reveal similar patterns or lack thereof to calibrate the significance of C10."]}, "preview_triage_prompt": "## Query\n以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Layout\nLayout: 独居老人 (Elderly Living Alone)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>, 床头灯<onoff_light>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房运动传感器<occupancy_sensor>\n- living_room: 客厅温度传感器<temperature_sensor>, 客厅灯<dimmable_light>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 294,\n    \"bedroom\": 295,\n    \"kitchen\": 300,\n    \"entrance\": 147,\n    \"bathroom\": 31\n  },\n  \"attribute_frequency\": {\n    \"Occupancy\": 610,\n    \"MeasuredValue\": 438,\n    \"OnOff\": 12,\n    \"CurrentPositionLiftPercent100ths\": 3,\n    \"CurrentLevel\": 1,\n    \"StateValue\": 1,\n    \"LockState\": 1\n  },\n  \"lock_state_flips\": 1,\n  \"occupancy_events\": 610,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-16T11:55:00\",\n    \"end_ts\": \"2026-06-16T12:49:03\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 22,\n      \"bedroom\": 23,\n      \"kitchen\": 22,\n      \"entrance\": 11,\n      \"bathroom\": 2\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"kitchen_occupancy\",\n      \"bedroom_occupancy\",\n      \"entrance_occupancy\"\n    ],\n    \"alarmish_count\": 45,\n    \"preview_lines\": [\n      \"[2026-06-16T11:55:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2521\",\n      \"[2026-06-16T11:55:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2440\",\n      \"[2026-06-16T11:55:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2530\",\n      \"[2026-06-16T11:55:00] kitchen_occupancy | OccupancySensing.Occupancy = 1\",\n      \"[2026-06-16T11:57:00] bedroom_occupancy | OccupancySensing.Occupancy = 1\",\n      \"[2026-06-16T11:59:03] entrance_occupancy | OccupancySensing.Occupancy = 1\",\n      \"[2026-06-16T11:59:08] living_room_occupancy | OccupancySensing.Occupancy = 1\",\n      \"[2026-06-16T12:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2520\",\n      \"[2026-06-16T1", "preview_verifier_prompt": "## Query\n以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。\n\n## Triage\n{\n  \"latent_task_profile\": \"behavior-sequence | single-event-safety\",\n  \"focus_rooms\": [\"kitchen\", \"bedroom\", \"entrance\"],\n  \"focus_devices\": [\"kitchen_cook_surface\", \"front_door_contact\", \"front_door_lock\", \"bedroom_window_covering\", \"bedroom_light\"],\n  \"focus_chunk_ids\": [\"C06\", \"C10\"],\n  \"suspected_patterns\": [\n    \"Potential stove-off event while occupancy is confirmed in kitchen (safety hazard)\",\n    \"Nighttime departure sequence: Door lock engagement followed immediately by bedroom window closing and lights toggling\",\n    \"Temperature drop rate exceeding normal baseline suggesting HVAC changes or room vacating\"\n  ],\n  \"why_these_chunks\": [\n    \"C06 contains a specific 'OnOff.OnOff = False' event for the cook surface while occupancy was recorded, indicating a potential safety gap.\",\n    \"C10 shows a distinct temporal cluster of events (door contact true, door lock operation, window covering movement, light toggle) typical of leaving the residence at night, which requires verification against the occupant's schedule.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Standard evening routine: Cooking in the kitchen followed by a planned departure sequence involving locking the door, closing blinds, and toggling lights.\",\n      \"evidence\": [\"High occupancy frequency in Living Room (294), Bedroom (295), and Kitchen (300) indicates active use.\", \"C10 shows a logical temporal sequence: Door contact true -> Lock operation -> Window covering close -> Light toggle. This mimics a 'Goodnight/Leaving' automation script or manual action.\", \"Temperature values in C10 are stable and within expected ranges for an occupied home at night (21-22°C range).\"],\n      \"weaknesses\": [\"The stove-off event in C06 occurred while occupancy was confirmed in the kitchen, which contradicts typical safety behavior if cooking was ongoing.\", \"The specific timing of the departure sequence (20:55) requires verification against known occupant schedules to rule out unauthorized access or simulation.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Potential fire hazard: Stove turned off despite continuous occupancy and temperature readings suggesting active heating.\",\n      \"threat_type\": \"Safety Hazard\",\n      \"evidence\": [\"At 17:22:00, `kitchen_cook_surface` state changed to `False`.\", \"Immediately following this, `kitchen_temp_sensor` reported"}}
{"episode_id": "SQ4_FP_B_0885", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq4\\SQ4_FP_B_0885.json", "metadata": {"sq_type": "SQ4", "sq_name": "复合安全推理", "variant": "FP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "young_professional", "base_date": "2026-06-01T00:00:00", "seed": 20261514, "scenario_id": "FG-02", "total_events": 1659, "anomaly_events_count": 4}, "ground_truth": {"scenario_id": "FG-02-FP", "scenario_name": "FG-02-FP: 电暖器/取暖器正常使用", "category": "fire_gas", "is_anomaly": false, "threat_type": "none", "key_difference": "有人在房间且温度上升后趋于稳定（不是持续飙升），无烟雾报警触发", "difficulty_score": 10, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 2, "D5_fp_similarity": 2}, "target_room": "living_room", "injection_time": "2026-06-01T06:20:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"The home safety system is reporting catastrophic false-positive temperature readings (e.g., 2714) likely due to sensor drift or data corruption, rather than a physical fire hazard, as ambient room temperatures remain stable in the 23°C range.\",\n  \"reasoning\": [\n      \"Analysis of Chunks C00-C04 reveals that despite temperature sensors reporting values exceeding 2500 for several hours, occupancy logs consistently show rooms are empty and no other devices (lights, appliances) indicate active heating events.\",\n      \"Physical impossibility check: Values like 2639, 2714, and 2480 are physically impossible for indoor ambient air in standard units (Celsius/Fahrenheit/Kelvin), ruling out actual fires or cooking-related heat spikes.\",\n      \"Correlation analysis shows that when the kitchen cook surface was turned off at 19:34, the anomalous high temperature readings immediately ceased, returning to normal ~22-23 values in subsequent chunks (C16), confirming the anomaly was isolated to specific sensor data points.\"\n    ],\n  \"key_evidence\": [\n      \"Kitchen temperature spiked to 2714 while living room remained at ~2300, indicating non-uniform environmental heat but uniform sensor error pattern.\",\n      \"Temperature readings dropped instantly from >2700 to ~2200 after the cook surface was turned off at 19:34, proving the spike was not caused by residual appliance heat.\",\n      \"Occupancy sensors report '0' (empty) in all rooms during the entire period of extreme temperature readings, contradicting any scenario involving people generating heat.\"\n    ],\n  \"recommended_actions\": [\n      \"Immediately reset or recalibrate all temperature sensors to restore accurate monitoring.\",\n      \"Inspect sensor hardware for obstructions, calibration errors, or firmware glitches causing data spoofing.\",\n      \"Verify smoke detector functionality via manual test button press to ensure they are not falsely triggered by corrupted input data.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "The home safety system is reporting catastrophic false-positive temperature readings (e.g., 2714) likely due to sensor drift or data corruption, rather than a physical fire hazard, as ambient room temperatures remain stable in the 23°C range.", "reasoning": ["Analysis of Chunks C00-C04 reveals that despite temperature sensors reporting values exceeding 2500 for several hours, occupancy logs consistently show rooms are empty and no other devices (lights, appliances) indicate active heating events.", "Physical impossibility check: Values like 2639, 2714, and 2480 are physically impossible for indoor ambient air in standard units (Celsius/Fahrenheit/Kelvin), ruling out actual fires or cooking-related heat spikes.", "Correlation analysis shows that when the kitchen cook surface was turned off at 19:34, the anomalous high temperature readings immediately ceased, returning to normal ~22-23 values in subsequent chunks (C16), confirming the anomaly was isolated to specific sensor data points."], "key_evidence": ["Kitchen temperature spiked to 2714 while living room remained at ~2300, indicating non-uniform environmental heat but uniform sensor error pattern.", "Temperature readings dropped instantly from >2700 to ~2200 after the cook surface was turned off at 19:34, proving the spike was not caused by residual appliance heat.", "Occupancy sensors report '0' (empty) in all rooms during the entire period of extreme temperature readings, contradicting any scenario involving people generating heat."], "recommended_actions": ["Immediately reset or recalibrate all temperature sensors to restore accurate monitoring.", "Inspect sensor hardware for obstructions, calibration errors, or firmware glitches causing data spoofing.", "Verify smoke detector functionality via manual test button press to ensure they are not falsely triggered by corrupted input data."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 61.41957473754883, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1659, "chunk_count": 21, "signals": {"room_activity": {"living_room": 405, "master_bedroom": 336, "second_bedroom": 336, "kitchen": 298, "bathroom": 54, "entrance": 230}, "attribute_frequency": {"MeasuredValue": 1157, "Occupancy": 473, "OnOff": 14, "StateValue": 5, "LockState": 4, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 4, "occupancy_events": 473, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\", \"entrance\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"living_room_temp_sensor\", \"entrance_occupancy\", \"front_door_lock\", \"front_door_contact\"],\n  \"focus_chunk_ids\": [\"C15\", \"C16\", \"C17\", \"C18\", \"C19\"],\n  \"suspected_patterns\": [\n    \"sustained_abnormal_temperature_elevation\",\n    \"nighttime_security_activity_spike\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunks C15-C16 show kitchen temperatures spiking to ~2639 (far exceeding normal ranges seen in C00-C14), indicating a potential fire hazard or sensor failure.\",\n    \"Chunks C15-C20 exhibit a pattern of repeated entrance occupancy events late at night (22:13 onwards) with frequent door lock/unlock cycles, suggesting either an intruder or unusual household behavior requiring safety verification.\",\n    \"The combination of extreme heat and active entry points creates a composite safety risk profile.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "living_room", "entrance"], "focus_devices": ["kitchen_temp_sensor", "living_room_temp_sensor", "entrance_occupancy", "front_door_lock", "front_door_contact"], "focus_chunk_ids": ["C15", "C16", "C17", "C18", "C19"], "suspected_patterns": ["sustained_abnormal_temperature_elevation", "nighttime_security_activity_spike"], "why_these_chunks": ["Chunks C15-C16 show kitchen temperatures spiking to ~2639 (far exceeding normal ranges seen in C00-C14), indicating a potential fire hazard or sensor failure.", "Chunks C15-C20 exhibit a pattern of repeated entrance occupancy events late at night (22:13 onwards) with frequent door lock/unlock cycles, suggesting either an intruder or unusual household behavior requiring safety verification.", "The combination of extreme heat and active entry points creates a composite safety risk profile."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The temperature readings represent a valid internal sensor fault or calibration error, while occupancy data reflects standard evening household routine.\",\n      \"evidence\": [\n        \"Room temperatures (2200-2300 range) are physically impossible for ambient air but consistent across all sensors.\",\n        \"Occupancy patterns show continuous presence in living/entrance and bedroom vacating at night (22:00+), typical of family winding down.\",\n        \"Kitchen appliance usage (cook surface on/off, dishwasher cycle) aligns with normal cooking times.\"\n      ],\n      \"weaknesses\": [\n        \"Does not explain why the 'impossible' numbers spike specifically in the kitchen before stabilizing.\",\n        \"Fails to account for the specific timing of the door lock/unlock sequence relative to the temperature anomalies.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Sensor malfunction causing garbage data; no actual security threat exists.\",\n      \"threat_type\": \"False Positive / Data Integrity\",\n      \"evidence\": [\n        \"Temperatures jump from ~2500 to >2700 then drop rapidly, inconsistent with thermal physics of a room heating up over minutes.\",\n        \"Values are uniform across distinct rooms, suggesting a central data corruption event rather than localized heat sources.\"\n      ],\n      \"weaknesses\": [\n        \"Coincides with high-frequency entrance occupancy events and door cycling which could be genuine intruder behavior masked by noise.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Active intrusion with environmental tampering or distraction tactics.\",\n      \"threat_type\": \"Physical Intrusion / Security Breach\",\n      \"evidence\": [\n        \"Repeated entrance_occupancy = 1 signals between 18:15 and 23:10 without corresponding bedroom occupancy changes until late.\",\n        \"Front door contact triggered True and LockState changed to 1 (Locked) at 22:13:47, immediately followed by light off.\",\n        \"Kitchen temperature spikes (up to 2714) may indicate an active cooking device used as a smokescreen, fire hazard, or sensor cover-up attempt.\"\n      ],\n      \"weaknesses\": [\n        \"Could be a resident testing smoke alarms or cleaning the kitchen.\",\n        \"The 'locked' state suggests the system secured itself, mitigating immediate theft risk, though potential for forced entry remains if lock failed.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"Temperature values exceeding 2700 (physically impossible for Celsius/Fahrenheit/Kelvin in standard units) appearing simultaneously in multiple rooms suggest either a catastrophic sensor failure or a deliberate data spoofing attack.\",\n    \"The sequence of Entrance Occupancy -> Door Contact Triggered -> Auto-Lock at 22:13 indicates a discrete entry event that occurred after the initial period of anomalous temperature readings.\",\n    \"Kitchen Cook Surface turned ON at 18:49 and OFF at 19:34, yet temperatures continued to climb to 2700+ later in C16/C17, implying the spike is not solely due to this single cooking event.\"\n  ],\n  \"missing_information\": [\n    \"Unit of measurement for temperature (Celsius, Fahrenheit, Kelvin) to determine if 2300 is a typo for 23.00 or a real value.\",\n    \"Identity of occupants (who is inside?) to validate if the occupancy pattern is normal or suspicious.\",\n    \"Historical data prior to 18:15 to establish baseline temperature behavior and rule out a delayed system initialization error.\",\n    \"Status of other home systems (smoke detectors, gas leaks) during the temperature spike window.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The temperature readings represent a valid internal sensor fault or calibration error, while occupancy data reflects standard evening household routine.", "evidence": ["Room temperatures (2200-2300 range) are physically impossible for ambient air but consistent across all sensors.", "Occupancy patterns show continuous presence in living/entrance and bedroom vacating at night (22:00+), typical of family winding down.", "Kitchen appliance usage (cook surface on/off, dishwasher cycle) aligns with normal cooking times."], "weaknesses": ["Does not explain why the 'impossible' numbers spike specifically in the kitchen before stabilizing.", "Fails to account for the specific timing of the door lock/unlock sequence relative to the temperature anomalies."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Sensor malfunction causing garbage data; no actual security threat exists.", "threat_type": "False Positive / Data Integrity", "evidence": ["Temperatures jump from ~2500 to >2700 then drop rapidly, inconsistent with thermal physics of a room heating up over minutes.", "Values are uniform across distinct rooms, suggesting a central data corruption event rather than localized heat sources."], "weaknesses": ["Coincides with high-frequency entrance occupancy events and door cycling which could be genuine intruder behavior masked by noise."]}, {"id": "A2", "description": "Active intrusion with environmental tampering or distraction tactics.", "threat_type": "Physical Intrusion / Security Breach", "evidence": ["Repeated entrance_occupancy = 1 signals between 18:15 and 23:10 without corresponding bedroom occupancy changes until late.", "Front door contact triggered True and LockState changed to 1 (Locked) at 22:13:47, immediately followed by light off.", "Kitchen temperature spikes (up to 2714) may indicate an active cooking device used as a smokescreen, fire hazard, or sensor cover-up attempt."], "weaknesses": ["Could be a resident testing smoke alarms or cleaning the kitchen.", "The 'locked' state suggests the system secured itself, mitigating immediate theft risk, though potential for forced entry remains if lock failed."]}], "most_discriminative_evidence": ["Temperature values exceeding 2700 (physically impossible for Celsius/Fahrenheit/Kelvin in standard units) appearing simultaneously in multiple rooms suggest either a catastrophic sensor failure or a deliberate data spoofing attack.", "The sequence of Entrance Occupancy -> Door Contact Triggered -> Auto-Lock at 22:13 indicates a discrete entry event that occurred after the initial period of anomalous temperature readings.", "Kitchen Cook Surface turned ON at 18:49 and OFF at 19:34, yet temperatures continued to climb to 2700+ later in C16/C17, implying the spike is not solely due to this single cooking event."], "missing_information": ["Unit of measurement for temperature (Celsius, Fahrenheit, Kelvin) to determine if 2300 is a typo for 23.00 or a real value.", "Identity of occupants (who is inside?) to validate if the occupancy pattern is normal or suspicious.", "Historical data prior to 18:15 to establish baseline temperature behavior and rule out a delayed system initialization error.", "Status of other home systems (smoke detectors, gas leaks) during the temperature spike window."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\", \"C18\", \"C19\"],\n  \"missing_checks\": [\n    \"Verify temperature unit (C/F/K) to interpret '2639' vs '23.00'.\",\n    \"Cross-reference 'C00-C014' for baseline temperature behavior prior to the spike.\",\n    \"Confirm identity of occupants during late-night entrance events to distinguish intruder from resident.\",\n    \"Check status of smoke/gas detectors during the high-temperature window.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identified the critical anomaly (impossible temperature readings) and the security correlation (late-night entry/locking).\",\n    \"However, evidence sufficiency is low because the 'Investigator Output' explicitly cites missing historical data ('C00-C14') and occupant identity as critical gaps needed to form a conclusion.\",\n    \"Chunks C15-C17 are insufficient on their own; we need the pre-event baseline (C00-C04) to confirm this is a deviation rather than a system initialization error, and we need to review the full night's logs (C18-C19) to see if the threat persisted or resolved after the auto-lock.\",\n    \"No drift detected; the investigation remains focused on safety and risk assessment.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C00", "C01", "C02", "C03", "C04", "C18", "C19"], "missing_checks": ["Verify temperature unit (C/F/K) to interpret '2639' vs '23.00'.", "Cross-reference 'C00-C014' for baseline temperature behavior prior to the spike.", "Confirm identity of occupants during late-night entrance events to distinguish intruder from resident.", "Check status of smoke/gas detectors during the high-temperature window."], "supervisor_notes": ["The analysis correctly identified the critical anomaly (impossible temperature readings) and the security correlation (late-night entry/locking).", "However, evidence sufficiency is low because the 'Investigator Output' explicitly cites missing historical data ('C00-C14') and occupant identity as critical gaps needed to form a conclusion.", "Chunks C15-C17 are insufficient on their own; we need the pre-event baseline (C00-C04) to confirm this is a deviation rather than a system initialization error, and we need to review the full night's logs (C18-C19) to see if the threat persisted or resolved after the auto-lock.", "No drift detected; the investigation remains focused on safety and risk assessment."]}, "preview_triage_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 405,\n    \"master_bedroom\": 336,\n    \"second_bedroom\": 336,\n    \"kitchen\": 298,\n    \"bathroom\": 54,\n    \"entrance\": 230\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1157,\n    \"Occupancy\": 473,\n    \"OnOff\": 14,\n    \"StateValue\": 5,\n    \"LockState\": 4,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 473,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-01T00:00:00\",\n    \"end_ts\": \"2026-06-01T01:20:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 20,\n      \"master_bedroom\": 19,\n      \"second_bedroom\": 19,\n      \"kitchen\": 16,\n      \"bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"master_bedroom_occupancy\"\n    ],\n    \"alarmish_count\": 15,\n    \"preview_lines\": [\n      \"[2026-06-01T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2278\",\n      \"[2026-06-01T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2267\",\n      \"[2026-06-01T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2276\",\n      \"[2026-06-01T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2267\",\n      \"[2026-06-01T00:00:00] living_room_occupancy | OccupancySensing.", "preview_verifier_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\", \"entrance\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"living_room_temp_sensor\", \"entrance_occupancy\", \"front_door_lock\", \"front_door_contact\"],\n  \"focus_chunk_ids\": [\"C15\", \"C16\", \"C17\", \"C18\", \"C19\"],\n  \"suspected_patterns\": [\n    \"sustained_abnormal_temperature_elevation\",\n    \"nighttime_security_activity_spike\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunks C15-C16 show kitchen temperatures spiking to ~2639 (far exceeding normal ranges seen in C00-C14), indicating a potential fire hazard or sensor failure.\",\n    \"Chunks C15-C20 exhibit a pattern of repeated entrance occupancy events late at night (22:13 onwards) with frequent door lock/unlock cycles, suggesting either an intruder or unusual household behavior requiring safety verification.\",\n    \"The combination of extreme heat and active entry points creates a composite safety risk profile.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The temperature readings represent a valid internal sensor fault or calibration error, while occupancy data reflects standard evening household routine.\",\n      \"evidence\": [\n        \"Room temperatures (2200-2300 range) are physically impossible for ambient air but consistent across all sensors.\",\n        \"Occupancy patterns show continuous presence in living/entrance and bedroom vacating at night (22:00+), typical of family winding down.\",\n        \"Kitchen appliance usage (cook surface on/off, dishwasher cycle) aligns with normal cooking times.\"\n      ],\n      \"weaknesses\": [\n        \"Does not explain why the 'impossible' numbers spike specifically in the kitchen before stabilizing.\",\n        \"Fails to account for the specific timing of the door lock/unlock sequence relative to the temperature anomalies.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Sensor malfunction causing garbage data; no actual security threat exists.\",\n      \"threat_type\": \"False Positive / Data Integrity\",\n      \"evidence\": [\n        \"Temperatures jump from ~2500 to >2700 then drop rapidly, inconsistent with thermal physics of a room heating up over minutes.\",\n        \"Values are uniform across distinct rooms, suggesting a central data corruption event rather than localized heat sources.\"\n      ],\n      \"weaknesses\": [\n        \"Coincides with high-f"}}
{"episode_id": "SQ4_FP_B_0916", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq4\\SQ4_FP_B_0916.json", "metadata": {"sq_type": "SQ4", "sq_name": "复合安全推理", "variant": "FP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "young_professional", "base_date": "2026-06-22T00:00:00", "seed": 20261545, "scenario_id": "BA-01", "total_events": 1659, "anomaly_events_count": 4}, "ground_truth": {"scenario_id": "BA-01-FP", "scenario_name": "BA-01-FP: 住户失眠在家走动", "category": "behavioral_anomaly", "is_anomaly": false, "threat_type": "none", "key_difference": "活动从卧室开始（住户起床），路径合理（卧室→客厅→厨房→卧室），最终回到卧室", "difficulty_score": 11, "difficulty_level": 3, "difficulty_label": "L3_composite_reasoning", "difficulty_dimensions": {"D1_evidence_count": 3, "D2_signal_directness": 2, "D3_cross_device": 3, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "second_bedroom", "injection_time": "2026-06-22T21:54:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"A localized sensor malfunction in the kitchen caused a massive data spike and subsequent readout failure during cooking, with no evidence of an actual fire or safety breach.\",\n  \"reasoning\": [\n      \"Initial analysis revealed that all temperature sensors report values around 2300, which is physically impossible for Celsius/Fahrenheit; this indicates a firmware bug sending raw ADC integers instead of calibrated temperatures (Normal Hypothesis N1).\",\n      \"The 'anomaly' was identified as the kitchen sensor reading ~2700 while others remained at ~2300. However, normalizing these values (dividing by ~9) shows the kitchen only spiked to ~300°C-equivalent (if 2300=25°C) or simply deviated by ~40 units from other rooms, which corresponds to a plausible ~25-30°C difference typical of active cooking, not a fire.\",\n      \"The definitive cause of the alarm state was the sensor failing completely: the value dropped to 'None' at 19:00:00 immediately after the cook surface turned on, then resumed reporting normal baseline values (~2300) once the heat source was removed at 19:48:00, indicating a temporary hardware glitch rather than a thermal hazard.\",\n      \"Post-incident logs (C17-C19) show stable temperatures across all rooms, occupancy patterns consistent with human presence, and no activation of smoke alarms, gas detectors, or emergency protocols.\"\n    ],\n  \"key_evidence\": [\n      \"Kitchen temp sensor reported 'None' starting at 19:00:00 and recovered to normal range (~2268-2371) by 19:20:00 after the cook surface was turned off at 19:48:00.\",\n      \"No smoke detector triggers, fire suppression events, or HVAC emergency overrides were recorded in the entire log sequence (C00-C19).\",\n      \"All room sensors converged back to the same baseline offset (~2240-2270) by 20:00, proving the system-wide calibration bias is constant and the earlier divergence was isolated to the kitchen sensor's transient failure.\"\n    ],\n  \"recommended_actions\": [\n      \"Replace the kitchen temperature sensor due to intermittent connectivity/readout failure.\",\n      \"Update firmware to correct the temperature scaling factor (divide raw ADC value by calibration constant) to prevent future misinterpretation of readings.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "A localized sensor malfunction in the kitchen caused a massive data spike and subsequent readout failure during cooking, with no evidence of an actual fire or safety breach.", "reasoning": ["Initial analysis revealed that all temperature sensors report values around 2300, which is physically impossible for Celsius/Fahrenheit; this indicates a firmware bug sending raw ADC integers instead of calibrated temperatures (Normal Hypothesis N1).", "The 'anomaly' was identified as the kitchen sensor reading ~2700 while others remained at ~2300. However, normalizing these values (dividing by ~9) shows the kitchen only spiked to ~300°C-equivalent (if 2300=25°C) or simply deviated by ~40 units from other rooms, which corresponds to a plausible ~25-30°C difference typical of active cooking, not a fire.", "The definitive cause of the alarm state was the sensor failing completely: the value dropped to 'None' at 19:00:00 immediately after the cook surface turned on, then resumed reporting normal baseline values (~2300) once the heat source was removed at 19:48:00, indicating a temporary hardware glitch rather than a thermal hazard.", "Post-incident logs (C17-C19) show stable temperatures across all rooms, occupancy patterns consistent with human presence, and no activation of smoke alarms, gas detectors, or emergency protocols."], "key_evidence": ["Kitchen temp sensor reported 'None' starting at 19:00:00 and recovered to normal range (~2268-2371) by 19:20:00 after the cook surface was turned off at 19:48:00.", "No smoke detector triggers, fire suppression events, or HVAC emergency overrides were recorded in the entire log sequence (C00-C19).", "All room sensors converged back to the same baseline offset (~2240-2270) by 20:00, proving the system-wide calibration bias is constant and the earlier divergence was isolated to the kitchen sensor's transient failure."], "recommended_actions": ["Replace the kitchen temperature sensor due to intermittent connectivity/readout failure.", "Update firmware to correct the temperature scaling factor (divide raw ADC value by calibration constant) to prevent future misinterpretation of readings."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 70.94706058502197, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1659, "chunk_count": 21, "signals": {"room_activity": {"living_room": 402, "master_bedroom": 336, "second_bedroom": 336, "kitchen": 298, "bathroom": 57, "entrance": 230}, "attribute_frequency": {"MeasuredValue": 1154, "Occupancy": 472, "OnOff": 14, "StateValue": 5, "LockState": 4, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 4, "occupancy_events": 472, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\n    \"kitchen\",\n    \"living_room\"\n  ],\n  \"focus_devices\": [\n    \"kitchen_temp_sensor\",\n    \"living_room_temp_sensor\",\n    \"living_room_ac\",\n    \"entrance_occupancy\",\n    \"bathroom_occupancy\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C00\",\n    \"C15\",\n    \"C16\"\n  ],\n  \"suspected_patterns\": [\n    \"Sensor Data Corruption: Temperature readings in C00-C04 range from 2269 to 2559, which is physically impossible for a standard thermometer (likely raw ADC values instead of Celsius).\",\n    \"Anomalous Thermal Spike: In C15/C16, kitchen temperature jumps to ~2697 while others are normal (~2300), suggesting a sensor fault or calibration drift rather than actual overheating.\",\n    \"HVAC Control Lag/Conflict: AC turns ON in C15 but temperatures remain elevated or show erratic patterns immediately after, indicating potential control logic issues or sensor noise affecting feedback loops.\"\n  ],\n  \"why_these_chunks\": [\n    \"C00 contains the earliest evidence of massive data corruption (values >2000) across all temperature sensors, establishing the baseline anomaly.\",\n    \"C15 and C16 contain the only instance of extreme localized deviation (Kitchen=2697 vs LivingRoom=2316) combined with active HVAC switching, making them critical for distinguishing between a single device failure and a systemic safety risk like fire detection false positives.\",\n    \"These chunks also show the highest 'alarmish_count' (29-31), correlating with the data anomalies.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "living_room"], "focus_devices": ["kitchen_temp_sensor", "living_room_temp_sensor", "living_room_ac", "entrance_occupancy", "bathroom_occupancy"], "focus_chunk_ids": ["C00", "C15", "C16"], "suspected_patterns": ["Sensor Data Corruption: Temperature readings in C00-C04 range from 2269 to 2559, which is physically impossible for a standard thermometer (likely raw ADC values instead of Celsius).", "Anomalous Thermal Spike: In C15/C16, kitchen temperature jumps to ~2697 while others are normal (~2300), suggesting a sensor fault or calibration drift rather than actual overheating.", "HVAC Control Lag/Conflict: AC turns ON in C15 but temperatures remain elevated or show erratic patterns immediately after, indicating potential control logic issues or sensor noise affecting feedback loops."], "why_these_chunks": ["C00 contains the earliest evidence of massive data corruption (values >2000) across all temperature sensors, establishing the baseline anomaly.", "C15 and C16 contain the only instance of extreme localized deviation (Kitchen=2697 vs LivingRoom=2316) combined with active HVAC switching, making them critical for distinguishing between a single device failure and a systemic safety risk like fire detection false positives.", "These chunks also show the highest 'alarmish_count' (29-31), correlating with the data anomalies."]}, "investigator_raw": "```json\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Systematic Sensor Calibration Offset: All temperature sensors are reporting values approximately 2000 units higher than the actual ambient temperature (e.g., reporting ~2300 instead of ~30°C). This is likely a fixed firmware bug where the raw ADC integer value is being sent without division by a calibration factor.\",\n      \"evidence\": [\n        \"C00 shows consistent readings around 2269-2298 across all rooms, which correlates with typical indoor temperatures if divided by ~8-9.\",\n        \"In C15/C16, while kitchen spikes to 2697/2717 and drops back to 2400s, the other rooms remain in the 2280-2310 range, suggesting a localized physical event rather than total sensor failure.\",\n        \"Occupancy and light data function normally (e.g., entrance occupancy = 1 at 18:21), indicating the communication protocol and logic gates are working.\"\n    ]\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Kitchen Thermal Hazard / Fire Risk: A significant thermal anomaly occurred in the kitchen between 18:25 and 19:00. The reported temperature spiked from ~2300 (normalized ~230) to >2700 (normalized >270) and remained elevated for nearly 40 minutes while cooking activities were active.\",\n      \"threat_type\": \"Fire/Safety Hazard\",\n      \"evidence\": [\n        \"C15 18:25: Kitchen reports 2697 vs Living Room 2316. If normalized, this is a massive differential (>40°C difference).\",\n        \"C15 18:30-18:55: Kitchen temperature remains erratic and high (2717 -> 2695 -> 2619 -> 2576) while living room stabilizes around 2300.\",\n        \"C15 18:59: 'kitchen_cook_surface' turns ON; 'kitchen_light' turns ON.\",\n        \"C15 19:00: Temperature reading drops to None, followed by a reset trend, suggesting a component may have failed or triggered an over-temp cutoff.\"\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Data Integrity Failure: The system experienced a period of corrupted data logging where meaningful temperature readings were lost or replaced with garbage values, potentially masking real-time conditions.\",\n      \"threat_type\": \"Monitoring Blindspot\",\n      \"evidence\": [\n        \"C15 19:00:00: Value explicitly logged as 'None' for kitchen_temp_sensor.\",\n        \"C16 19:49:00: Value explicitly logged as 'None' for kitchen_temp_sensor shortly after cook surface turned off.\",\n        \"The sudden drop from 2529 to 2498 to 2460 in C15 could be a rapid cooling due to fire suppression, a sensor disconnect, or a glitched readout.\"\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The extreme divergence between the kitchen sensor (peaking at 2717) and all other room sensors (staying below 2320) during the evening hours (C15), which persists despite HVAC activation in the living room.\",\n    \"The temporal correlation between the temperature spike in the kitchen and the activation of the cook surface and kitchen lights (18:59:00 - 19:00:00).\",\n    \"The intermittent loss of data ('None') specifically for the kitchen sensor starting at 19:00:00 and again at 19:49:00, indicating a hardware fault or protective shutdown in that specific zone.\"\n  ],\n  \"missing_information\": [\n    \"Actual absolute temperature conversion factor: Without knowing the divisor (e.g., is 2300 actually 230°C or 25°C?), we must rely on relative deltas.\",\n    \"Smoke detector status: No logs indicate smoke detection events during the kitchen temperature spike.\",\n    \"HVAC System Mode details: While AC was turned on, the target temperature setpoint and current mode (Cool/Heat/Auto) are not explicitly defined beyond 'Mode=3'.\",\n    \"Cook Surface Type: Is it an induction coil, gas stove, or electric radiant heater? This affects the expected heat signature.\"\n  ]\n}\n```", "investigator_parsed": {"_parse_failed": true, "raw_preview": "```json\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Systematic Sensor Calibration Offset: All temperature sensors are reporting values approximately 2000 units higher than the actual ambient temperature (e.g., reporting ~2300 instead of ~30°C). This is likely a fixed firmware bug where the raw ADC integer value is being sent without division by a calibration factor.\",\n      \"evidence\": [\n        \"C00 shows consistent readings around 2269-2298 across all rooms, which correlates with typical indoor temperatures if divided by ~8-9.\",\n        \"In C15/C16, while kitchen spikes to 2697/2717 and drops back to 2400s, the other rooms remain in the 2280-2310 range, suggesting a localized physical event rather than total sensor failure.\",\n        \"Occupancy and light data function normally (e.g., entrance occupancy = 1 at 18:21), indicating the communication protocol and logic gates are working.\"\n    ]\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"desc"}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C17\", \"C18\", \"C19\"],\n  \"missing_checks\": [\n    \"Verify HVAC cooling capacity and runtime to determine if the temperature spike was suppressed or ignored.\",\n    \"Check for any smoke alarm or fire suppression system triggers in logs immediately following the kitchen temperature anomaly (approx 19:00-19:30).\",\n    \"Cross-reference 'None' data loss events with power outage logs to rule out a total system failure vs. localized sensor fault.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identified the data corruption pattern (ADC values) and the localized thermal spike in the kitchen as a potential hazard.\",\n    \"However, the current evidence is insufficient to confirm a safety event because it lacks post-incident data. We need chunks C17-C19 to see what happened after the temperature dropped/reset at 19:00 (did smoke alarms trigger? did the AC fail?).\",\n    \"Without seeing the immediate aftermath (C17+) or confirmation of other safety sensors (smoke/gas), we cannot definitively declare the status 'Safe' or 'Critical Hazard', only that there was a significant anomaly.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C17", "C18", "C19"], "missing_checks": ["Verify HVAC cooling capacity and runtime to determine if the temperature spike was suppressed or ignored.", "Check for any smoke alarm or fire suppression system triggers in logs immediately following the kitchen temperature anomaly (approx 19:00-19:30).", "Cross-reference 'None' data loss events with power outage logs to rule out a total system failure vs. localized sensor fault."], "supervisor_notes": ["The analysis correctly identified the data corruption pattern (ADC values) and the localized thermal spike in the kitchen as a potential hazard.", "However, the current evidence is insufficient to confirm a safety event because it lacks post-incident data. We need chunks C17-C19 to see what happened after the temperature dropped/reset at 19:00 (did smoke alarms trigger? did the AC fail?).", "Without seeing the immediate aftermath (C17+) or confirmation of other safety sensors (smoke/gas), we cannot definitively declare the status 'Safe' or 'Critical Hazard', only that there was a significant anomaly."]}, "preview_triage_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 402,\n    \"master_bedroom\": 336,\n    \"second_bedroom\": 336,\n    \"kitchen\": 298,\n    \"bathroom\": 57,\n    \"entrance\": 230\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1154,\n    \"Occupancy\": 472,\n    \"OnOff\": 14,\n    \"StateValue\": 5,\n    \"LockState\": 4,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 472,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-22T00:00:00\",\n    \"end_ts\": \"2026-06-22T01:20:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 20,\n      \"master_bedroom\": 19,\n      \"second_bedroom\": 19,\n      \"kitchen\": 16,\n      \"bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"master_bedroom_occupancy\"\n    ],\n    \"alarmish_count\": 15,\n    \"preview_lines\": [\n      \"[2026-06-22T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2269\",\n      \"[2026-06-22T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2262\",\n      \"[2026-06-22T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2262\",\n      \"[2026-06-22T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2276\",\n      \"[2026-06-22T00:00:00] living_room_occupancy | OccupancySensing.", "preview_verifier_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\n    \"kitchen\",\n    \"living_room\"\n  ],\n  \"focus_devices\": [\n    \"kitchen_temp_sensor\",\n    \"living_room_temp_sensor\",\n    \"living_room_ac\",\n    \"entrance_occupancy\",\n    \"bathroom_occupancy\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C00\",\n    \"C15\",\n    \"C16\"\n  ],\n  \"suspected_patterns\": [\n    \"Sensor Data Corruption: Temperature readings in C00-C04 range from 2269 to 2559, which is physically impossible for a standard thermometer (likely raw ADC values instead of Celsius).\",\n    \"Anomalous Thermal Spike: In C15/C16, kitchen temperature jumps to ~2697 while others are normal (~2300), suggesting a sensor fault or calibration drift rather than actual overheating.\",\n    \"HVAC Control Lag/Conflict: AC turns ON in C15 but temperatures remain elevated or show erratic patterns immediately after, indicating potential control logic issues or sensor noise affecting feedback loops.\"\n  ],\n  \"why_these_chunks\": [\n    \"C00 contains the earliest evidence of massive data corruption (values >2000) across all temperature sensors, establishing the baseline anomaly.\",\n    \"C15 and C16 contain the only instance of extreme localized deviation (Kitchen=2697 vs LivingRoom=2316) combined with active HVAC switching, making them critical for distinguishing between a single device failure and a systemic safety risk like fire detection false positives.\",\n    \"These chunks also show the highest 'alarmish_count' (29-31), correlating with the data anomalies.\"\n  ]\n}\n\n## Investigator\n```json\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Systematic Sensor Calibration Offset: All temperature sensors are reporting values approximately 2000 units higher than the actual ambient temperature (e.g., reporting ~2300 instead of ~30°C). This is likely a fixed firmware bug where the raw ADC integer value is being sent without division by a calibration factor.\",\n      \"evidence\": [\n        \"C00 shows consistent readings around 2269-2298 across all rooms, which correlates with typical indoor temperatures if divided by ~8-9.\",\n        \"In C15/C16, while kitchen spikes to 2697/2717 and drops back to 2400s, the other rooms remain in the 2280-2310 range, suggesting a localized physical event rather than total sensor failure.\",\n        \"Occupancy and light data function normally (e.g., entrance occupancy = 1 at 18:21), indicating the communication protocol and "}}
{"episode_id": "SQ4_FP_C_0854", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq4\\SQ4_FP_C_0854.json", "metadata": {"sq_type": "SQ4", "sq_name": "复合安全推理", "variant": "FP", "layout_id": "C", "layout_name": "三室两厅 (3BR)", "profile_id": "family_with_children", "base_date": "2026-06-17T00:00:00", "seed": 20261483, "scenario_id": "CH-01", "total_events": 2302, "anomaly_events_count": 4}, "ground_truth": {"scenario_id": "CH-01-FP", "scenario_name": "CH-01-FP: 孩子生病请假在家（家长陪护）", "category": "child_specific", "is_anomaly": false, "threat_type": "none", "key_difference": "家长也在家（多个房间有活动），不只是儿童房，说明有成人陪护", "difficulty_score": 10, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 2, "D5_fp_similarity": 2}, "target_room": "kids_room", "injection_time": "2026-06-17T22:49:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"Critical sensor failure causing physically impossible temperature readings (>2000°C) while occupancy sensors failed to detect human presence for over six hours, followed by a delayed and chaotic reactivation of the home system.\",\n  \"reasoning\": [\n      \"Temperature readings across all rooms consistently exceeded 2000 (e.g., 2493, 2559), which is physically impossible for a residential environment without total structural destruction, definitively ruling out real-world heat sources like fires or occupants.\",\n      \"Occupancy sensors reported '0' (empty) for all rooms from 00:00 until 06:12, despite the logs indicating massive thermal energy accumulation; if humans were present to cause such heat, occupancy would have been detected immediately.\",\n      \"The system exhibited erratic behavior including multiple 'lock_state_flips' without corresponding door contact events, and temperatures only stabilized after occupants returned at 06:12, suggesting a firmware bug or unit conversion error rather than an environmental event.\"\n    ],\n  \"key_evidence\": [\n      \"Log entries showing living_room_temp_sensor reading 2493 at 06:20:00 and 2559 at 02:45:00.\",\n      \"Continuous OccupancySensing.Occupancy = 0 across all rooms from 00:00:00 to 06:12:00.\",\n      \"Presence of 5 lock_state_flips with no corroborating entrance_contact_sensor data during the anomaly window.\"\n    ],\n  \"recommended_actions\": [\n      \"Immediately reset all connected smart home devices (thermostats, locks, sensors) to factory settings.\",\n      \"Replace all temperature and occupancy sensors as they are unreliable and may fail in the future.\",\n      \"Contact the IoT service provider to report a critical firmware bug regarding temperature scaling and sensor fusion logic.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "Critical sensor failure causing physically impossible temperature readings (>2000°C) while occupancy sensors failed to detect human presence for over six hours, followed by a delayed and chaotic reactivation of the home system.", "reasoning": ["Temperature readings across all rooms consistently exceeded 2000 (e.g., 2493, 2559), which is physically impossible for a residential environment without total structural destruction, definitively ruling out real-world heat sources like fires or occupants.", "Occupancy sensors reported '0' (empty) for all rooms from 00:00 until 06:12, despite the logs indicating massive thermal energy accumulation; if humans were present to cause such heat, occupancy would have been detected immediately.", "The system exhibited erratic behavior including multiple 'lock_state_flips' without corresponding door contact events, and temperatures only stabilized after occupants returned at 06:12, suggesting a firmware bug or unit conversion error rather than an environmental event."], "key_evidence": ["Log entries showing living_room_temp_sensor reading 2493 at 06:20:00 and 2559 at 02:45:00.", "Continuous OccupancySensing.Occupancy = 0 across all rooms from 00:00:00 to 06:12:00.", "Presence of 5 lock_state_flips with no corroborating entrance_contact_sensor data during the anomaly window."], "recommended_actions": ["Immediately reset all connected smart home devices (thermostats, locks, sensors) to factory settings.", "Replace all temperature and occupancy sensors as they are unreliable and may fail in the future.", "Contact the IoT service provider to report a critical firmware bug regarding temperature scaling and sensor fusion logic."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 63.78584933280945, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 2302, "chunk_count": 29, "signals": {"room_activity": {"living_room": 402, "master_bedroom": 520, "kids_room": 520, "kitchen": 303, "dining_room": 223, "second_bedroom": 48, "master_bathroom": 54, "entrance": 231, "second_bathroom": 1}, "attribute_frequency": {"MeasuredValue": 1156, "Occupancy": 1097, "OnOff": 27, "StateValue": 7, "LockState": 5, "CurrentPositionLiftPercent100ths": 3, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 5, "occupancy_events": 1097, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\n    \"living_room\",\n    \"master_bedroom\",\n    \"kids_room\",\n    \"kitchen\"\n  ],\n  \"focus_devices\": [\n    \"temperature_sensor\",\n    \"occupancy_sensor\",\n    \"door_lock\",\n    \"contact_sensor\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C00\",\n    \"C01\",\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C28\"\n  ],\n  \"suspected_patterns\": [\n    \"Anomalous temperature readings (e.g., 2271, 2559) indicating potential sensor calibration failure or extreme environmental conditions.\",\n    \"High frequency of occupancy events ('alarmish_count' > 40 in later chunks) suggesting either a crowded house, sensor malfunction, or continuous loop activity.\",\n    \"Presence of 'lock_state_flips': 5 in the aggregate metrics requires verification against entrance contact sensors to rule out unauthorized access attempts.\",\n    \"Temperature trends show a non-linear rise and fall that does not strictly correlate with typical diurnal cycles or occupancy patterns.\"\n  ],\n  \"why_these_chunks\": [\n    \"C00-C04: Contain the initial anomalous temperature spike sequence starting at 2271 and rising to 2400+, critical for establishing baseline deviation.\",\n    \"C05-C06: Show the peak of the temperature anomaly (reaching ~2559) and the first clear signs of human occupancy returning after an empty period, linking the heat source to presence.\",\n    \"C28: The final chunk shows temperatures stabilizing around normal ranges (224-227), providing a post-event baseline to confirm if the earlier spikes were transient errors or sustained anomalies.\",\n    \"All selected chunks contain high 'alarmish_count' values (>20), indicating these are the periods where the system detected significant deviations requiring investigation.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["living_room", "master_bedroom", "kids_room", "kitchen"], "focus_devices": ["temperature_sensor", "occupancy_sensor", "door_lock", "contact_sensor"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04", "C05", "C28"], "suspected_patterns": ["Anomalous temperature readings (e.g., 2271, 2559) indicating potential sensor calibration failure or extreme environmental conditions.", "High frequency of occupancy events ('alarmish_count' > 40 in later chunks) suggesting either a crowded house, sensor malfunction, or continuous loop activity.", "Presence of 'lock_state_flips': 5 in the aggregate metrics requires verification against entrance contact sensors to rule out unauthorized access attempts.", "Temperature trends show a non-linear rise and fall that does not strictly correlate with typical diurnal cycles or occupancy patterns."], "why_these_chunks": ["C00-C04: Contain the initial anomalous temperature spike sequence starting at 2271 and rising to 2400+, critical for establishing baseline deviation.", "C05-C06: Show the peak of the temperature anomaly (reaching ~2559) and the first clear signs of human occupancy returning after an empty period, linking the heat source to presence.", "C28: The final chunk shows temperatures stabilizing around normal ranges (224-227), providing a post-event baseline to confirm if the earlier spikes were transient errors or sustained anomalies.", "All selected chunks contain high 'alarmish_count' values (>20), indicating these are the periods where the system detected significant deviations requiring investigation."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Sensor Calibration Drift / Unit Error\",\n      \"evidence\": [\n        \"All temperature readings across every room (living_room, master_bedroom, kids_room, kitchen) consistently exceed 2000 degrees.\",\n        \"The values start around 2271 and rise linearly to ~2493 over 6 hours, a pattern typical of sensor drift or unit conversion failure (e.g., reading in millikelvin or incorrect offset).\"\n      ],\n      \"weaknesses\": [\n        \"A real-world household cannot sustain internal temperatures above 100°C without structural damage or fire; this physical impossibility invalidates the 'normal' hypothesis.\"\n      ]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"Systematic Data Logging Artifact\",\n      \"evidence\": [\n        \"Occupancy sensors report '0' for all rooms continuously from 00:00 until 06:12, despite the massive thermal energy accumulation implied by the logs.\"\n      ],\n      \"weaknesses\": [\n        \"If occupants were present causing heat, occupancy sensors should eventually trigger. The prolonged absence contradicts the high-energy thermal state if interpreted as normal human habitation.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Critical Sensor Failure Leading to False Alarms\",\n      \"threat_type\": \"Data Integrity / System Malfunction\",\n      \"evidence\": [\n        \"Temperature values are physically impossible for a residential environment (ranging from 2271 to 2493).\",\n        \"The consistent nature of the error across multiple independent sensors suggests a shared firmware bug, unit misconfiguration (e.g., multiplying by 1000), or hardware fault rather than an environmental event.\",\n        \"The structured signals show 5 lock_state_flips but no corresponding door contact sensor events in the chunks, indicating potential desynchronization between security and HVAC systems.\"\n      ],\n      \"weaknesses\": [\n        \"This is a technical malfunction, not necessarily a security breach, though it compromises the reliability of all automated safety responses triggered by these false readings.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Potential Unauthorized Entry with Sensor Blind Spot\",\n      \"threat_type\": \"Security Breach (High Probability due to data noise)\",\n      \"evidence\": [\n        \"Presence of 'lock_state_flips': 5 in aggregate metrics without immediate correlation to entrance occupancy events in the raw chunks.\",\n        \"Despite the chaotic temperature data, the house remains reported as empty ('Occupancy': 0) for 6+ hours while the 'system' believes temperatures are skyrocketing, potentially masking an intruder who is bypassing standard detection logic or utilizing a signal jammer affecting the thermal sensors specifically.\"\n      ],\n      \"weaknesses\": [\n        \"The primary evidence is indirect (lock flips); the lack of direct motion or entry sensor logs in the provided focused chunks makes definitive confirmation difficult based solely on this text.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The magnitude of temperature readings (>2000) which definitively rules out normal environmental conditions and points to a critical system-level error.\",\n    \"The temporal gap between the final 'lock_state_flip' metric and the first legitimate 'Occupancy=1' event at 06:12, suggesting the anomaly period may have coincided with unauthorized access attempts.\"\n  ],\n  \"missing_information\": [\n    \"Raw log entries for 'entrance_contact_sensor' and 'door_lock_status' during the specific time windows where 'lock_state_flips' occurred.\",\n    \"Historical baseline temperature data to confirm if the sensor calibration has been drifting or if this is an acute event.\",\n    \"Alert history or user notifications generated during the 00:00-06:20 window to see if humans intervened.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Sensor Calibration Drift / Unit Error", "evidence": ["All temperature readings across every room (living_room, master_bedroom, kids_room, kitchen) consistently exceed 2000 degrees.", "The values start around 2271 and rise linearly to ~2493 over 6 hours, a pattern typical of sensor drift or unit conversion failure (e.g., reading in millikelvin or incorrect offset)."], "weaknesses": ["A real-world household cannot sustain internal temperatures above 100°C without structural damage or fire; this physical impossibility invalidates the 'normal' hypothesis."]}, {"id": "N2", "description": "Systematic Data Logging Artifact", "evidence": ["Occupancy sensors report '0' for all rooms continuously from 00:00 until 06:12, despite the massive thermal energy accumulation implied by the logs."], "weaknesses": ["If occupants were present causing heat, occupancy sensors should eventually trigger. The prolonged absence contradicts the high-energy thermal state if interpreted as normal human habitation."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Critical Sensor Failure Leading to False Alarms", "threat_type": "Data Integrity / System Malfunction", "evidence": ["Temperature values are physically impossible for a residential environment (ranging from 2271 to 2493).", "The consistent nature of the error across multiple independent sensors suggests a shared firmware bug, unit misconfiguration (e.g., multiplying by 1000), or hardware fault rather than an environmental event.", "The structured signals show 5 lock_state_flips but no corresponding door contact sensor events in the chunks, indicating potential desynchronization between security and HVAC systems."], "weaknesses": ["This is a technical malfunction, not necessarily a security breach, though it compromises the reliability of all automated safety responses triggered by these false readings."]}, {"id": "A2", "description": "Potential Unauthorized Entry with Sensor Blind Spot", "threat_type": "Security Breach (High Probability due to data noise)", "evidence": ["Presence of 'lock_state_flips': 5 in aggregate metrics without immediate correlation to entrance occupancy events in the raw chunks.", "Despite the chaotic temperature data, the house remains reported as empty ('Occupancy': 0) for 6+ hours while the 'system' believes temperatures are skyrocketing, potentially masking an intruder who is bypassing standard detection logic or utilizing a signal jammer affecting the thermal sensors specifically."], "weaknesses": ["The primary evidence is indirect (lock flips); the lack of direct motion or entry sensor logs in the provided focused chunks makes definitive confirmation difficult based solely on this text."]}], "most_discriminative_evidence": ["The magnitude of temperature readings (>2000) which definitively rules out normal environmental conditions and points to a critical system-level error.", "The temporal gap between the final 'lock_state_flip' metric and the first legitimate 'Occupancy=1' event at 06:12, suggesting the anomaly period may have coincided with unauthorized access attempts."], "missing_information": ["Raw log entries for 'entrance_contact_sensor' and 'door_lock_status' during the specific time windows where 'lock_state_flips' occurred.", "Historical baseline temperature data to confirm if the sensor calibration has been drifting or if this is an acute event.", "Alert history or user notifications generated during the 00:00-06:20 window to see if humans intervened."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C07\", \"C29\"],\n  \"missing_checks\": [\n    \"Verify raw 'entrance_contact_sensor' logs during the specific time windows of 'lock_state_flips' to confirm unauthorized entry.\",\n    \"Cross-reference alert history/user notifications for the 00:00-06:20 window to determine if humans intervened.\"\n  ],\n  \"supervisor_notes\": [\n    \"The investigation correctly identified the critical anomaly (impossible temperature readings) and ruled out normal hypotheses based on physical constraints.\",\n    \"However, the current evidence selection is insufficient to validate Hypothesis A2 (Unauthorized Entry). The Triage Output selected C00-C06 and C28 but missed the crucial time window immediately following the last lock flip before occupancy was detected at 06:12. Chunk C07 likely contains the transition period needed to correlate the lock flips with potential intrusion events.\",\n    \"Additionally, the total list of available chunks goes up to C28, but the Triage Output mentions a final chunk C28 as a post-event baseline. If the event timeline extends beyond what was analyzed in C00-C06, we need to ensure C28 is indeed the correct endpoint or if there are later chunks (like C29 which exists in the available list but wasn't initially flagged) that show the system recovery or return to normal. Wait, checking available list: it ends at C28. The Triage selected C28. The issue is specifically the gap around the lock flips.\",\n    \"Re-evaluating needs: The primary gap is the detailed log of entrance sensors during the flip events. While chunk selection covers the anomaly start/end, it lacks the granular data on the security interface (contact sensors) required to prove the 'blind spot' theory. We need chunks explicitly containing the 'entrance_contact_sensor' data points mentioned in missing information.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C07", "C29"], "missing_checks": ["Verify raw 'entrance_contact_sensor' logs during the specific time windows of 'lock_state_flips' to confirm unauthorized entry.", "Cross-reference alert history/user notifications for the 00:00-06:20 window to determine if humans intervened."], "supervisor_notes": ["The investigation correctly identified the critical anomaly (impossible temperature readings) and ruled out normal hypotheses based on physical constraints.", "However, the current evidence selection is insufficient to validate Hypothesis A2 (Unauthorized Entry). The Triage Output selected C00-C06 and C28 but missed the crucial time window immediately following the last lock flip before occupancy was detected at 06:12. Chunk C07 likely contains the transition period needed to correlate the lock flips with potential intrusion events.", "Additionally, the total list of available chunks goes up to C28, but the Triage Output mentions a final chunk C28 as a post-event baseline. If the event timeline extends beyond what was analyzed in C00-C06, we need to ensure C28 is indeed the correct endpoint or if there are later chunks (like C29 which exists in the available list but wasn't initially flagged) that show the system recovery or return to normal. Wait, checking available list: it ends at C28. The Triage selected C28. The issue is specifically the gap around the lock flips.", "Re-evaluating needs: The primary gap is the detailed log of entrance sensors during the flip events. While chunk selection covers the anomaly start/end, it lacks the granular data on the security interface (contact sensors) required to prove the 'blind spot' theory. We need chunks explicitly containing the 'entrance_contact_sensor' data points mentioned in missing information."]}, "preview_triage_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Layout\nLayout: 三室两厅 (3BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kids_room: 儿童房温度传感器<temperature_sensor>, 儿童房灯<dimmable_light>, 儿童房窗帘<window_covering>, 儿童房窗户传感器<contact_sensor>, 儿童房运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅副灯<dimmable_light>, 客厅氛围灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘1<window_covering>, 客厅窗户传感器1<contact_sensor>, 客厅窗户传感器2<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n- master_bathroom: 主卫漏水传感器<water_leak_detector>, 主卫灯<onoff_light>, 主卫运动传感器<occupancy_sensor>\n- master_bedroom: 主卧床头灯<onoff_light>, 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>\n- second_bedroom: 次卧灯<dimmable_light>, 次卧空调<air_conditioner>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 402,\n    \"master_bedroom\": 520,\n    \"kids_room\": 520,\n    \"kitchen\": 303,\n    \"dining_room\": 223,\n    \"second_bedroom\": 48,\n    \"master_bathroom\": 54,\n    \"entrance\": 231,\n    \"second_bathroom\": 1\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1156,\n    \"Occupancy\": 1097,\n    \"OnOff\": 27,\n    \"StateValue\": 7,\n    \"LockState\": 5,\n    \"CurrentPositionLiftPercent100ths\": 3,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 5,\n  \"occupancy_events\": 1097,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-17T00:00:00\",\n    \"end_ts\": \"2026-06-17T01:10:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 18,\n      \"master_bedroom\": 18,\n      \"kids_room\": 18,\n      \"kitchen\": 14,\n      \"dining_room\": 3,\n      \"second_bedroom\": 3,\n      \"master_bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"kids_room_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n ", "preview_verifier_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\n    \"living_room\",\n    \"master_bedroom\",\n    \"kids_room\",\n    \"kitchen\"\n  ],\n  \"focus_devices\": [\n    \"temperature_sensor\",\n    \"occupancy_sensor\",\n    \"door_lock\",\n    \"contact_sensor\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C00\",\n    \"C01\",\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C28\"\n  ],\n  \"suspected_patterns\": [\n    \"Anomalous temperature readings (e.g., 2271, 2559) indicating potential sensor calibration failure or extreme environmental conditions.\",\n    \"High frequency of occupancy events ('alarmish_count' > 40 in later chunks) suggesting either a crowded house, sensor malfunction, or continuous loop activity.\",\n    \"Presence of 'lock_state_flips': 5 in the aggregate metrics requires verification against entrance contact sensors to rule out unauthorized access attempts.\",\n    \"Temperature trends show a non-linear rise and fall that does not strictly correlate with typical diurnal cycles or occupancy patterns.\"\n  ],\n  \"why_these_chunks\": [\n    \"C00-C04: Contain the initial anomalous temperature spike sequence starting at 2271 and rising to 2400+, critical for establishing baseline deviation.\",\n    \"C05-C06: Show the peak of the temperature anomaly (reaching ~2559) and the first clear signs of human occupancy returning after an empty period, linking the heat source to presence.\",\n    \"C28: The final chunk shows temperatures stabilizing around normal ranges (224-227), providing a post-event baseline to confirm if the earlier spikes were transient errors or sustained anomalies.\",\n    \"All selected chunks contain high 'alarmish_count' values (>20), indicating these are the periods where the system detected significant deviations requiring investigation.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Sensor Calibration Drift / Unit Error\",\n      \"evidence\": [\n        \"All temperature readings across every room (living_room, master_bedroom, kids_room, kitchen) consistently exceed 2000 degrees.\",\n        \"The values start around 2271 and rise linearly to ~2493 over 6 hours, a pattern typical of sensor drift or unit conversion failure (e.g., reading in millikelvin or incorrect offset).\"\n      ],\n      \"weaknesses\": [\n        \"A real-world household cannot sustain internal temperatures above 100°C without structural damage or fire; this physical impossibility invalidates the 'n"}}
{"episode_id": "SQ4_FP_C_0861", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq4\\SQ4_FP_C_0861.json", "metadata": {"sq_type": "SQ4", "sq_name": "复合安全推理", "variant": "FP", "layout_id": "C", "layout_name": "三室两厅 (3BR)", "profile_id": "family_with_children", "base_date": "2026-06-09T00:00:00", "seed": 20261490, "scenario_id": "BA-03", "total_events": 2290, "anomaly_events_count": 5}, "ground_truth": {"scenario_id": "BA-03-FP", "scenario_name": "BA-03-FP: 小孩玩开关", "category": "behavioral_anomaly", "is_anomaly": false, "threat_type": "none", "key_difference": "只在儿童房一个房间内发生，kids_room_occupancy=1，有小孩在场", "difficulty_score": 10, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 3, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "kids_room", "injection_time": "2026-06-09T21:31:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"System-wide sensor calibration failure causing physically impossible temperature readings that falsely indicate a critical overheating event.\",\n  \"reasoning\": [\n      \"The temperature values (e.g., 2490, 2537) far exceed the maximum possible physical temperature for an indoor residential environment (~25°C) and even standard Celsius limits, strongly indicating a data encoding error (likely milli-Celsius stored as integer without division).\",\n      \"Despite these extreme 'readings', there is no corresponding activation of smoke detectors, CO alarms, or HVAC corrective actions (AC), which would be mandatory for real fire or overheating hazards.\",\n      \"The erratic nature of the data, including instantaneous jumps and drops between sensors in different rooms without logical cause (e.g., solar gain patterns), confirms a system-wide sensor logic or transmission fault rather than a physical heat source.\"\n    ],\n  \"key_evidence\": [\n      \"Temperature readings peaking at ~2537 while occupancy logs show residents present but unharmed and no alarm triggers occur.\",\n      \"Absence of any smoke/CO alarm events or HVAC intervention logs during the period where temperatures allegedly reached lethal levels.\",\n      \"Data pattern shows uniform distribution across rooms initially, then random divergence inconsistent with thermal physics.\"\n    ],\n  \"recommended_actions\": [\n      \"Immediately inspect all temperature sensors for firmware issues or unit configuration errors (verify if reading is mC vs C).\",\n      \"Reset the sensor network and recalibrate devices to ensure accurate baseline readings before re-enabling automated alerts.\",\n      \"Review raw device metadata to confirm the specific data type and scaling factor used by the IoT platform.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "System-wide sensor calibration failure causing physically impossible temperature readings that falsely indicate a critical overheating event.", "reasoning": ["The temperature values (e.g., 2490, 2537) far exceed the maximum possible physical temperature for an indoor residential environment (~25°C) and even standard Celsius limits, strongly indicating a data encoding error (likely milli-Celsius stored as integer without division).", "Despite these extreme 'readings', there is no corresponding activation of smoke detectors, CO alarms, or HVAC corrective actions (AC), which would be mandatory for real fire or overheating hazards.", "The erratic nature of the data, including instantaneous jumps and drops between sensors in different rooms without logical cause (e.g., solar gain patterns), confirms a system-wide sensor logic or transmission fault rather than a physical heat source."], "key_evidence": ["Temperature readings peaking at ~2537 while occupancy logs show residents present but unharmed and no alarm triggers occur.", "Absence of any smoke/CO alarm events or HVAC intervention logs during the period where temperatures allegedly reached lethal levels.", "Data pattern shows uniform distribution across rooms initially, then random divergence inconsistent with thermal physics."], "recommended_actions": ["Immediately inspect all temperature sensors for firmware issues or unit configuration errors (verify if reading is mC vs C).", "Reset the sensor network and recalibrate devices to ensure accurate baseline readings before re-enabling automated alerts.", "Review raw device metadata to confirm the specific data type and scaling factor used by the IoT platform."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 63.75222086906433, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 2290, "chunk_count": 29, "signals": {"room_activity": {"living_room": 403, "master_bedroom": 519, "kids_room": 520, "kitchen": 303, "dining_room": 217, "second_bedroom": 48, "master_bathroom": 52, "entrance": 227, "second_bathroom": 1}, "attribute_frequency": {"MeasuredValue": 1156, "Occupancy": 1082, "OnOff": 30, "StateValue": 7, "LockState": 5, "CurrentPositionLiftPercent100ths": 3, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 5, "occupancy_events": 1082, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\n    \"kitchen\",\n    \"living_room\",\n    \"master_bedroom\",\n    \"kids_room\"\n  ],\n  \"focus_devices\": [\n    \"temperature_sensor\",\n    \"occupancy_sensor\",\n    \"smoke_co_alarm\",\n    \"water_leak_detector\",\n    \"door_lock\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C00\",\n    \"C01\",\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C06\"\n  ],\n  \"suspected_patterns\": [\n    \"Rapid temperature rise across multiple rooms during night/early morning hours (C00-C04) suggesting HVAC failure or external heat gain.\",\n    \"Persistent occupancy in sleeping areas combined with high temperatures indicates potential overheating risk for residents.\",\n    \"High alarmish_count in early chunks correlates with the temperature spike, indicating system detection of anomalies.\",\n    \"Sudden drop in temperature readings in later chunks (C20+) suggests a corrective action (AC on) or sensor drift requiring verification.\"\n  ],\n  \"why_these_chunks\": [\n    \"C00-C04 show the baseline and the onset of the critical temperature anomaly (rising from ~22°C to >24°C).\",\n    \"C05-C06 capture the peak temperature values (>25°C) coinciding with resident presence, representing the highest safety risk window.\",\n    \"These chunks contain the 'top_devices' list heavily weighted towards temperature sensors, confirming the primary data stream driving the safety inference.\",\n    \"The transition from these high-temp chunks to later normal-reading chunks is necessary to determine if the event was a transient fault or a sustained hazard.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "living_room", "master_bedroom", "kids_room"], "focus_devices": ["temperature_sensor", "occupancy_sensor", "smoke_co_alarm", "water_leak_detector", "door_lock"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04", "C05", "C06"], "suspected_patterns": ["Rapid temperature rise across multiple rooms during night/early morning hours (C00-C04) suggesting HVAC failure or external heat gain.", "Persistent occupancy in sleeping areas combined with high temperatures indicates potential overheating risk for residents.", "High alarmish_count in early chunks correlates with the temperature spike, indicating system detection of anomalies.", "Sudden drop in temperature readings in later chunks (C20+) suggests a corrective action (AC on) or sensor drift requiring verification."], "why_these_chunks": ["C00-C04 show the baseline and the onset of the critical temperature anomaly (rising from ~22°C to >24°C).", "C05-C06 capture the peak temperature values (>25°C) coinciding with resident presence, representing the highest safety risk window.", "These chunks contain the 'top_devices' list heavily weighted towards temperature sensors, confirming the primary data stream driving the safety inference.", "The transition from these high-temp chunks to later normal-reading chunks is necessary to determine if the event was a transient fault or a sustained hazard."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The house is empty, and the temperature readings represent a stable outdoor ambient temperature (approx. 22-23°C) that slowly rises due to external weather conditions (e.g., hot summer day).\",\n      \"evidence\": [\n        \"All room occupancy sensors consistently report 0 until 06:11.\",\n        \"Temperature values across all rooms remain relatively uniform (within 5-10 degrees of each other), suggesting no localized heat sources like appliances or people.\",\n        \"The gradual rise from ~22.7 to ~24.9 could be attributed to solar gain or rising outside temperatures.\"\n      ],\n      \"weaknesses\": [\n        \"A rise of ~2.2 degrees Celsius over 6 hours in an enclosed house with no HVAC activity is unusually steep for pure ambient drift.\",\n        \"Sensor precision appears inconsistent; values fluctuate wildly between readings (e.g., Kids Room jumps from 2482 to 2492 in one minute), which is not characteristic of passive thermal mass responding to ambient air.\",\n        \"The magnitude of the reading (2490) likely exceeds the maximum measurable range for standard Celsius sensors if interpreted literally as °C, implying a data encoding error or scale issue rather than physical reality.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Critical Sensor Calibration Failure / Data Encoding Error causing false high-temperature readings.\",\n      \"threat_type\": \"Data Integrity / False Positive\",\n      \"evidence\": [\n        \"Temperature values exceed physically plausible limits for indoor environments (peaking at 2490, likely meant to be 24.90°C but encoded as integer * 100 or similar).\",\n        \"Erratic short-term variance: The same room shows different temperatures minutes apart without cause (e.g., Master Bedroom drops from 2494 to 2478 instantly at 06:15, then rises again).\",\n        \"Lack of correlation with occupancy events: Occupancy changes do not trigger expected thermal spikes, yet temperatures continue to 'rise' erratically.\",\n        \"Uniformity paradox: While values are uniform initially, they diverge significantly later (Kitchen vs Master Bedroom) without logical cause (e.g., stove use).\"\n      ],\n      \"weaknesses\": [\n        \"Does not explain the 'heat' threat itself unless the system logic misinterprets these numbers as a fire risk, triggering unnecessary alarms.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Undetected Fire or Uncontrolled Heat Source leading to actual overheating.\",\n      \"threat_type\": \"Safety Hazard\",\n      \"evidence\": [\n        \"Continuous upward trend in temperature readings throughout the monitoring period.\",\n        \"High absolute values (if interpreted correctly as scaled integers) indicate extreme heat.\"\n      ],\n      \"weaknesses\": [\n        \"No smoke detector or fire alarm signals are present in the provided chunks.\",\n        \"The lack of occupant presence during the peak heating phase makes it harder to verify if residents were exposed, though the event occurs while the house was unoccupied.\",\n        \"The erratic nature of the data points (instant drops and jumps) contradicts the physics of a real fire, which would show a monotonic increase.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The instantaneous temperature drop in the master bedroom from 2494 to 2478 at 06:15 despite no change in environmental conditions strongly indicates sensor noise or calibration drift, ruling out a real fire (which would only get hotter).\",\n    \"The value '2490' appearing repeatedly suggests a unit conversion failure (likely 24.90°C stored as an integer) rather than an actual 2490°C environment, which would destroy the structure immediately.\"\n  ],\n  \"missing_information\": [\n    \"Raw device metadata to confirm the unit of measurement (Celsius vs Fahrenheit vs milli-Celsius).\",\n    \"HVAC system logs to determine if the AC/HVAC was active or in 'Off' mode during this period.\",\n    \"Smoke/CO alarm status logs to rule out concurrent safety events.\",\n    \"Calibration history for the specific temperature sensors mentioned.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The house is empty, and the temperature readings represent a stable outdoor ambient temperature (approx. 22-23°C) that slowly rises due to external weather conditions (e.g., hot summer day).", "evidence": ["All room occupancy sensors consistently report 0 until 06:11.", "Temperature values across all rooms remain relatively uniform (within 5-10 degrees of each other), suggesting no localized heat sources like appliances or people.", "The gradual rise from ~22.7 to ~24.9 could be attributed to solar gain or rising outside temperatures."], "weaknesses": ["A rise of ~2.2 degrees Celsius over 6 hours in an enclosed house with no HVAC activity is unusually steep for pure ambient drift.", "Sensor precision appears inconsistent; values fluctuate wildly between readings (e.g., Kids Room jumps from 2482 to 2492 in one minute), which is not characteristic of passive thermal mass responding to ambient air.", "The magnitude of the reading (2490) likely exceeds the maximum measurable range for standard Celsius sensors if interpreted literally as °C, implying a data encoding error or scale issue rather than physical reality."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Critical Sensor Calibration Failure / Data Encoding Error causing false high-temperature readings.", "threat_type": "Data Integrity / False Positive", "evidence": ["Temperature values exceed physically plausible limits for indoor environments (peaking at 2490, likely meant to be 24.90°C but encoded as integer * 100 or similar).", "Erratic short-term variance: The same room shows different temperatures minutes apart without cause (e.g., Master Bedroom drops from 2494 to 2478 instantly at 06:15, then rises again).", "Lack of correlation with occupancy events: Occupancy changes do not trigger expected thermal spikes, yet temperatures continue to 'rise' erratically.", "Uniformity paradox: While values are uniform initially, they diverge significantly later (Kitchen vs Master Bedroom) without logical cause (e.g., stove use)."], "weaknesses": ["Does not explain the 'heat' threat itself unless the system logic misinterprets these numbers as a fire risk, triggering unnecessary alarms."]}, {"id": "A2", "description": "Undetected Fire or Uncontrolled Heat Source leading to actual overheating.", "threat_type": "Safety Hazard", "evidence": ["Continuous upward trend in temperature readings throughout the monitoring period.", "High absolute values (if interpreted correctly as scaled integers) indicate extreme heat."], "weaknesses": ["No smoke detector or fire alarm signals are present in the provided chunks.", "The lack of occupant presence during the peak heating phase makes it harder to verify if residents were exposed, though the event occurs while the house was unoccupied.", "The erratic nature of the data points (instant drops and jumps) contradicts the physics of a real fire, which would show a monotonic increase."]}], "most_discriminative_evidence": ["The instantaneous temperature drop in the master bedroom from 2494 to 2478 at 06:15 despite no change in environmental conditions strongly indicates sensor noise or calibration drift, ruling out a real fire (which would only get hotter).", "The value '2490' appearing repeatedly suggests a unit conversion failure (likely 24.90°C stored as an integer) rather than an actual 2490°C environment, which would destroy the structure immediately."], "missing_information": ["Raw device metadata to confirm the unit of measurement (Celsius vs Fahrenheit vs milli-Celsius).", "HVAC system logs to determine if the AC/HVAC was active or in 'Off' mode during this period.", "Smoke/CO alarm status logs to rule out concurrent safety events.", "Calibration history for the specific temperature sensors mentioned."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C07\", \"C08\", \"C09\", \"C10\"],\n  \"missing_checks\": [\n    \"Verify HVAC system logs to confirm if AC was active during the temperature spike.\",\n    \"Cross-reference smoke/CO alarm status logs for any triggered events despite lack of explicit 'alarm' flags in current chunks.\",\n    \"Check sensor calibration history and raw metadata units (e.g., milli-Celsius vs Celsius) to definitively rule out data encoding errors.\",\n    \"Analyze later chunks (C20+) to determine if the temperature drop represents a corrective action (AC on) or persistent sensor drift.\"\n  ],\n  \"supervisor_notes\": [\n    \"The investigation correctly identified potential data integrity issues (encoding errors) versus physical anomalies, but stopped too early. The hypothesis regarding sensor failure relies heavily on the erratic nature of C00-C06.\",\n    \"More chunks are needed to see the trend after the 'drop' mentioned in the Triage Output (C20+). We need to see if temperatures stabilize at a normal level (supporting the sensor error theory) or continue to climb (supporting an undetected heat source).\",\n    \"The current evidence set does not include HVAC operational logs, which is critical to distinguishing between external heat gain, appliance usage, or HVAC failure.\",\n    \"While the focus is on safety, the primary conclusion hinges on data quality. Without confirming the unit of measurement via metadata or seeing the long-term trend, we cannot definitively state the home is safe from overheating.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C07", "C08", "C09", "C10"], "missing_checks": ["Verify HVAC system logs to confirm if AC was active during the temperature spike.", "Cross-reference smoke/CO alarm status logs for any triggered events despite lack of explicit 'alarm' flags in current chunks.", "Check sensor calibration history and raw metadata units (e.g., milli-Celsius vs Celsius) to definitively rule out data encoding errors.", "Analyze later chunks (C20+) to determine if the temperature drop represents a corrective action (AC on) or persistent sensor drift."], "supervisor_notes": ["The investigation correctly identified potential data integrity issues (encoding errors) versus physical anomalies, but stopped too early. The hypothesis regarding sensor failure relies heavily on the erratic nature of C00-C06.", "More chunks are needed to see the trend after the 'drop' mentioned in the Triage Output (C20+). We need to see if temperatures stabilize at a normal level (supporting the sensor error theory) or continue to climb (supporting an undetected heat source).", "The current evidence set does not include HVAC operational logs, which is critical to distinguishing between external heat gain, appliance usage, or HVAC failure.", "While the focus is on safety, the primary conclusion hinges on data quality. Without confirming the unit of measurement via metadata or seeing the long-term trend, we cannot definitively state the home is safe from overheating."]}, "preview_triage_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Layout\nLayout: 三室两厅 (3BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kids_room: 儿童房温度传感器<temperature_sensor>, 儿童房灯<dimmable_light>, 儿童房窗帘<window_covering>, 儿童房窗户传感器<contact_sensor>, 儿童房运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅副灯<dimmable_light>, 客厅氛围灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘1<window_covering>, 客厅窗户传感器1<contact_sensor>, 客厅窗户传感器2<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n- master_bathroom: 主卫漏水传感器<water_leak_detector>, 主卫灯<onoff_light>, 主卫运动传感器<occupancy_sensor>\n- master_bedroom: 主卧床头灯<onoff_light>, 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>\n- second_bedroom: 次卧灯<dimmable_light>, 次卧空调<air_conditioner>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 403,\n    \"master_bedroom\": 519,\n    \"kids_room\": 520,\n    \"kitchen\": 303,\n    \"dining_room\": 217,\n    \"second_bedroom\": 48,\n    \"master_bathroom\": 52,\n    \"entrance\": 227,\n    \"second_bathroom\": 1\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1156,\n    \"Occupancy\": 1082,\n    \"OnOff\": 30,\n    \"StateValue\": 7,\n    \"LockState\": 5,\n    \"CurrentPositionLiftPercent100ths\": 3,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 5,\n  \"occupancy_events\": 1082,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-09T00:00:00\",\n    \"end_ts\": \"2026-06-09T01:10:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 18,\n      \"master_bedroom\": 18,\n      \"kids_room\": 18,\n      \"kitchen\": 14,\n      \"dining_room\": 3,\n      \"second_bedroom\": 3,\n      \"master_bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"kids_room_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n ", "preview_verifier_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\n    \"kitchen\",\n    \"living_room\",\n    \"master_bedroom\",\n    \"kids_room\"\n  ],\n  \"focus_devices\": [\n    \"temperature_sensor\",\n    \"occupancy_sensor\",\n    \"smoke_co_alarm\",\n    \"water_leak_detector\",\n    \"door_lock\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C00\",\n    \"C01\",\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C06\"\n  ],\n  \"suspected_patterns\": [\n    \"Rapid temperature rise across multiple rooms during night/early morning hours (C00-C04) suggesting HVAC failure or external heat gain.\",\n    \"Persistent occupancy in sleeping areas combined with high temperatures indicates potential overheating risk for residents.\",\n    \"High alarmish_count in early chunks correlates with the temperature spike, indicating system detection of anomalies.\",\n    \"Sudden drop in temperature readings in later chunks (C20+) suggests a corrective action (AC on) or sensor drift requiring verification.\"\n  ],\n  \"why_these_chunks\": [\n    \"C00-C04 show the baseline and the onset of the critical temperature anomaly (rising from ~22°C to >24°C).\",\n    \"C05-C06 capture the peak temperature values (>25°C) coinciding with resident presence, representing the highest safety risk window.\",\n    \"These chunks contain the 'top_devices' list heavily weighted towards temperature sensors, confirming the primary data stream driving the safety inference.\",\n    \"The transition from these high-temp chunks to later normal-reading chunks is necessary to determine if the event was a transient fault or a sustained hazard.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The house is empty, and the temperature readings represent a stable outdoor ambient temperature (approx. 22-23°C) that slowly rises due to external weather conditions (e.g., hot summer day).\",\n      \"evidence\": [\n        \"All room occupancy sensors consistently report 0 until 06:11.\",\n        \"Temperature values across all rooms remain relatively uniform (within 5-10 degrees of each other), suggesting no localized heat sources like appliances or people.\",\n        \"The gradual rise from ~22.7 to ~24.9 could be attributed to solar gain or rising outside temperatures.\"\n      ],\n      \"weaknesses\": [\n        \"A rise of ~2.2 degrees Celsius over 6 hours in an enclosed house with no HVAC activity is unusually steep for pure ambient drift.\",\n        \"Sensor precision appears"}}
{"episode_id": "SQ4_TP_A_0720", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq4\\SQ4_TP_A_0720.json", "metadata": {"sq_type": "SQ4", "sq_name": "复合安全推理", "variant": "TP", "layout_id": "A", "layout_name": "一室一厅 (Studio/1BR)", "profile_id": "young_professional", "base_date": "2026-06-02T00:00:00", "seed": 20261349, "scenario_id": "FG-01", "total_events": 1284, "anomaly_events_count": 7}, "ground_truth": {"scenario_id": "FG-01", "scenario_name": "厨房忘关火", "category": "fire_gas", "is_anomaly": true, "threat_type": "unattended_cooking", "key_evidence": ["灶具开启状态 + 厨房无人（occupancy=0）持续超过5分钟", "厨房温度持续异常上升", "最终烟雾报警器触发"], "expected_response": "立即提醒住户关闭灶具，如无法联系则自动关闭（如支持远程关闭）", "difficulty_score": 11, "difficulty_level": 3, "difficulty_label": "L3_composite_reasoning", "difficulty_dimensions": {"D1_evidence_count": 3, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 2, "D5_fp_similarity": 2}, "target_room": "living_room", "injection_time": "2026-06-02T01:11:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"All temperature sensors across the home are reporting impossible values (ranging from ~2100 to ~2600) due to a severe calibration error or unit mismatch, rendering environmental safety monitoring invalid.\",\n  \"reasoning\": [\n      \"Temperature readings in chunks C02 through C15 consistently exceed 2000 units (e.g., 2466°C), which is physically impossible for residential environments and definitively rules out normal operation.\",\n      \"The anomaly persists continuously over an 18-hour period (03:35 to 23:50), indicating a systemic hardware failure or firmware bug rather than a transient glitch or external heat source.\",\n      \"Occupancy and appliance logs show normal human activity (lights on, windows opened, cooking) during these periods, yet temperatures continue to drift upwards or remain erroneously high, proving the sensor logic is decoupled from physical reality.\",\n      \"While the Triage noted potential security concerns regarding early morning door events, the lack of lock/unlock cycle data in the provided text and the overwhelming evidence of sensor failure prioritizes the device malfunction as the critical safety issue.\"\n    ],\n  \"key_evidence\": [\n      \"C02-C03: Living room sensor reads 2466 at 05:30 with 0 occupancy; bedroom reads 2358.\",\n      \"C12-C13: Kitchen sensor reads 2284 while stove is off, and bedroom reads 2174, showing no correlation between activity and realistic temperature changes.\",\n      \"C15: Sensors still report ~2250-2270 range late at night, confirming the error has not reset or self-corrected.\",\n      \"Absence of any reading below 2000 suggests the raw ADC counts or millikelvin values were interpreted incorrectly without proper scaling.\"\n    ],\n  \"recommended_actions\": [\n      \"Immediately disable all connected smart thermostats and HVAC systems to prevent the system from attempting to cool/heat based on false 'extreme heat' readings.\",\n      \"Manually verify actual room temperatures using independent physical thermometers and document baseline values.\",\n      \"Perform a factory reset or firmware update on the IoT hub/sensors, or replace the affected temperature sensor devices.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "All temperature sensors across the home are reporting impossible values (ranging from ~2100 to ~2600) due to a severe calibration error or unit mismatch, rendering environmental safety monitoring invalid.", "reasoning": ["Temperature readings in chunks C02 through C15 consistently exceed 2000 units (e.g., 2466°C), which is physically impossible for residential environments and definitively rules out normal operation.", "The anomaly persists continuously over an 18-hour period (03:35 to 23:50), indicating a systemic hardware failure or firmware bug rather than a transient glitch or external heat source.", "Occupancy and appliance logs show normal human activity (lights on, windows opened, cooking) during these periods, yet temperatures continue to drift upwards or remain erroneously high, proving the sensor logic is decoupled from physical reality.", "While the Triage noted potential security concerns regarding early morning door events, the lack of lock/unlock cycle data in the provided text and the overwhelming evidence of sensor failure prioritizes the device malfunction as the critical safety issue."], "key_evidence": ["C02-C03: Living room sensor reads 2466 at 05:30 with 0 occupancy; bedroom reads 2358.", "C12-C13: Kitchen sensor reads 2284 while stove is off, and bedroom reads 2174, showing no correlation between activity and realistic temperature changes.", "C15: Sensors still report ~2250-2270 range late at night, confirming the error has not reset or self-corrected.", "Absence of any reading below 2000 suggests the raw ADC counts or millikelvin values were interpreted incorrectly without proper scaling."], "recommended_actions": ["Immediately disable all connected smart thermostats and HVAC systems to prevent the system from attempting to cool/heat based on false 'extreme heat' readings.", "Manually verify actual room temperatures using independent physical thermometers and document baseline values.", "Perform a factory reset or firmware update on the IoT hub/sensors, or replace the affected temperature sensor devices."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 55.06095623970032, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1284, "chunk_count": 17, "signals": {"room_activity": {"living_room": 403, "bedroom": 508, "kitchen": 304, "bathroom": 55, "entrance": 14}, "attribute_frequency": {"MeasuredValue": 868, "Occupancy": 376, "OnOff": 19, "StateValue": 5, "LockState": 4, "CurrentPositionLiftPercent100ths": 2, "SmokeState": 1, "ExpressedState": 1, "SystemMode": 1, "OperationalState": 1, "CurrentLevel": 1}, "lock_state_flips": 4, "occupancy_events": 376, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\", \"bedroom\"],\n  \"focus_devices\": [\"temperature_sensor\", \"occupancy_sensor\", \"contact_sensor\"],\n  \"focus_chunk_ids\": [\"C02\", \"C03\", \"C12\", \"C13\"],\n  \"suspected_patterns\": [\n    \"Abnormal temperature scaling (values in thousands suggesting unit mismatch or sensor drift)\",\n    \"Correlation between high occupancy events and elevated temperature readings in living areas\",\n    \"Potential security breach indicated by entrance contact sensor activity late at night\"\n  ],\n  \"why_these_chunks\": [\n    \"C02-C03 show the peak of anomalous temperature readings during low-occupancy periods, indicating potential environmental hazards or sensor failure.\",\n    \"C12-C13 display the highest alarm counts and significant temperature spikes coinciding with active occupancy, requiring immediate safety verification.\",\n    \"The transition from C14 to C16 shows reduced activity but persistent monitoring needs due to previous anomalies.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "living_room", "bedroom"], "focus_devices": ["temperature_sensor", "occupancy_sensor", "contact_sensor"], "focus_chunk_ids": ["C02", "C03", "C12", "C13"], "suspected_patterns": ["Abnormal temperature scaling (values in thousands suggesting unit mismatch or sensor drift)", "Correlation between high occupancy events and elevated temperature readings in living areas", "Potential security breach indicated by entrance contact sensor activity late at night"], "why_these_chunks": ["C02-C03 show the peak of anomalous temperature readings during low-occupancy periods, indicating potential environmental hazards or sensor failure.", "C12-C13 display the highest alarm counts and significant temperature spikes coinciding with active occupancy, requiring immediate safety verification.", "The transition from C14 to C16 shows reduced activity but persistent monitoring needs due to previous anomalies."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Sensor calibration drift or firmware bug causing offset values.\",\n      \"evidence\": [\"Temperature readings in C02-C03 (e.g., 2466) are consistently high but stable relative to each other across rooms during the early morning hours, suggesting a systematic error rather than random noise.\", \"In C12-C13, temperatures drop into realistic ranges (~22-26) as occupancy increases and appliances run, implying the sensor logic functions correctly when active.\"],\n      \"weaknesses\": [\"Does not explain why the 'realistic' range starts at ~2174 instead of ~20-25. An offset of +2000 is too large for a simple linear calibration error without affecting the lower-range data.\", \"Fails to account for the complete absence of temperature data points in C02/C03 between 06:38 and 07:00 where lights and windows were actively manipulated.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Critical Sensor Failure/Calibration Catastrophe leading to false environmental alarms.\",\n      \"threat_type\": \"Environmental Safety Hazard (False Positive)\",\n      \"evidence\": [\"C02 & C03 show persistent values >2200 (e.g., 2495) while actual ambient temps should be <30°C. This indicates a severe scaling error or unit mismatch (e.g., reading milliKelvin or raw ADC counts).\", \"Data gaps exist in C02/C03 specifically after human activity begins (06:38), coinciding with light/window changes, suggesting the sensor may have frozen, crashed, or lost power during state transitions.\", \"The magnitude of the error (>2000 units) renders all thermal safety checks invalid until reset.\"],\n      \"weaknesses\": [\"Relies on external knowledge of normal room temperatures; if the house is indeed kept at extreme heat (unlikely), this hypothesis fails.\"],\n      \"threat_level\": \"High\"\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Potential Security Breach / Tailgating Event at Entrance.\",\n      \"threat_type\": \"Security Intrusion\",\n      \"evidence\": [\"Structured Signals show `entrance` activity count of 14, significantly higher than `bathroom` (55) but occurring outside typical waking hours based on C02 timestamps (03:35-05:30).\", \"C02 shows no occupancy in living areas during these early morning hours, yet entrance sensors triggered multiple times. If residents are asleep in bedrooms, frequent entrance triggers suggest someone entering/exiting the home while it was ostensibly empty or locked down.\"],\n      \"weaknesses\": [\"Could be a pet, delivery driver, or family member moving between rooms (e.g., retrieving medication before bed).\"],\n      \"threat_level\": \"Medium\"\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The impossibility of room temperatures being 2200°C-2500°C (Evidence from C02, C03, C12), which definitively rules out 'normal operation' and forces a conclusion of sensor failure or data corruption.\",\n    \"The temporal correlation between the start of anomalous readings (03:35) and low occupancy, contrasted with data loss during active human movement (06:38+), suggesting hardware instability under load or environmental stress.\"\n  ],\n  \"missing_information\": [\n    \"Raw device logs for the specific timestamp 06:38:00 - 06:40:00 to determine if the temperature sensor crashed during the bedroom window/light activation.\",\n    \"Historical baseline temperature readings for this household to confirm if 2174 (C13 start) is an anomaly or a new baseline.\",\n    \"Access logs for the Entrance sensor to verify if the 14 events correspond to lock/unlock cycles or just motion detection.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Sensor calibration drift or firmware bug causing offset values.", "evidence": ["Temperature readings in C02-C03 (e.g., 2466) are consistently high but stable relative to each other across rooms during the early morning hours, suggesting a systematic error rather than random noise.", "In C12-C13, temperatures drop into realistic ranges (~22-26) as occupancy increases and appliances run, implying the sensor logic functions correctly when active."], "weaknesses": ["Does not explain why the 'realistic' range starts at ~2174 instead of ~20-25. An offset of +2000 is too large for a simple linear calibration error without affecting the lower-range data.", "Fails to account for the complete absence of temperature data points in C02/C03 between 06:38 and 07:00 where lights and windows were actively manipulated."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Critical Sensor Failure/Calibration Catastrophe leading to false environmental alarms.", "threat_type": "Environmental Safety Hazard (False Positive)", "evidence": ["C02 & C03 show persistent values >2200 (e.g., 2495) while actual ambient temps should be <30°C. This indicates a severe scaling error or unit mismatch (e.g., reading milliKelvin or raw ADC counts).", "Data gaps exist in C02/C03 specifically after human activity begins (06:38), coinciding with light/window changes, suggesting the sensor may have frozen, crashed, or lost power during state transitions.", "The magnitude of the error (>2000 units) renders all thermal safety checks invalid until reset."], "weaknesses": ["Relies on external knowledge of normal room temperatures; if the house is indeed kept at extreme heat (unlikely), this hypothesis fails."], "threat_level": "High"}, {"id": "A2", "description": "Potential Security Breach / Tailgating Event at Entrance.", "threat_type": "Security Intrusion", "evidence": ["Structured Signals show `entrance` activity count of 14, significantly higher than `bathroom` (55) but occurring outside typical waking hours based on C02 timestamps (03:35-05:30).", "C02 shows no occupancy in living areas during these early morning hours, yet entrance sensors triggered multiple times. If residents are asleep in bedrooms, frequent entrance triggers suggest someone entering/exiting the home while it was ostensibly empty or locked down."], "weaknesses": ["Could be a pet, delivery driver, or family member moving between rooms (e.g., retrieving medication before bed)."], "threat_level": "Medium"}], "most_discriminative_evidence": ["The impossibility of room temperatures being 2200°C-2500°C (Evidence from C02, C03, C12), which definitively rules out 'normal operation' and forces a conclusion of sensor failure or data corruption.", "The temporal correlation between the start of anomalous readings (03:35) and low occupancy, contrasted with data loss during active human movement (06:38+), suggesting hardware instability under load or environmental stress."], "missing_information": ["Raw device logs for the specific timestamp 06:38:00 - 06:40:00 to determine if the temperature sensor crashed during the bedroom window/light activation.", "Historical baseline temperature readings for this household to confirm if 2174 (C13 start) is an anomaly or a new baseline.", "Access logs for the Entrance sensor to verify if the 14 events correspond to lock/unlock cycles or just motion detection."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C04\", \"C15\"],\n  \"missing_checks\": [\n    \"Verify data continuity and error codes in C04 to confirm if the sensor crash at 06:38 was isolated or part of a larger sequence.\",\n    \"Check C15 for any subsequent temperature recoveries or reset events after the anomaly window.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis is highly on-topic and correctly identifies the critical safety risks (sensor failure vs. security breach).\",\n    \"However, evidence sufficiency is low because the hypothesis regarding the 'crash' during human activity relies on a specific gap (06:38) that needs context from adjacent chunks (C04/C15) to determine cause-and-effect.\",\n    \"The Triage output suggested focusing on C02-C03 and C12-C13, but the Investigator's hypothesis about the timing of the crash relative to light/window manipulation requires checking the chunk immediately following C03 (C04) and potentially C15 to see if the system recovered or entered an error state.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C04", "C15"], "missing_checks": ["Verify data continuity and error codes in C04 to confirm if the sensor crash at 06:38 was isolated or part of a larger sequence.", "Check C15 for any subsequent temperature recoveries or reset events after the anomaly window."], "supervisor_notes": ["The analysis is highly on-topic and correctly identifies the critical safety risks (sensor failure vs. security breach).", "However, evidence sufficiency is low because the hypothesis regarding the 'crash' during human activity relies on a specific gap (06:38) that needs context from adjacent chunks (C04/C15) to determine cause-and-effect.", "The Triage output suggested focusing on C02-C03 and C12-C13, but the Investigator's hypothesis about the timing of the crash relative to light/window manipulation requires checking the chunk immediately following C03 (C04) and potentially C15 to see if the system recovered or entered an error state."]}, "preview_triage_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Layout\nLayout: 一室一厅 (Studio/1BR)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅台灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 403,\n    \"bedroom\": 508,\n    \"kitchen\": 304,\n    \"bathroom\": 55,\n    \"entrance\": 14\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 868,\n    \"Occupancy\": 376,\n    \"OnOff\": 19,\n    \"StateValue\": 5,\n    \"LockState\": 4,\n    \"CurrentPositionLiftPercent100ths\": 2,\n    \"SmokeState\": 1,\n    \"ExpressedState\": 1,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 376,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-02T00:00:00\",\n    \"end_ts\": \"2026-06-02T01:40:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 26,\n      \"bedroom\": 24,\n      \"kitchen\": 26,\n      \"bathroom\": 4\n    },\n    \"top_devices\": [\n      \"kitchen_temp_sensor\",\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"bathroom_occupancy\"\n    ],\n    \"alarmish_count\": 14,\n    \"preview_lines\": [\n      \"[2026-06-02T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2281\",\n      \"[2026-06-02T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2168\",\n      \"[2026-06-02T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2274\",\n      \"[2026-06-02T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-02T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-02T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-02T00:05:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2268\",\n      \"[2026-06-02T00:05:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2168\",\n", "preview_verifier_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\", \"bedroom\"],\n  \"focus_devices\": [\"temperature_sensor\", \"occupancy_sensor\", \"contact_sensor\"],\n  \"focus_chunk_ids\": [\"C02\", \"C03\", \"C12\", \"C13\"],\n  \"suspected_patterns\": [\n    \"Abnormal temperature scaling (values in thousands suggesting unit mismatch or sensor drift)\",\n    \"Correlation between high occupancy events and elevated temperature readings in living areas\",\n    \"Potential security breach indicated by entrance contact sensor activity late at night\"\n  ],\n  \"why_these_chunks\": [\n    \"C02-C03 show the peak of anomalous temperature readings during low-occupancy periods, indicating potential environmental hazards or sensor failure.\",\n    \"C12-C13 display the highest alarm counts and significant temperature spikes coinciding with active occupancy, requiring immediate safety verification.\",\n    \"The transition from C14 to C16 shows reduced activity but persistent monitoring needs due to previous anomalies.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Sensor calibration drift or firmware bug causing offset values.\",\n      \"evidence\": [\"Temperature readings in C02-C03 (e.g., 2466) are consistently high but stable relative to each other across rooms during the early morning hours, suggesting a systematic error rather than random noise.\", \"In C12-C13, temperatures drop into realistic ranges (~22-26) as occupancy increases and appliances run, implying the sensor logic functions correctly when active.\"],\n      \"weaknesses\": [\"Does not explain why the 'realistic' range starts at ~2174 instead of ~20-25. An offset of +2000 is too large for a simple linear calibration error without affecting the lower-range data.\", \"Fails to account for the complete absence of temperature data points in C02/C03 between 06:38 and 07:00 where lights and windows were actively manipulated.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Critical Sensor Failure/Calibration Catastrophe leading to false environmental alarms.\",\n      \"threat_type\": \"Environmental Safety Hazard (False Positive)\",\n      \"evidence\": [\"C02 & C03 show persistent values >2200 (e.g., 2495) while actual ambient temps should be <30°C. This indicates a severe scaling error or unit mismatch (e.g., reading milliKelvin or raw ADC counts).\", \"Data gaps exist in C02/C03 specific"}}
{"episode_id": "SQ4_FP_D_0851", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq4\\SQ4_FP_D_0851.json", "metadata": {"sq_type": "SQ4", "sq_name": "复合安全推理", "variant": "FP", "layout_id": "D", "layout_name": "独居老人 (Elderly Living Alone)", "profile_id": "elderly_living_alone", "base_date": "2026-06-03T00:00:00", "seed": 20261480, "scenario_id": "EL-02", "total_events": 1853, "anomaly_events_count": 4}, "ground_truth": {"scenario_id": "EL-02-FP", "scenario_name": "EL-02-FP: 正常午睡", "category": "elderly_specific", "is_anomaly": false, "threat_type": "none", "key_difference": "发生在正常午睡时段（12:30-14:00），最后活动在卧室且灯已关/窗帘已关", "difficulty_score": 12, "difficulty_level": 3, "difficulty_label": "L3_composite_reasoning", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 3, "D3_cross_device": 2, "D4_temporal_span": 3, "D5_fp_similarity": 2}, "target_room": "kitchen", "injection_time": "2026-06-03T08:48:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"fire_risk\",\n  \"threat_description\": \"The household faces a critical fire risk due to unattended cooking followed by sensor failure and sustained high temperatures, indicating a potential equipment malfunction or ventilation issue in the kitchen.\",\n  \"reasoning\": [\n    \"At 06:06:32, the kitchen cook surface was activated, and immediately at 06:07:02 (within 30 seconds), the temperature sensor reported 'None', suggesting the heat caused the sensor to fail or disconnect.\",\n    \"Despite the cook surface being turned off at 06:26:00, kitchen temperatures remained critically high (>2500) for hours without significant cooling, indicating either the stove failed to cool down properly, ventilation is blocked, or the appliance itself is malfunctioning as a heat source.\",\n    \"While occupancy logs show the resident returning frequently, the combination of immediate sensor loss upon heating activation and prolonged extreme temperatures creates a severe fire hazard scenario that cannot be ruled out as normal operation.\"\n  ],\n  \"key_evidence\": [\n    \"Timestamp sequence: 'kitchen_cook_surface | OnOff.OnOff = True' at 06:06:32 followed immediately by 'kitchen_temp_sensor | ... = None' at 06:07:02.\",\n    \"Temperature readings in the kitchen peaked above 2550 and remained elevated even after the cook surface was deactivated at 06:26:00.\",\n    \"Continuous data loss from the kitchen temperature sensor during peak activity periods while other room sensors functioned normally.\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately inspect the kitchen for signs of smoke, soot, or overheating components on the cook surface.\",\n    \"Replace the kitchen temperature sensor and verify its calibration before resuming cooking activities.\",\n    \"Test the HVAC system and ensure kitchen ventilation fans are operational to prevent future heat buildup.\",\n    \"Review security camera footage if available to confirm whether the resident left the kitchen unattended during the initial heating phase.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "fire_risk", "threat_description": "The household faces a critical fire risk due to unattended cooking followed by sensor failure and sustained high temperatures, indicating a potential equipment malfunction or ventilation issue in the kitchen.", "reasoning": ["At 06:06:32, the kitchen cook surface was activated, and immediately at 06:07:02 (within 30 seconds), the temperature sensor reported 'None', suggesting the heat caused the sensor to fail or disconnect.", "Despite the cook surface being turned off at 06:26:00, kitchen temperatures remained critically high (>2500) for hours without significant cooling, indicating either the stove failed to cool down properly, ventilation is blocked, or the appliance itself is malfunctioning as a heat source.", "While occupancy logs show the resident returning frequently, the combination of immediate sensor loss upon heating activation and prolonged extreme temperatures creates a severe fire hazard scenario that cannot be ruled out as normal operation."], "key_evidence": ["Timestamp sequence: 'kitchen_cook_surface | OnOff.OnOff = True' at 06:06:32 followed immediately by 'kitchen_temp_sensor | ... = None' at 06:07:02.", "Temperature readings in the kitchen peaked above 2550 and remained elevated even after the cook surface was deactivated at 06:26:00.", "Continuous data loss from the kitchen temperature sensor during peak activity periods while other room sensors functioned normally."], "recommended_actions": ["Immediately inspect the kitchen for signs of smoke, soot, or overheating components on the cook surface.", "Replace the kitchen temperature sensor and verify its calibration before resuming cooking activities.", "Test the HVAC system and ensure kitchen ventilation fans are operational to prevent future heat buildup.", "Review security camera footage if available to confirm whether the resident left the kitchen unattended during the initial heating phase."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 68.71266412734985, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1853, "chunk_count": 24, "signals": {"room_activity": {"living_room": 496, "bedroom": 533, "kitchen": 532, "bathroom": 61, "entrance": 231}, "attribute_frequency": {"Occupancy": 943, "MeasuredValue": 870, "OnOff": 22, "CurrentPositionLiftPercent100ths": 5, "LockState": 4, "StateValue": 4, "CurrentLevel": 1}, "lock_state_flips": 4, "occupancy_events": 943, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\", \"bedroom\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"kitchen_occupancy\", \"kitchen_cook_surface\", \"living_room_temp_sensor\", \"bedroom_temp_sensor\", \"bathroom_occupancy\"],\n  \"focus_chunk_ids\": [\"C03\", \"C04\", \"C05\", \"C06\", \"C07\", \"C19\"],\n  \"suspected_patterns\": [\n    \"sustained_high_temperature\",\n    \"cooking_without_monitoring\",\n    \"sensor_data_loss\",\n    \"late_night_activity\"\n  ],\n  \"why_these_chunks\": [\n    \"C03-C07 show a continuous upward trend in room temperatures (2400+ values) despite occupancy, suggesting potential heating issues or lack of ventilation.\",\n    \"C04 contains the critical event 'kitchen_cook_surface | OnOff.OnOff = False' immediately after occupancy spikes and high temps, indicating unattended cooking which is a major fire risk for an elderly person living alone.\",\n    \"C04 also shows 'kitchen_temp_sensor | ... = None', indicating sensor failure or disconnection during a high-risk period.\",\n    \"C19 shows activity at 20:15 with temperatures still elevated but starting to drop, requiring verification if the kitchen was left on or if the AC worked correctly.\",\n    \"The pattern of high alarm counts in these chunks combined with temperature anomalies suggests a composite safety issue involving environmental conditions and human behavior.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "living_room", "bedroom"], "focus_devices": ["kitchen_temp_sensor", "kitchen_occupancy", "kitchen_cook_surface", "living_room_temp_sensor", "bedroom_temp_sensor", "bathroom_occupancy"], "focus_chunk_ids": ["C03", "C04", "C05", "C06", "C07", "C19"], "suspected_patterns": ["sustained_high_temperature", "cooking_without_monitoring", "sensor_data_loss", "late_night_activity"], "why_these_chunks": ["C03-C07 show a continuous upward trend in room temperatures (2400+ values) despite occupancy, suggesting potential heating issues or lack of ventilation.", "C04 contains the critical event 'kitchen_cook_surface | OnOff.OnOff = False' immediately after occupancy spikes and high temps, indicating unattended cooking which is a major fire risk for an elderly person living alone.", "C04 also shows 'kitchen_temp_sensor | ... = None', indicating sensor failure or disconnection during a high-risk period.", "C19 shows activity at 20:15 with temperatures still elevated but starting to drop, requiring verification if the kitchen was left on or if the AC worked correctly.", "The pattern of high alarm counts in these chunks combined with temperature anomalies suggests a composite safety issue involving environmental conditions and human behavior."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"High ambient temperature due to external weather conditions (e.g., heatwave) combined with closed windows/doors.\",\n      \"evidence\": [\"Bedroom temperatures are consistently high (23xx-24xx range) but lower than the kitchen, suggesting insulation or different exposure.\", \"Multiple lock/unlock events and frequent entrance occupancy indicate active residents moving through the home throughout the day.\", \"Temperature fluctuations in the living room (2500-2550) show some variability rather than a flat line, which might suggest HVAC cycling or window opening attempts.\"],\n      \"weaknesses\": [\"Kitchen temperatures remain extremely high (>2500) even when no cooking is actively detected in logs after the initial event.\", \"The magnitude of the temperature difference between rooms (~100-200 units) exceeds typical thermal gradients for standard residential construction.\", \"No 'MeasuredValue' data points from the kitchen sensor during peak activity periods suggests a hardware failure rather than just environmental heat.\"]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"Sensor malfunction causing data drift and loss of calibration.\",\n      \"evidence\": [\"Kitchen temperature sensor reports 'None' values at specific timestamps while other sensors continue reporting valid numbers.\", \"Temperature readings jump significantly (e.g., from 2488 to 2505) without corresponding changes in occupancy or device state.\", \"The pattern of missing data correlates with periods of high activity, potentially indicating power instability or connection drops.\"],\n      \"weaknesses\": [\"This hypothesis fails to explain why only the kitchen sensor loses data or why its readings are so disproportionately higher than the bedroom/living room if it were simply drifting.\", \"It does not account for the specific behavioral anomaly of turning on the cook surface immediately before the sensor disconnects.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Unattended cooking leading to potential fire hazard and subsequent sensor failure.\",\n      \"threat_type\": \"Fire Safety / Equipment Failure\",\n      \"evidence\": [\"At 06:06:32, 'kitchen_cook_surface | OnOff.OnOff = True'.\", \"Immediately following this, at 06:07:02, 'kitchen_temp_sensor | ... = None', indicating the sensor was overwhelmed or disconnected by heat/smoke.\", \"At 06:26:00, 'kitchen_cook_surface | OnOff.OnOff = False', showing the device was turned off, but temperatures remained critically high (2488 -> 2479 drop is minimal compared to expected cooling).\", \"Continuous high temperature readings in the kitchen (peaking >2550) despite occupancy patterns that do not support constant active cooking.\", \"Residents frequently leave the kitchen area ('kitchen_occupancy' drops to 0 multiple times) while temperatures remain extreme.\"],\n      \"weaknesses\": [\"There is no explicit 'fire' alarm event logged in the provided chunks.\", \"The occupant returns to the kitchen frequently; one cannot confirm they left unattended for a critical duration based solely on these logs.\"]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Critical HVAC/Furnace failure resulting in lethal indoor environment.\",\n      \"threat_type\": \"Environmental Hazard / Life Safety\",\n      \"evidence\": [\"All room temperatures are abnormally high for June (assuming standard climate), especially the kitchen reaching >2550 units.\", \"Despite occupants being present in bedrooms and living rooms, temperatures do not stabilize or decrease.\", \"The disparity between bedroom (~2400) and kitchen (>2500) suggests a localized heating source (likely the stove) failing to dissipate heat due to lack of ventilation or systemic AC failure.\", \"Repeated sensor errors ('None') in the kitchen suggest the environment exceeded the sensor's operational limits.\"],\n      \"weaknesses\": [\"Cannot definitively distinguish between a single point failure (stove + no vent) vs. total system failure without historical baseline data.\"],\n      \"weaknesses\": [\"Cannot definitively distinguish between a single point failure (stove + no vent) vs. total system failure without historical baseline data.\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"Timestamp correlation: 'kitchen_cook_surface' turned ON at 06:06:32 followed immediately by sensor data loss ('None') at 06:07:02, strongly implying the heat caused the sensor failure.\",\n    \"Behavioral mismatch: High kitchen temperatures persist long after the cook surface was turned OFF at 06:26:00, indicating poor ventilation or an inability to cool down.\",\n    \"Data integrity gap: The sudden switch from valid high readings to 'None' specifically in the kitchen, while other room sensors function normally, isolates the issue to the kitchen environment rather than a network-wide outage.\"\n  ],\n  \"missing_information\": [\n    \"Historical baseline temperature data to confirm if current levels are anomalous relative to normal weather conditions.\",\n    \"Logs for smoke detectors or carbon monoxide alarms to see if safety protocols were triggered.\",\n    \"HVAC system status logs (thermostat settings, fan speed, error codes) to determine if the cooling system is offline.\",\n    \"Duration analysis of how long the cook surface remained on versus how long the resident was in the kitchen to assess the 'unattended' risk factor.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "High ambient temperature due to external weather conditions (e.g., heatwave) combined with closed windows/doors.", "evidence": ["Bedroom temperatures are consistently high (23xx-24xx range) but lower than the kitchen, suggesting insulation or different exposure.", "Multiple lock/unlock events and frequent entrance occupancy indicate active residents moving through the home throughout the day.", "Temperature fluctuations in the living room (2500-2550) show some variability rather than a flat line, which might suggest HVAC cycling or window opening attempts."], "weaknesses": ["Kitchen temperatures remain extremely high (>2500) even when no cooking is actively detected in logs after the initial event.", "The magnitude of the temperature difference between rooms (~100-200 units) exceeds typical thermal gradients for standard residential construction.", "No 'MeasuredValue' data points from the kitchen sensor during peak activity periods suggests a hardware failure rather than just environmental heat."]}, {"id": "N2", "description": "Sensor malfunction causing data drift and loss of calibration.", "evidence": ["Kitchen temperature sensor reports 'None' values at specific timestamps while other sensors continue reporting valid numbers.", "Temperature readings jump significantly (e.g., from 2488 to 2505) without corresponding changes in occupancy or device state.", "The pattern of missing data correlates with periods of high activity, potentially indicating power instability or connection drops."], "weaknesses": ["This hypothesis fails to explain why only the kitchen sensor loses data or why its readings are so disproportionately higher than the bedroom/living room if it were simply drifting.", "It does not account for the specific behavioral anomaly of turning on the cook surface immediately before the sensor disconnects."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Unattended cooking leading to potential fire hazard and subsequent sensor failure.", "threat_type": "Fire Safety / Equipment Failure", "evidence": ["At 06:06:32, 'kitchen_cook_surface | OnOff.OnOff = True'.", "Immediately following this, at 06:07:02, 'kitchen_temp_sensor | ... = None', indicating the sensor was overwhelmed or disconnected by heat/smoke.", "At 06:26:00, 'kitchen_cook_surface | OnOff.OnOff = False', showing the device was turned off, but temperatures remained critically high (2488 -> 2479 drop is minimal compared to expected cooling).", "Continuous high temperature readings in the kitchen (peaking >2550) despite occupancy patterns that do not support constant active cooking.", "Residents frequently leave the kitchen area ('kitchen_occupancy' drops to 0 multiple times) while temperatures remain extreme."], "weaknesses": ["There is no explicit 'fire' alarm event logged in the provided chunks.", "The occupant returns to the kitchen frequently; one cannot confirm they left unattended for a critical duration based solely on these logs."]}, {"id": "A2", "description": "Critical HVAC/Furnace failure resulting in lethal indoor environment.", "threat_type": "Environmental Hazard / Life Safety", "evidence": ["All room temperatures are abnormally high for June (assuming standard climate), especially the kitchen reaching >2550 units.", "Despite occupants being present in bedrooms and living rooms, temperatures do not stabilize or decrease.", "The disparity between bedroom (~2400) and kitchen (>2500) suggests a localized heating source (likely the stove) failing to dissipate heat due to lack of ventilation or systemic AC failure.", "Repeated sensor errors ('None') in the kitchen suggest the environment exceeded the sensor's operational limits."], "weaknesses": ["Cannot definitively distinguish between a single point failure (stove + no vent) vs. total system failure without historical baseline data."]}], "most_discriminative_evidence": ["Timestamp correlation: 'kitchen_cook_surface' turned ON at 06:06:32 followed immediately by sensor data loss ('None') at 06:07:02, strongly implying the heat caused the sensor failure.", "Behavioral mismatch: High kitchen temperatures persist long after the cook surface was turned OFF at 06:26:00, indicating poor ventilation or an inability to cool down.", "Data integrity gap: The sudden switch from valid high readings to 'None' specifically in the kitchen, while other room sensors function normally, isolates the issue to the kitchen environment rather than a network-wide outage."], "missing_information": ["Historical baseline temperature data to confirm if current levels are anomalous relative to normal weather conditions.", "Logs for smoke detectors or carbon monoxide alarms to see if safety protocols were triggered.", "HVAC system status logs (thermostat settings, fan speed, error codes) to determine if the cooling system is offline.", "Duration analysis of how long the cook surface remained on versus how long the resident was in the kitchen to assess the 'unattended' risk factor."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C08\", \"C19\"],\n  \"missing_checks\": [\n    \"Verify HVAC/Thermostat status logs to rule out system-wide cooling failure.\",\n    \"Check for smoke or CO alarm triggers during the high-temperature window.\",\n    \"Analyze occupancy duration vs. cook surface active time in C04 to confirm unattended cooking.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identifies potential fire hazards and sensor failures based on C03-C07.\",\n    \"However, evidence regarding late-night activity (suggested by Triage) is incomplete; C19 was selected but needs inclusion to verify if temperatures remained elevated after typical waking hours.\",\n    \"C08 should be reviewed to see if it bridges the gap between the initial incident and later events, potentially revealing sustained heat or recovery patterns.\",\n    \"Current hypotheses do not fully account for a systemic HVAC failure; checking thermostat logs (likely in adjacent chunks) is critical before concluding it's solely a stove issue.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C08", "C19"], "missing_checks": ["Verify HVAC/Thermostat status logs to rule out system-wide cooling failure.", "Check for smoke or CO alarm triggers during the high-temperature window.", "Analyze occupancy duration vs. cook surface active time in C04 to confirm unattended cooking."], "supervisor_notes": ["The analysis correctly identifies potential fire hazards and sensor failures based on C03-C07.", "However, evidence regarding late-night activity (suggested by Triage) is incomplete; C19 was selected but needs inclusion to verify if temperatures remained elevated after typical waking hours.", "C08 should be reviewed to see if it bridges the gap between the initial incident and later events, potentially revealing sustained heat or recovery patterns.", "Current hypotheses do not fully account for a systemic HVAC failure; checking thermostat logs (likely in adjacent chunks) is critical before concluding it's solely a stove issue."]}, "preview_triage_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Layout\nLayout: 独居老人 (Elderly Living Alone)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>, 床头灯<onoff_light>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房运动传感器<occupancy_sensor>\n- living_room: 客厅温度传感器<temperature_sensor>, 客厅灯<dimmable_light>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 496,\n    \"bedroom\": 533,\n    \"kitchen\": 532,\n    \"bathroom\": 61,\n    \"entrance\": 231\n  },\n  \"attribute_frequency\": {\n    \"Occupancy\": 943,\n    \"MeasuredValue\": 870,\n    \"OnOff\": 22,\n    \"CurrentPositionLiftPercent100ths\": 5,\n    \"LockState\": 4,\n    \"StateValue\": 4,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 943,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-03T00:00:00\",\n    \"end_ts\": \"2026-06-03T01:35:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 24,\n      \"bedroom\": 24,\n      \"kitchen\": 24,\n      \"bathroom\": 4,\n      \"entrance\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"kitchen_occupancy\"\n    ],\n    \"alarmish_count\": 20,\n    \"preview_lines\": [\n      \"[2026-06-03T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2276\",\n      \"[2026-06-03T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2170\",\n      \"[2026-06-03T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2276\",\n      \"[2026-06-03T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-03T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-03T00:00:00] kitchen_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-03T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-03T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-03T00:05:00] li", "preview_verifier_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\", \"bedroom\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"kitchen_occupancy\", \"kitchen_cook_surface\", \"living_room_temp_sensor\", \"bedroom_temp_sensor\", \"bathroom_occupancy\"],\n  \"focus_chunk_ids\": [\"C03\", \"C04\", \"C05\", \"C06\", \"C07\", \"C19\"],\n  \"suspected_patterns\": [\n    \"sustained_high_temperature\",\n    \"cooking_without_monitoring\",\n    \"sensor_data_loss\",\n    \"late_night_activity\"\n  ],\n  \"why_these_chunks\": [\n    \"C03-C07 show a continuous upward trend in room temperatures (2400+ values) despite occupancy, suggesting potential heating issues or lack of ventilation.\",\n    \"C04 contains the critical event 'kitchen_cook_surface | OnOff.OnOff = False' immediately after occupancy spikes and high temps, indicating unattended cooking which is a major fire risk for an elderly person living alone.\",\n    \"C04 also shows 'kitchen_temp_sensor | ... = None', indicating sensor failure or disconnection during a high-risk period.\",\n    \"C19 shows activity at 20:15 with temperatures still elevated but starting to drop, requiring verification if the kitchen was left on or if the AC worked correctly.\",\n    \"The pattern of high alarm counts in these chunks combined with temperature anomalies suggests a composite safety issue involving environmental conditions and human behavior.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"High ambient temperature due to external weather conditions (e.g., heatwave) combined with closed windows/doors.\",\n      \"evidence\": [\"Bedroom temperatures are consistently high (23xx-24xx range) but lower than the kitchen, suggesting insulation or different exposure.\", \"Multiple lock/unlock events and frequent entrance occupancy indicate active residents moving through the home throughout the day.\", \"Temperature fluctuations in the living room (2500-2550) show some variability rather than a flat line, which might suggest HVAC cycling or window opening attempts.\"],\n      \"weaknesses\": [\"Kitchen temperatures remain extremely high (>2500) even when no cooking is actively detected in logs after the initial event.\", \"The magnitude of the temperature difference between rooms (~100-200 units) exceeds typical thermal gradients for standard residential construction.\", \"No 'MeasuredValue' data points from the kitchen sensor during peak activity periods suggests "}}
{"episode_id": "SQ4_TN_A_0961", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq4\\SQ4_TN_A_0961.json", "metadata": {"sq_type": "SQ4", "sq_name": "复合安全推理", "variant": "TN", "layout_id": "A", "layout_name": "一室一厅 (Studio/1BR)", "profile_id": "young_professional", "base_date": "2026-06-09T00:00:00", "seed": 20261590, "scenario_id": null, "total_events": 1118, "anomaly_events_count": 0}, "ground_truth": {"scenario_id": "TN", "scenario_name": "Normal — no anomaly", "category": "none", "is_anomaly": false, "threat_type": "none", "variant": "TN", "difficulty_score": 0, "difficulty_level": 0, "difficulty_label": "TN_baseline", "difficulty_dimensions": {"D1_evidence_count": 0, "D2_signal_directness": 0, "D3_cross_device": 0, "D4_temporal_span": 0, "D5_fp_similarity": 0}}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"Systematic sensor failure reporting temperatures in Kelvin (approx. 2000-2500) instead of Celsius across all zones and times, causing false alarm triggers and data invalidity.\",\n  \"reasoning\": [\n      \"Temperature readings consistently range between 2100 and 2700 across all rooms from midnight to evening; converting these values by subtracting 273.15 yields realistic room temperatures (approx. 18°C to 24°C), indicating a unit conversion error rather than actual overheating or fire risk.\",\n      \"The anomalous temperature pattern is present in early morning chunks (C00-C03) before any cooking activity begins, proving the readings are not caused by appliance usage but by a systemic calibration fault or software configuration error.\",\n      \"While Chunk C10 shows a sequence of door lock state change followed by contact opening and occupancy detection consistent with an entry event, the ambiguity of the 'LockState=2' code prevents confirming unauthorized access without external logs; however, the overwhelming evidence points to the primary anomaly being the sensor malfunction which corrupts safety logic.\"\n    ],\n  \"key_evidence\": [\n      \"All three sensors (living_room, bedroom, kitchen) report values >2000 simultaneously for over 12 hours.\",\n      \"Kitchen temperature drops significantly when cooking stops (e.g., from 2719 to 2663 in C10), demonstrating relative consistency typical of a scaling error rather than erratic hardware failure.\"\n    ],\n  \"recommended_actions\": [\n      \"Immediately verify and correct the temperature sensor unit configuration (ensure output is Celsius, not Kelvin).\",\n      \"Review historical logs prior to 2026-06-09T00:00:00 to confirm if this is a persistent baseline issue or a sudden drift/firmware bug.\",\n      \"Investigate the specific 'LockState' integer codes to definitively classify the entry event in Chunk C10 as authorized or unauthorized.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "Systematic sensor failure reporting temperatures in Kelvin (approx. 2000-2500) instead of Celsius across all zones and times, causing false alarm triggers and data invalidity.", "reasoning": ["Temperature readings consistently range between 2100 and 2700 across all rooms from midnight to evening; converting these values by subtracting 273.15 yields realistic room temperatures (approx. 18°C to 24°C), indicating a unit conversion error rather than actual overheating or fire risk.", "The anomalous temperature pattern is present in early morning chunks (C00-C03) before any cooking activity begins, proving the readings are not caused by appliance usage but by a systemic calibration fault or software configuration error.", "While Chunk C10 shows a sequence of door lock state change followed by contact opening and occupancy detection consistent with an entry event, the ambiguity of the 'LockState=2' code prevents confirming unauthorized access without external logs; however, the overwhelming evidence points to the primary anomaly being the sensor malfunction which corrupts safety logic."], "key_evidence": ["All three sensors (living_room, bedroom, kitchen) report values >2000 simultaneously for over 12 hours.", "Kitchen temperature drops significantly when cooking stops (e.g., from 2719 to 2663 in C10), demonstrating relative consistency typical of a scaling error rather than erratic hardware failure."], "recommended_actions": ["Immediately verify and correct the temperature sensor unit configuration (ensure output is Celsius, not Kelvin).", "Review historical logs prior to 2026-06-09T00:00:00 to confirm if this is a persistent baseline issue or a sudden drift/firmware bug.", "Investigate the specific 'LockState' integer codes to definitively classify the entry event in Chunk C10 as authorized or unauthorized."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 66.82898569107056, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1118, "chunk_count": 14, "signals": {"room_activity": {"living_room": 396, "bedroom": 355, "kitchen": 298, "bathroom": 55, "entrance": 14}, "attribute_frequency": {"MeasuredValue": 866, "Occupancy": 216, "OnOff": 18, "StateValue": 5, "LockState": 4, "CurrentPositionLiftPercent100ths": 2, "SystemMode": 1, "OperationalState": 1, "CurrentLevel": 1}, "lock_state_flips": 4, "occupancy_events": 216, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\", \"entrance\"],\n  \"focus_devices\": [\"temperature_sensor\", \"front_door_lock\", \"front_door_contact\", \"occupancy_sensor\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C10\", \"C11\", \"C12\"],\n  \"suspected_patterns\": [\n    \"Temperature values are approximately 10x higher than normal room temperatures (e.g., 2552 vs ~25), suggesting a unit mismatch (Kelvin/Celsius scale error) or sensor malfunction rather than actual overheating.\",\n    \"High 'alarmish_count' in early chunks (C00-C03) coincides with the anomalous temperature readings, potentially triggering false alarms due to the data scaling issue.\",\n    \"Discrepancy between occupancy sensors reporting '0' and deterministic signals showing frequent 'Occupancy' attribute updates suggests potential sensor latency or logic errors during low-activity periods.\",\n    \"Entry events in C10 show a sequence of lock state change followed by contact opening/closing, which requires verification against the specific lock operation type to confirm unauthorized access vs. normal entry.\"\n  ],\n  \"why_these_chunks\": [\n    \"C00-C03: Contain the initial burst of high 'alarmish_count' values alongside the first appearance of the anomalously scaled temperature readings (2000+).\",\n    \"C10: Shows critical security event sequences (lock/unlock/contact) at night when occupancy is expected to be low, requiring safety context.\",\n    \"C11-C12: High alarm counts persist into the evening; must be correlated with occupancy patterns to determine if alarms are genuine threats or artifacts of the suspected sensor/unit errors.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "living_room", "entrance"], "focus_devices": ["temperature_sensor", "front_door_lock", "front_door_contact", "occupancy_sensor"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C10", "C11", "C12"], "suspected_patterns": ["Temperature values are approximately 10x higher than normal room temperatures (e.g., 2552 vs ~25), suggesting a unit mismatch (Kelvin/Celsius scale error) or sensor malfunction rather than actual overheating.", "High 'alarmish_count' in early chunks (C00-C03) coincides with the anomalous temperature readings, potentially triggering false alarms due to the data scaling issue.", "Discrepancy between occupancy sensors reporting '0' and deterministic signals showing frequent 'Occupancy' attribute updates suggests potential sensor latency or logic errors during low-activity periods.", "Entry events in C10 show a sequence of lock state change followed by contact opening/closing, which requires verification against the specific lock operation type to confirm unauthorized access vs. normal entry."], "why_these_chunks": ["C00-C03: Contain the initial burst of high 'alarmish_count' values alongside the first appearance of the anomalously scaled temperature readings (2000+).", "C10: Shows critical security event sequences (lock/unlock/contact) at night when occupancy is expected to be low, requiring safety context.", "C11-C12: High alarm counts persist into the evening; must be correlated with occupancy patterns to determine if alarms are genuine threats or artifacts of the suspected sensor/unit errors."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The system is experiencing a widespread sensor calibration failure or unit conversion error, reporting temperatures in Kelvin (approx. -273°C offset) instead of Celsius.\",\n      \"evidence\": [\"All temperature sensors report values between 2100 and 2500 consistently across different rooms and times.\", \"The values fluctuate slightly (e.g., 2268 to 2394) consistent with minor thermal drift but lack the magnitude expected for actual overheating.\", \"In C10, kitchen values drop from ~2719 to ~2283 as cooking stops, showing relative consistency despite absolute absurdity.\"],\n      \"weaknesses\": [\"Does not explain the 'alarmish_count' spikes mentioned in triage output if alarms are triggered by absolute thresholds.\", \"Fails to account for potential hardware melting if the reading were real.\"]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"Household activity follows a standard daily routine: residents wake up in the morning (C03), prepare food in the evening (C10), and secure the home at night.\",\n      \"evidence\": [\"C03 shows occupancy events in bedroom/bathroom at 06:23-07:00 coinciding with lights turning on.\", \"C10 shows front door lock state change, entry light activation, and subsequent kitchen usage (cooking surface on/off).\"],\n      \"weaknesses\": [\"Ignores the massive temperature anomaly which could be a security risk indicator (e.g., fire suppression failure masked by bad data).\" ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Sensor malfunction causing false alarm cascades; the 'alarmish_count' spikes are artifacts of the temperature scale error triggering threshold violations.\",\n      \"threat_type\": \"System Reliability / False Positive Security Alert\",\n      \"evidence\": [\"Triage notes 'alarmish_count' in C00-C03 coincide with 2000+ temp readings.\", \"Living room occupancy is 0 for hours in C00-C02 while temps hover near 2300-2400, likely triggering high-temp alarms unnecessarily.\", \"No actual heat signature correlates with the data; the pattern is static noise around an impossible baseline.\"],\n      \"weaknesses\": [\"If the alarm logic relies on rate-of-change rather than absolute value, this might not trigger alarms, contradicting the triage suspicion.\"]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Potential unauthorized entry event during low-occupancy windows (C10 sequence), where lock manipulation occurred before resident arrival.\",\n      \"threat_type\": \"Physical Intrusion Attempt\",\n      \"evidence\": [\"C10 starts with LockState=2 at 18:28:00, followed immediately by DoorContact=False (open) at 18:28:02.\", \"Entry light activates 7 seconds later.\", \"Resident occupancy detection occurs 2 minutes after door contact opens.\", \"Sequence implies someone unlocked/opened the door, then entered, then turned on lights.\"],\n      \"weaknesses\": [\"Could be a legitimate resident leaving and re-entering, or testing the lock mechanism.\", \"The rapid succession (2 seconds) between lock change and door open suggests automated unlocking or very fast manual action, making it ambiguous without video.\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"Consistent reporting of temperatures >2000K across all zones indicates a systemic unit mismatch (Kelvin vs Celsius) rather than localized heating events.\",\n    \"Temporal gap in C10 between 'front_door_lock' state change (18:28:00) and 'living_room_occupancy' detection (18:28:21) with an intervening 'front_door_contact' open signal suggests a discrete entry event requiring verification.\",\n    \"Absence of any logical correlation between appliance operation (AC on in C10) and the reported temperature values, confirming the data is non-physical.\"\n  ],\n  \"missing_information\": [\n    \"Actual definition of the 'LockState' integer codes (e.g., does 2 mean 'unlocked' or 'armed'?)\",\n    \"Video footage or audio logs corresponding to the C10 timestamp range to verify who entered.\",\n    \"Historical temperature baseline for these specific sensors to confirm if this is a new calibration drift or a sudden hardware failure.\",\n    \"The specific threshold values used by the alarm system to generate the 'alarmish_count' to determine if they were triggered by the absolute temp value or the rate of change.\"]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The system is experiencing a widespread sensor calibration failure or unit conversion error, reporting temperatures in Kelvin (approx. -273°C offset) instead of Celsius.", "evidence": ["All temperature sensors report values between 2100 and 2500 consistently across different rooms and times.", "The values fluctuate slightly (e.g., 2268 to 2394) consistent with minor thermal drift but lack the magnitude expected for actual overheating.", "In C10, kitchen values drop from ~2719 to ~2283 as cooking stops, showing relative consistency despite absolute absurdity."], "weaknesses": ["Does not explain the 'alarmish_count' spikes mentioned in triage output if alarms are triggered by absolute thresholds.", "Fails to account for potential hardware melting if the reading were real."]}, {"id": "N2", "description": "Household activity follows a standard daily routine: residents wake up in the morning (C03), prepare food in the evening (C10), and secure the home at night.", "evidence": ["C03 shows occupancy events in bedroom/bathroom at 06:23-07:00 coinciding with lights turning on.", "C10 shows front door lock state change, entry light activation, and subsequent kitchen usage (cooking surface on/off)."], "weaknesses": ["Ignores the massive temperature anomaly which could be a security risk indicator (e.g., fire suppression failure masked by bad data)."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Sensor malfunction causing false alarm cascades; the 'alarmish_count' spikes are artifacts of the temperature scale error triggering threshold violations.", "threat_type": "System Reliability / False Positive Security Alert", "evidence": ["Triage notes 'alarmish_count' in C00-C03 coincide with 2000+ temp readings.", "Living room occupancy is 0 for hours in C00-C02 while temps hover near 2300-2400, likely triggering high-temp alarms unnecessarily.", "No actual heat signature correlates with the data; the pattern is static noise around an impossible baseline."], "weaknesses": ["If the alarm logic relies on rate-of-change rather than absolute value, this might not trigger alarms, contradicting the triage suspicion."]}, {"id": "A2", "description": "Potential unauthorized entry event during low-occupancy windows (C10 sequence), where lock manipulation occurred before resident arrival.", "threat_type": "Physical Intrusion Attempt", "evidence": ["C10 starts with LockState=2 at 18:28:00, followed immediately by DoorContact=False (open) at 18:28:02.", "Entry light activates 7 seconds later.", "Resident occupancy detection occurs 2 minutes after door contact opens.", "Sequence implies someone unlocked/opened the door, then entered, then turned on lights."], "weaknesses": ["Could be a legitimate resident leaving and re-entering, or testing the lock mechanism.", "The rapid succession (2 seconds) between lock change and door open suggests automated unlocking or very fast manual action, making it ambiguous without video."]}], "most_discriminative_evidence": ["Consistent reporting of temperatures >2000K across all zones indicates a systemic unit mismatch (Kelvin vs Celsius) rather than localized heating events.", "Temporal gap in C10 between 'front_door_lock' state change (18:28:00) and 'living_room_occupancy' detection (18:28:21) with an intervening 'front_door_contact' open signal suggests a discrete entry event requiring verification.", "Absence of any logical correlation between appliance operation (AC on in C10) and the reported temperature values, confirming the data is non-physical."], "missing_information": ["Actual definition of the 'LockState' integer codes (e.g., does 2 mean 'unlocked' or 'armed'?)", "Video footage or audio logs corresponding to the C10 timestamp range to verify who entered.", "Historical temperature baseline for these specific sensors to confirm if this is a new calibration drift or a sudden hardware failure.", "The specific threshold values used by the alarm system to generate the 'alarmish_count' to determine if they were triggered by the absolute temp value or the rate of change."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C04\", \"C13\"],\n  \"missing_checks\": [\n    \"Verify LockState code definitions to determine if the C10 event was unauthorized or a resident action.\",\n    \"Check C04 and C13 for historical temperature baselines to confirm if the >2000 readings are new anomalies or consistent behavior.\",\n    \"Correlate 'alarmish_count' spikes in C11-C12 with occupancy data to rule out false positives from the temperature error.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identified the likely unit mismatch (Kelvin vs Celsius) but lacks temporal context. Chunk C04 is needed to see if the anomalous temperatures started suddenly or were always present; this distinguishes a one-time failure from a chronic calibration issue.\",\n    \"Chunk C13 (evening/night) is required to assess the persistence of the alarm issues seen in C11-C12 and verify if any other security events occurred during low-occupancy windows.\",\n    \"The hypothesis regarding unauthorized entry in C10 relies heavily on ambiguous integer codes. Without the definition of 'LockState=2', the safety assessment cannot definitively classify this as a threat vs. normal activity.\",\n    \"The investigation has not yet ruled out that the 'alarmish_count' in later chunks (C11-C12) might be genuine threats rather than artifacts, necessitating a review of occupancy patterns in C13.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C04", "C13"], "missing_checks": ["Verify LockState code definitions to determine if the C10 event was unauthorized or a resident action.", "Check C04 and C13 for historical temperature baselines to confirm if the >2000 readings are new anomalies or consistent behavior.", "Correlate 'alarmish_count' spikes in C11-C12 with occupancy data to rule out false positives from the temperature error."], "supervisor_notes": ["The analysis correctly identified the likely unit mismatch (Kelvin vs Celsius) but lacks temporal context. Chunk C04 is needed to see if the anomalous temperatures started suddenly or were always present; this distinguishes a one-time failure from a chronic calibration issue.", "Chunk C13 (evening/night) is required to assess the persistence of the alarm issues seen in C11-C12 and verify if any other security events occurred during low-occupancy windows.", "The hypothesis regarding unauthorized entry in C10 relies heavily on ambiguous integer codes. Without the definition of 'LockState=2', the safety assessment cannot definitively classify this as a threat vs. normal activity.", "The investigation has not yet ruled out that the 'alarmish_count' in later chunks (C11-C12) might be genuine threats rather than artifacts, necessitating a review of occupancy patterns in C13."]}, "preview_triage_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Layout\nLayout: 一室一厅 (Studio/1BR)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅台灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 396,\n    \"bedroom\": 355,\n    \"kitchen\": 298,\n    \"bathroom\": 55,\n    \"entrance\": 14\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 866,\n    \"Occupancy\": 216,\n    \"OnOff\": 18,\n    \"StateValue\": 5,\n    \"LockState\": 4,\n    \"CurrentPositionLiftPercent100ths\": 2,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 216,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-09T00:00:00\",\n    \"end_ts\": \"2026-06-09T01:50:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 27,\n      \"bedroom\": 27,\n      \"kitchen\": 22,\n      \"bathroom\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"bathroom_occupancy\"\n    ],\n    \"alarmish_count\": 12,\n    \"preview_lines\": [\n      \"[2026-06-09T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2272\",\n      \"[2026-06-09T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2163\",\n      \"[2026-06-09T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2270\",\n      \"[2026-06-09T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-09T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-09T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-09T00:05:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2268\",\n      \"[2026-06-09T00:05:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2164\",\n      \"[2026-06-09T00:05:00] kitchen_temp_sens", "preview_verifier_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\", \"entrance\"],\n  \"focus_devices\": [\"temperature_sensor\", \"front_door_lock\", \"front_door_contact\", \"occupancy_sensor\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C10\", \"C11\", \"C12\"],\n  \"suspected_patterns\": [\n    \"Temperature values are approximately 10x higher than normal room temperatures (e.g., 2552 vs ~25), suggesting a unit mismatch (Kelvin/Celsius scale error) or sensor malfunction rather than actual overheating.\",\n    \"High 'alarmish_count' in early chunks (C00-C03) coincides with the anomalous temperature readings, potentially triggering false alarms due to the data scaling issue.\",\n    \"Discrepancy between occupancy sensors reporting '0' and deterministic signals showing frequent 'Occupancy' attribute updates suggests potential sensor latency or logic errors during low-activity periods.\",\n    \"Entry events in C10 show a sequence of lock state change followed by contact opening/closing, which requires verification against the specific lock operation type to confirm unauthorized access vs. normal entry.\"\n  ],\n  \"why_these_chunks\": [\n    \"C00-C03: Contain the initial burst of high 'alarmish_count' values alongside the first appearance of the anomalously scaled temperature readings (2000+).\",\n    \"C10: Shows critical security event sequences (lock/unlock/contact) at night when occupancy is expected to be low, requiring safety context.\",\n    \"C11-C12: High alarm counts persist into the evening; must be correlated with occupancy patterns to determine if alarms are genuine threats or artifacts of the suspected sensor/unit errors.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The system is experiencing a widespread sensor calibration failure or unit conversion error, reporting temperatures in Kelvin (approx. -273°C offset) instead of Celsius.\",\n      \"evidence\": [\"All temperature sensors report values between 2100 and 2500 consistently across different rooms and times.\", \"The values fluctuate slightly (e.g., 2268 to 2394) consistent with minor thermal drift but lack the magnitude expected for actual overheating.\", \"In C10, kitchen values drop from ~2719 to ~2283 as cooking stops, showing relative consistency despite absolute absurdity.\"],\n      \"weaknesses\": [\"Does not explain the 'alarmish_count' spikes mentioned in triage output if alarms are"}}
{"episode_id": "SQ4_FP_C_0880", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq4\\SQ4_FP_C_0880.json", "metadata": {"sq_type": "SQ4", "sq_name": "复合安全推理", "variant": "FP", "layout_id": "C", "layout_name": "三室两厅 (3BR)", "profile_id": "family_with_children", "base_date": "2026-06-25T00:00:00", "seed": 20261509, "scenario_id": "CH-04", "total_events": 2297, "anomaly_events_count": 5}, "ground_truth": {"scenario_id": "CH-04-FP", "scenario_name": "CH-04-FP: 家长在玄关操作门锁", "category": "child_specific", "is_anomaly": false, "threat_type": "none", "key_difference": "成人成功解锁（UserIndex=1，无LockOperationError），不是儿童输错密码", "difficulty_score": 9, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "second_bathroom", "injection_time": "2026-06-25T19:39:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_drift\",\n  \"threat_description\": \"System-wide temperature sensors are reporting values approximately 10 times higher than expected (e.g., ~25°C reported as ~2530), indicating a severe calibration error or unit conversion failure that renders environmental monitoring unreliable.\",\n  \"reasoning\": [\n    \"Analysis of chunks C06-C07 shows consistent temperature readings in the 2500-2540 range across all rooms during morning hours, which is physically impossible for indoor air temperature and suggests a multiplication error (likely x10) rather than a thermal spike.\",\n    \"In contrast, chunk C18 (afternoon) reports temperatures around 2350-2390, and chunks C27-C28 (evening) report temperatures around 2250-2270. The relative consistency within each time block but the massive shift between blocks confirms a systematic reporting error rather than a transient hardware failure or actual environmental hazard.\",\n    \"The missing data points ('None') observed in C06 align with sensor communication issues often triggered by overflow errors or saturation when raw ADC values are misinterpreted as final measurements, further supporting the diagnosis of a software-level scaling or unit drift.\"\n  ],\n  \"key_evidence\": [\n    \"Morning readings (C06/C07): Living room temp jumped from baseline to 2503 at 07:15:00 immediately after cooking stopped, remaining elevated (~2530) while occupancy was active.\",\n    \"Evening readings (C27/C28): Temperatures reset to realistic-looking ranges of ~2250-2270 after auto-locking and window closure, establishing the 'true' baseline.\",\n    \"Simultaneity: All four temperature sensors (living_room, master_bedroom, kids_room, kitchen) exhibited the exact same erroneous magnitude and pattern simultaneously, ruling out individual sensor failure.\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately verify the device configuration for all temperature sensors to check for unit settings (Celsius vs Fahrenheit vs Raw Counts) and scaling factors.\",\n    \"Review system logs to identify if a firmware update or configuration change occurred around 07:10 AM on June 25th that could have introduced this multiplier error.\",\n    \"Temporarily disable automated HVAC controls dependent on these specific sensor readings to prevent potential overheating due to incorrect feedback loops until calibration is confirmed.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_drift", "threat_description": "System-wide temperature sensors are reporting values approximately 10 times higher than expected (e.g., ~25°C reported as ~2530), indicating a severe calibration error or unit conversion failure that renders environmental monitoring unreliable.", "reasoning": ["Analysis of chunks C06-C07 shows consistent temperature readings in the 2500-2540 range across all rooms during morning hours, which is physically impossible for indoor air temperature and suggests a multiplication error (likely x10) rather than a thermal spike.", "In contrast, chunk C18 (afternoon) reports temperatures around 2350-2390, and chunks C27-C28 (evening) report temperatures around 2250-2270. The relative consistency within each time block but the massive shift between blocks confirms a systematic reporting error rather than a transient hardware failure or actual environmental hazard.", "The missing data points ('None') observed in C06 align with sensor communication issues often triggered by overflow errors or saturation when raw ADC values are misinterpreted as final measurements, further supporting the diagnosis of a software-level scaling or unit drift."], "key_evidence": ["Morning readings (C06/C07): Living room temp jumped from baseline to 2503 at 07:15:00 immediately after cooking stopped, remaining elevated (~2530) while occupancy was active.", "Evening readings (C27/C28): Temperatures reset to realistic-looking ranges of ~2250-2270 after auto-locking and window closure, establishing the 'true' baseline.", "Simultaneity: All four temperature sensors (living_room, master_bedroom, kids_room, kitchen) exhibited the exact same erroneous magnitude and pattern simultaneously, ruling out individual sensor failure."], "recommended_actions": ["Immediately verify the device configuration for all temperature sensors to check for unit settings (Celsius vs Fahrenheit vs Raw Counts) and scaling factors.", "Review system logs to identify if a firmware update or configuration change occurred around 07:10 AM on June 25th that could have introduced this multiplier error.", "Temporarily disable automated HVAC controls dependent on these specific sensor readings to prevent potential overheating due to incorrect feedback loops until calibration is confirmed."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 73.37469172477722, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 2297, "chunk_count": 29, "signals": {"room_activity": {"living_room": 398, "master_bedroom": 517, "kids_room": 519, "kitchen": 303, "dining_room": 219, "second_bedroom": 48, "master_bathroom": 56, "entrance": 236, "second_bathroom": 1}, "attribute_frequency": {"MeasuredValue": 1156, "Occupancy": 1089, "OnOff": 26, "StateValue": 9, "LockState": 5, "CurrentPositionLiftPercent100ths": 3, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 5, "occupancy_events": 1089, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"entrance\", \"master_bedroom\"],\n  \"focus_devices\": [\"kitchen_cook_surface\", \"front_door_lock\", \"front_door_contact\", \"water_leak_detector\", \"temperature_sensor\"],\n  \"focus_chunk_ids\": [\"C06\", \"C18\", \"C27\"],\n  \"suspected_patterns\": [\n    \"High temperature readings across all rooms potentially indicating HVAC failure or sensor calibration drift.\",\n    \"Discrepancy between occupancy events and room activity counts suggests potential false positives or delayed signal propagation.\",\n    \"Sequence of door lock/unlock events occurring during occupied periods requires verification to rule out unauthorized access or system glitches.\"\n  ],\n  \"why_these_chunks\": [\n    \"C06: Contains critical operational state changes (cook surface on, lights off) and a missing temperature reading, which is a primary indicator for safety anomalies.\",\n    \"C18: Records specific manual lock operations followed immediately by contact state changes while occupants are present in other rooms, raising security questions.\",\n    \"C27: Captures the end-of-day transition sequence involving auto-locking and window closure, crucial for validating the home's 'away' mode activation logic.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "entrance", "master_bedroom"], "focus_devices": ["kitchen_cook_surface", "front_door_lock", "front_door_contact", "water_leak_detector", "temperature_sensor"], "focus_chunk_ids": ["C06", "C18", "C27"], "suspected_patterns": ["High temperature readings across all rooms potentially indicating HVAC failure or sensor calibration drift.", "Discrepancy between occupancy events and room activity counts suggests potential false positives or delayed signal propagation.", "Sequence of door lock/unlock events occurring during occupied periods requires verification to rule out unauthorized access or system glitches."], "why_these_chunks": ["C06: Contains critical operational state changes (cook surface on, lights off) and a missing temperature reading, which is a primary indicator for safety anomalies.", "C18: Records specific manual lock operations followed immediately by contact state changes while occupants are present in other rooms, raising security questions.", "C27: Captures the end-of-day transition sequence involving auto-locking and window closure, crucial for validating the home's 'away' mode activation logic."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The home is experiencing a system-wide sensor calibration drift or unit mismatch, where all temperature readings are erroneously multiplied by a factor of approximately 10 (e.g., reading 25°C as 2503), while actual environmental conditions remain stable and safe.\",\n      \"evidence\": [\n        \"C06: Temperature values jump to ~2500-2530 immediately after the cook surface turns off, which is physically impossible for indoor air temperature even if the stove was left on.\",\n        \"C18: Temperature values drop to ~2350-2380, a consistent offset from the previous high values, suggesting a systematic error rather than a thermal event.\",\n        \"C27: Temperature values reset to ~2250-2260, aligning with expected evening ambient temperatures if the multiplier were removed.\",\n        \"All sensors report identical patterns of fluctuation across different rooms simultaneously.\"\n      ],\n      \"weaknesses\": [\n        \"Does not explain the momentary `None` readings at C06/07:11:05 and C06/07:21:00.\",\n        \"Does not account for the specific door lock/unlock sequence occurring during occupied hours.\"\n      ]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"Resident behavior involves standard manual locking upon exiting a room or near the entrance, followed by automatic re-locking upon departure, indicating proper security protocol usage.\",\n      \"evidence\": [\n        \"C06: Manual lock operation at 07:14:35 coincides with occupancy in Kids/Master Bedroom but absence in Entrance initially; Auto-lock follows immediately after Entrance occupancy is detected at 07:14:46.\",\n        \"C18: Similar pattern at 16:30:00 (Manual Lock) followed by immediate Contact State change and Auto-lock logic.\",\n        \"High frequency of 'Occupancy' events (1089) correlates with normal daily movement between rooms (Living, Kitchen, Bedrooms).\"\n      ],\n      \"weaknesses\": [\n        \"The timing of the manual lock in C06 occurs while the resident appears to still be moving through other rooms (Master/Kids occupied), which could suggest confusion or an anomaly if they forgot they were inside.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Critical HVAC Failure or Sensor Calibration Catastrophe causing dangerously high reported temperatures, potentially triggering false fire alarms or indicating a total loss of climate control despite nominal device states.\",\n      \"threat_type\": \"Environmental Hazard / System Failure\",\n      \"evidence\": [\n        \"C06: Reported temperatures reach 2530 (approx. 25°C * 100 or similar scaling error) while the cook surface has been OFF since 07:20:00, yet values remain elevated until the end of the chunk.\",\n        \"C18: Values hover around 2350-2380, significantly higher than the baseline seen in C27 (~2250).\",\n        \"The magnitude of the spike (hundreds of units) far exceeds any reasonable thermal gradient caused by cooking activities lasting only 10 minutes.\",\n        \"Missing data points (`None`) at critical times (07:11, 07:21) suggest sensor overload or communication failure under stress.\"\n      ],\n      \"weaknesses\": [\n        \"If the raw data is indeed scaled incorrectly by the reporting system, the physical danger may be illusory.\",\n        \"No active fire alarm or smoke detector trigger logs are present in the provided chunks to confirm an emergency state.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Potential Unauthorized Access or Intrusion Attempt involving delayed entry detection or manipulation of the front door lock state while residents are away from the entrance zone.\",\n      \"threat_type\": \"Security Breach\",\n      \"evidence\": [\n        \"C06: At 07:14:35, a Manual Lock operation occurs. Immediately at 07:14:37, the DoorContact becomes `False` (Open), then at 07:14:38 Entrance Occupancy is detected as `1`. This sequence implies someone entered, unlocked, then locked again, or the system glitched.\",\n        \"C18: At 16:30:00, Manual Lock occurs. Contact opens at 16:30:02. Occupancy returns instantly. While likely normal exit/entry, the tight coupling requires verification that the 'Manual' operator was authorized.\",\n        \"The discrepancy between `front_door_contact` state changes and `entrance_occupancy` timestamps suggests potential signal latency or tampering.\"\n      ],\n      \"weaknesses\": [\n        \"Both incidents show immediate return to 'Closed/Locked' state within seconds, making sustained intrusion unlikely.\",\n        \"Auto-lock functionality activates correctly in both cases, mitigating the risk of the door being left open.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"C06 Temperature Readings: The values jumping to 2500+ range immediately after cooking stops and remaining there contradicts physical thermodynamics unless the sensor is broken or the unit of measurement is fundamentally misreported.\",\n    \"C06 Sequence Timing: The exact overlap of Front Door Manual Lock -> Contact Open -> Entrance Occupancy -> Auto Lock within a 13-second window creates a narrow window to determine if this was a legitimate resident action or a forced entry attempt.\"\n  ],\n  \"missing_information\": [\n    \"Raw temperature units (Celsius vs Fahrenheit vs Raw ADC counts) to verify if the '2503' reading is actually 25.03°C or a true anomaly.\",\n    \"History of the 'TemperatureMeasurement.MeasuredValue = None' errors to determine if it is a recurring hardware fault or intermittent interference.\",\n    \"Video footage or motion sensor granularity for the front door area during the 07:14 and 16:30 windows to confirm who performed the manual locking.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The home is experiencing a system-wide sensor calibration drift or unit mismatch, where all temperature readings are erroneously multiplied by a factor of approximately 10 (e.g., reading 25°C as 2503), while actual environmental conditions remain stable and safe.", "evidence": ["C06: Temperature values jump to ~2500-2530 immediately after the cook surface turns off, which is physically impossible for indoor air temperature even if the stove was left on.", "C18: Temperature values drop to ~2350-2380, a consistent offset from the previous high values, suggesting a systematic error rather than a thermal event.", "C27: Temperature values reset to ~2250-2260, aligning with expected evening ambient temperatures if the multiplier were removed.", "All sensors report identical patterns of fluctuation across different rooms simultaneously."], "weaknesses": ["Does not explain the momentary `None` readings at C06/07:11:05 and C06/07:21:00.", "Does not account for the specific door lock/unlock sequence occurring during occupied hours."]}, {"id": "N2", "description": "Resident behavior involves standard manual locking upon exiting a room or near the entrance, followed by automatic re-locking upon departure, indicating proper security protocol usage.", "evidence": ["C06: Manual lock operation at 07:14:35 coincides with occupancy in Kids/Master Bedroom but absence in Entrance initially; Auto-lock follows immediately after Entrance occupancy is detected at 07:14:46.", "C18: Similar pattern at 16:30:00 (Manual Lock) followed by immediate Contact State change and Auto-lock logic.", "High frequency of 'Occupancy' events (1089) correlates with normal daily movement between rooms (Living, Kitchen, Bedrooms)."], "weaknesses": ["The timing of the manual lock in C06 occurs while the resident appears to still be moving through other rooms (Master/Kids occupied), which could suggest confusion or an anomaly if they forgot they were inside."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Critical HVAC Failure or Sensor Calibration Catastrophe causing dangerously high reported temperatures, potentially triggering false fire alarms or indicating a total loss of climate control despite nominal device states.", "threat_type": "Environmental Hazard / System Failure", "evidence": ["C06: Reported temperatures reach 2530 (approx. 25°C * 100 or similar scaling error) while the cook surface has been OFF since 07:20:00, yet values remain elevated until the end of the chunk.", "C18: Values hover around 2350-2380, significantly higher than the baseline seen in C27 (~2250).", "The magnitude of the spike (hundreds of units) far exceeds any reasonable thermal gradient caused by cooking activities lasting only 10 minutes.", "Missing data points (`None`) at critical times (07:11, 07:21) suggest sensor overload or communication failure under stress."], "weaknesses": ["If the raw data is indeed scaled incorrectly by the reporting system, the physical danger may be illusory.", "No active fire alarm or smoke detector trigger logs are present in the provided chunks to confirm an emergency state."]}, {"id": "A2", "description": "Potential Unauthorized Access or Intrusion Attempt involving delayed entry detection or manipulation of the front door lock state while residents are away from the entrance zone.", "threat_type": "Security Breach", "evidence": ["C06: At 07:14:35, a Manual Lock operation occurs. Immediately at 07:14:37, the DoorContact becomes `False` (Open), then at 07:14:38 Entrance Occupancy is detected as `1`. This sequence implies someone entered, unlocked, then locked again, or the system glitched.", "C18: At 16:30:00, Manual Lock occurs. Contact opens at 16:30:02. Occupancy returns instantly. While likely normal exit/entry, the tight coupling requires verification that the 'Manual' operator was authorized.", "The discrepancy between `front_door_contact` state changes and `entrance_occupancy` timestamps suggests potential signal latency or tampering."], "weaknesses": ["Both incidents show immediate return to 'Closed/Locked' state within seconds, making sustained intrusion unlikely.", "Auto-lock functionality activates correctly in both cases, mitigating the risk of the door being left open."]}], "most_discriminative_evidence": ["C06 Temperature Readings: The values jumping to 2500+ range immediately after cooking stops and remaining there contradicts physical thermodynamics unless the sensor is broken or the unit of measurement is fundamentally misreported.", "C06 Sequence Timing: The exact overlap of Front Door Manual Lock -> Contact Open -> Entrance Occupancy -> Auto Lock within a 13-second window creates a narrow window to determine if this was a legitimate resident action or a forced entry attempt."], "missing_information": ["Raw temperature units (Celsius vs Fahrenheit vs Raw ADC counts) to verify if the '2503' reading is actually 25.03°C or a true anomaly.", "History of the 'TemperatureMeasurement.MeasuredValue = None' errors to determine if it is a recurring hardware fault or intermittent interference.", "Video footage or motion sensor granularity for the front door area during the 07:14 and 16:30 windows to confirm who performed the manual locking."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C07\", \"C28\"],\n  \"missing_checks\": [\n    \"Verify raw temperature units (Celsius vs Fahrenheit vs ADC) for chunks C06-C28 to confirm if '2503' is a scaling error.\",\n    \"Check occupancy and sensor logs in C07 to determine the duration and frequency of 'None' temperature readings.\",\n    \"Review full door lock/unlock sequences in C28 to establish baseline behavior patterns before the anomalies in C06/C18.\"\n  ],\n  \"supervisor_notes\": [\n    \"The investigation correctly identified the temperature anomaly (A1) and security sequence discrepancies (A2) but relied heavily on isolated chunks (C06, C18).\",\n    \"Chunk C07 was skipped; it likely contains the start or continuation of the temperature 'None' errors mentioned as missing evidence in N1/A1, which is critical for diagnosing sensor failure vs. data loss.\",\n    \"Chunk C28 (end of day) was not analyzed for context regarding the auto-lock logic or evening ambient temperatures mentioned in A1's weakness section.\",\n    \"Without verifying the unit of measurement (e.g., checking metadata or adjacent chunks), the conclusion that the home is in an 'Environmental Hazard' state remains speculative.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C07", "C28"], "missing_checks": ["Verify raw temperature units (Celsius vs Fahrenheit vs ADC) for chunks C06-C28 to confirm if '2503' is a scaling error.", "Check occupancy and sensor logs in C07 to determine the duration and frequency of 'None' temperature readings.", "Review full door lock/unlock sequences in C28 to establish baseline behavior patterns before the anomalies in C06/C18."], "supervisor_notes": ["The investigation correctly identified the temperature anomaly (A1) and security sequence discrepancies (A2) but relied heavily on isolated chunks (C06, C18).", "Chunk C07 was skipped; it likely contains the start or continuation of the temperature 'None' errors mentioned as missing evidence in N1/A1, which is critical for diagnosing sensor failure vs. data loss.", "Chunk C28 (end of day) was not analyzed for context regarding the auto-lock logic or evening ambient temperatures mentioned in A1's weakness section.", "Without verifying the unit of measurement (e.g., checking metadata or adjacent chunks), the conclusion that the home is in an 'Environmental Hazard' state remains speculative."]}, "preview_triage_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Layout\nLayout: 三室两厅 (3BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kids_room: 儿童房温度传感器<temperature_sensor>, 儿童房灯<dimmable_light>, 儿童房窗帘<window_covering>, 儿童房窗户传感器<contact_sensor>, 儿童房运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅副灯<dimmable_light>, 客厅氛围灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘1<window_covering>, 客厅窗户传感器1<contact_sensor>, 客厅窗户传感器2<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n- master_bathroom: 主卫漏水传感器<water_leak_detector>, 主卫灯<onoff_light>, 主卫运动传感器<occupancy_sensor>\n- master_bedroom: 主卧床头灯<onoff_light>, 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>\n- second_bedroom: 次卧灯<dimmable_light>, 次卧空调<air_conditioner>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 398,\n    \"master_bedroom\": 517,\n    \"kids_room\": 519,\n    \"kitchen\": 303,\n    \"dining_room\": 219,\n    \"second_bedroom\": 48,\n    \"master_bathroom\": 56,\n    \"entrance\": 236,\n    \"second_bathroom\": 1\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1156,\n    \"Occupancy\": 1089,\n    \"OnOff\": 26,\n    \"StateValue\": 9,\n    \"LockState\": 5,\n    \"CurrentPositionLiftPercent100ths\": 3,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 5,\n  \"occupancy_events\": 1089,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-25T00:00:00\",\n    \"end_ts\": \"2026-06-25T01:10:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 18,\n      \"master_bedroom\": 18,\n      \"kids_room\": 18,\n      \"kitchen\": 14,\n      \"dining_room\": 3,\n      \"second_bedroom\": 3,\n      \"master_bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"kids_room_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n ", "preview_verifier_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"entrance\", \"master_bedroom\"],\n  \"focus_devices\": [\"kitchen_cook_surface\", \"front_door_lock\", \"front_door_contact\", \"water_leak_detector\", \"temperature_sensor\"],\n  \"focus_chunk_ids\": [\"C06\", \"C18\", \"C27\"],\n  \"suspected_patterns\": [\n    \"High temperature readings across all rooms potentially indicating HVAC failure or sensor calibration drift.\",\n    \"Discrepancy between occupancy events and room activity counts suggests potential false positives or delayed signal propagation.\",\n    \"Sequence of door lock/unlock events occurring during occupied periods requires verification to rule out unauthorized access or system glitches.\"\n  ],\n  \"why_these_chunks\": [\n    \"C06: Contains critical operational state changes (cook surface on, lights off) and a missing temperature reading, which is a primary indicator for safety anomalies.\",\n    \"C18: Records specific manual lock operations followed immediately by contact state changes while occupants are present in other rooms, raising security questions.\",\n    \"C27: Captures the end-of-day transition sequence involving auto-locking and window closure, crucial for validating the home's 'away' mode activation logic.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The home is experiencing a system-wide sensor calibration drift or unit mismatch, where all temperature readings are erroneously multiplied by a factor of approximately 10 (e.g., reading 25°C as 2503), while actual environmental conditions remain stable and safe.\",\n      \"evidence\": [\n        \"C06: Temperature values jump to ~2500-2530 immediately after the cook surface turns off, which is physically impossible for indoor air temperature even if the stove was left on.\",\n        \"C18: Temperature values drop to ~2350-2380, a consistent offset from the previous high values, suggesting a systematic error rather than a thermal event.\",\n        \"C27: Temperature values reset to ~2250-2260, aligning with expected evening ambient temperatures if the multiplier were removed.\",\n        \"All sensors report identical patterns of fluctuation across different rooms simultaneously.\"\n      ],\n      \"weaknesses\": [\n        \"Does not explain the momentary `None` readings at C06/07:11:05 and C06/07:21:00.\",\n        \"Does not account for the specific door lock/unlock sequence occurring during occup"}}
{"episode_id": "SQ4_FP_D_0878", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq4\\SQ4_FP_D_0878.json", "metadata": {"sq_type": "SQ4", "sq_name": "复合安全推理", "variant": "FP", "layout_id": "D", "layout_name": "独居老人 (Elderly Living Alone)", "profile_id": "elderly_living_alone", "base_date": "2026-06-10T00:00:00", "seed": 20261507, "scenario_id": "EL-03", "total_events": 1855, "anomaly_events_count": 4}, "ground_truth": {"scenario_id": "EL-03-FP", "scenario_name": "EL-03-FP: 老人在旁边慢慢做饭", "category": "elderly_specific", "is_anomaly": false, "threat_type": "none", "key_difference": "虽然老人短暂离开了厨房，但5分钟后回来检查，不是忘了关火", "difficulty_score": 10, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 2, "D5_fp_similarity": 2}, "target_room": "kitchen", "injection_time": "2026-06-10T15:11:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"Global temperature sensor calibration failure causing invalid readings (2000-2500°C) that mimic a catastrophic fire but are physically impossible for domestic environments.\",\n  \"reasoning\": [\n      \"Temperature values across all rooms consistently exceed 2000 degrees Celsius throughout the timeline, which is physically impossible for any residential scenario and indicates a unit mismatch or raw data reporting error rather than real heat.\",\n      \"The anomaly is global and stable; if it were a real fire, temperatures would likely be concentrated in specific zones (e.g., kitchen), whereas here living rooms, bedrooms, and kitchens all report identical erroneous high values simultaneously.\",\n      \"Despite the sensor failure, other systems function normally: occupants entered the home, lights turned on/off, the cook surface operated correctly, and the door lock was manually engaged without any smoke detector alarms or CO sensor triggers being recorded.\"\n    ],\n  \"key_evidence\": [\n      \"Timestamp 2026-06-10T07:05:00 shows Living Room at 2518°C while occupancy sensors confirmed human presence inside, ruling out external environmental causes.\",\n      \"Kitchen cook_surface state changed from On to Off as expected (05:50:33 to 06:36:00), and subsequent sensor logs show 'None' or erratic values instead of realistic thermal decay, confirming sensor blindness or corruption.\"\n    ],\n  \"recommended_actions\": [\n      \"Immediately inspect and recalibrate/replace all temperature sensors in the home.\",\n      \"Verify no physical damage exists despite the false readings before considering evacuation.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "Global temperature sensor calibration failure causing invalid readings (2000-2500°C) that mimic a catastrophic fire but are physically impossible for domestic environments.", "reasoning": ["Temperature values across all rooms consistently exceed 2000 degrees Celsius throughout the timeline, which is physically impossible for any residential scenario and indicates a unit mismatch or raw data reporting error rather than real heat.", "The anomaly is global and stable; if it were a real fire, temperatures would likely be concentrated in specific zones (e.g., kitchen), whereas here living rooms, bedrooms, and kitchens all report identical erroneous high values simultaneously.", "Despite the sensor failure, other systems function normally: occupants entered the home, lights turned on/off, the cook surface operated correctly, and the door lock was manually engaged without any smoke detector alarms or CO sensor triggers being recorded."], "key_evidence": ["Timestamp 2026-06-10T07:05:00 shows Living Room at 2518°C while occupancy sensors confirmed human presence inside, ruling out external environmental causes.", "Kitchen cook_surface state changed from On to Off as expected (05:50:33 to 06:36:00), and subsequent sensor logs show 'None' or erratic values instead of realistic thermal decay, confirming sensor blindness or corruption."], "recommended_actions": ["Immediately inspect and recalibrate/replace all temperature sensors in the home.", "Verify no physical damage exists despite the false readings before considering evacuation."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 77.39098072052002, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1855, "chunk_count": 24, "signals": {"room_activity": {"living_room": 498, "bedroom": 529, "kitchen": 539, "bathroom": 59, "entrance": 230}, "attribute_frequency": {"Occupancy": 946, "MeasuredValue": 870, "OnOff": 22, "CurrentPositionLiftPercent100ths": 4, "LockState": 4, "StateValue": 4, "CurrentLevel": 1}, "lock_state_flips": 4, "occupancy_events": 946, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety | behavior-sequence\",\n  \"focus_rooms\": [\n    \"kitchen\",\n    \"bedroom\",\n    \"living_room\"\n  ],\n  \"focus_devices\": [\n    \"temperature_sensor\",\n    \"occupancy_sensor\",\n    \"cook_surface\",\n    \"door_lock\",\n    \"contact_sensor\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C00\",\n    \"C01\",\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C16\"\n  ],\n  \"suspected_patterns\": [\n    \"Extreme temperature anomalies (values ~2100-2500 vs normal ~20-30) indicating sensor calibration failure or unit mismatch.\",\n    \"Prolonged absence of occupants in living/bedrooms during early morning hours (C00-C03) while kitchen sensors report high activity or temperature.\",\n    \"High frequency of 'alarmish' events correlating with temperature spikes.\",\n    \"Potential fire risk due to unattended cooking indicated by cook_surface state changes in C16 after long periods of occupancy.\"\n  ],\n  \"why_these_chunks\": [\n    \"C00-C03: Show the initial period of total house vacancy combined with bizarrely high temperature readings, suggesting a system baseline issue or environmental hazard before arrival.\",\n    \"C04-C05: Capture the transition where occupants return (high entrance/bathroom occupancy) coinciding with peak temperature values, critical for determining if the heat is human-generated (cooking/heating) or equipment failure.\",\n    \"C16: Contains specific state change data for the cook_surface ('OnOff.OnOff = False'), which is essential for assessing immediate fire safety risks post-cooking.\",\n    \"All chunks containing temperature_sensor data are required to analyze the magnitude and duration of the thermal anomaly.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety | behavior-sequence", "focus_rooms": ["kitchen", "bedroom", "living_room"], "focus_devices": ["temperature_sensor", "occupancy_sensor", "cook_surface", "door_lock", "contact_sensor"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04", "C05", "C16"], "suspected_patterns": ["Extreme temperature anomalies (values ~2100-2500 vs normal ~20-30) indicating sensor calibration failure or unit mismatch.", "Prolonged absence of occupants in living/bedrooms during early morning hours (C00-C03) while kitchen sensors report high activity or temperature.", "High frequency of 'alarmish' events correlating with temperature spikes.", "Potential fire risk due to unattended cooking indicated by cook_surface state changes in C16 after long periods of occupancy."], "why_these_chunks": ["C00-C03: Show the initial period of total house vacancy combined with bizarrely high temperature readings, suggesting a system baseline issue or environmental hazard before arrival.", "C04-C05: Capture the transition where occupants return (high entrance/bathroom occupancy) coinciding with peak temperature values, critical for determining if the heat is human-generated (cooking/heating) or equipment failure.", "C16: Contains specific state change data for the cook_surface ('OnOff.OnOff = False'), which is essential for assessing immediate fire safety risks post-cooking.", "All chunks containing temperature_sensor data are required to analyze the magnitude and duration of the thermal anomaly."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"System Sensor Calibration Offset / Unit Mismatch\",\n      \"evidence\": [\n        \"All temperature readings across all rooms (Living: ~2276, Bedroom: ~2165, Kitchen: ~2262) are consistently in the 2000-2500 range throughout the entire timeline.\",\n        \"The values remain relatively stable and correlate with expected diurnal heating patterns (slight rise as occupancy increases), suggesting a systematic error rather than random noise.\",\n        \"No single sensor is reporting wildly different values compared to others; the offset appears global.\"\n      ],\n      \"weaknesses\": [\n        \"This hypothesis assumes the hardware is functioning correctly but misconfigured. If the unit is actually Celsius, a reading of 2300°C would indicate catastrophic equipment failure or fire, not just calibration.\",\n        \"Does not explain why `kitchen_temp_sensor` returns `None` at specific times (05:51, 06:37) if it were simply a constant offset failure.\"\n      ]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"Delayed Occupancy Reporting\",\n      \"evidence\": [\n        \"Occupancy sensors show '0' for all rooms from 00:00 to 05:30, despite high ambient heat suggesting activity or residual warmth from previous days.\",\n        \"Occupancy events spike only after 05:30 when lights turn on and temperatures continue to rise.\",\n        \"Structured signals show `occupancy_events`: 946 vs `lock_state_flips`: 4, suggesting the system registered many presence changes but perhaps lagged in room-level attribution.\"\n      ],\n      \"weaknesses\": [\n        \"A delay of 5+ hours for occupancy detection is highly irregular for standard PIR/RFID systems.\",\n        \"Cannot explain the initial massive temperature spike if no one was present to generate it, unless the house was pre-heated by an external event (fire/equipment).\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Catastrophic Thermal Event (Fire or Equipment Failure)\",\n      \"threat_type\": \"Life Safety / Fire Hazard\",\n      \"evidence\": [\n        \"Temperature values exceeding 2000°C (e.g., Living Room: 2518 at 07:05) are physically impossible for domestic environments and indicate either extreme real-world heat or total sensor data corruption.\",\n        \"If interpreted as real-world Celsius, this indicates a massive uncontained fire starting around 00:00 and intensifying through morning hours.\",\n        \"Correlation between rising temps and eventual human arrival suggests occupants entered a hazardous environment.\",\n        \"Kitchen cook_surface activates at 05:50 while temps are already >2400, indicating potential ignition source or post-ignition thermal runaway.\"\n      ],\n      \"weaknesses\": [\n        \"Could be a software bug where the sensor reports raw ADC counts instead of converted degrees (e.g., 2300 counts != 2300 degrees).\",\n        \"No smoke detector alarms or door lock breach attempts recorded prior to manual locking at 06:58, which might be expected in a rapid evacuation scenario.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Sensor Data Corruption / Firmware Glitch\",\n      \"threat_type\": \"Data Integrity / False Positive Alarm\",\n      \"evidence\": [\n        \"Sudden `None` values in `kitchen_temp_sensor` logs at 05:51:03 and 06:37:00, breaking the continuous stream of high-value readings.\",\n        \"The absolute magnitude (>2000) is statistically anomalous for any known residential heating appliance.\",\n        \"Consistency of the error across multiple zones suggests a central processing issue rather than individual sensor failure.\"\n      ],\n      \"weaknesses\": [\n        \"Does not account for the *trend* of the numbers rising logically over time; a glitch usually results in static errors or random noise, not a coherent ramp-up curve.\",\n        \"Fails to explain why the system continued to log other valid state changes (locks, lights, window covers) during the same corrupted period.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The specific timestamp 2026-06-10T07:05:00 showing `living_room_temp_sensor` at 2518 and `bedroom_temp_sensor` at 2414 strongly points towards a physical anomaly (fire) rather than a simple unit mismatch, as such temperatures would cause structural damage regardless of units used.\",\n    \"The sequence `kitchen_cook_surface | OnOff.OnOff = True` (05:50:33) followed immediately by `kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = None` (05:51:03) indicates the sensor may have been destroyed or blinded by the event it was measuring.\",\n    \"Manual door lock operation at 06:58:05 (LockState=2 then 1) occurring after temperatures peaked suggests an intentional security measure taken in response to the perceived threat, distinguishing this from passive system failure.\"\n  ],\n  \"missing_information\": [\n    \"Smoke detector status logs and alarm activation timestamps.\",\n    \"Carbon monoxide (CO) sensor readings.\",\n    \"Video feed snapshots or motion blur analysis from entrance cameras to confirm occupant behavior upon entry.\",\n    \"Historical baseline temperature data for this specific home to confirm if 2000+ readings are a known persistent bug or a new anomaly.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "System Sensor Calibration Offset / Unit Mismatch", "evidence": ["All temperature readings across all rooms (Living: ~2276, Bedroom: ~2165, Kitchen: ~2262) are consistently in the 2000-2500 range throughout the entire timeline.", "The values remain relatively stable and correlate with expected diurnal heating patterns (slight rise as occupancy increases), suggesting a systematic error rather than random noise.", "No single sensor is reporting wildly different values compared to others; the offset appears global."], "weaknesses": ["This hypothesis assumes the hardware is functioning correctly but misconfigured. If the unit is actually Celsius, a reading of 2300°C would indicate catastrophic equipment failure or fire, not just calibration.", "Does not explain why `kitchen_temp_sensor` returns `None` at specific times (05:51, 06:37) if it were simply a constant offset failure."]}, {"id": "N2", "description": "Delayed Occupancy Reporting", "evidence": ["Occupancy sensors show '0' for all rooms from 00:00 to 05:30, despite high ambient heat suggesting activity or residual warmth from previous days.", "Occupancy events spike only after 05:30 when lights turn on and temperatures continue to rise.", "Structured signals show `occupancy_events`: 946 vs `lock_state_flips`: 4, suggesting the system registered many presence changes but perhaps lagged in room-level attribution."], "weaknesses": ["A delay of 5+ hours for occupancy detection is highly irregular for standard PIR/RFID systems.", "Cannot explain the initial massive temperature spike if no one was present to generate it, unless the house was pre-heated by an external event (fire/equipment)."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Catastrophic Thermal Event (Fire or Equipment Failure)", "threat_type": "Life Safety / Fire Hazard", "evidence": ["Temperature values exceeding 2000°C (e.g., Living Room: 2518 at 07:05) are physically impossible for domestic environments and indicate either extreme real-world heat or total sensor data corruption.", "If interpreted as real-world Celsius, this indicates a massive uncontained fire starting around 00:00 and intensifying through morning hours.", "Correlation between rising temps and eventual human arrival suggests occupants entered a hazardous environment.", "Kitchen cook_surface activates at 05:50 while temps are already >2400, indicating potential ignition source or post-ignition thermal runaway."], "weaknesses": ["Could be a software bug where the sensor reports raw ADC counts instead of converted degrees (e.g., 2300 counts != 2300 degrees).", "No smoke detector alarms or door lock breach attempts recorded prior to manual locking at 06:58, which might be expected in a rapid evacuation scenario."]}, {"id": "A2", "description": "Sensor Data Corruption / Firmware Glitch", "threat_type": "Data Integrity / False Positive Alarm", "evidence": ["Sudden `None` values in `kitchen_temp_sensor` logs at 05:51:03 and 06:37:00, breaking the continuous stream of high-value readings.", "The absolute magnitude (>2000) is statistically anomalous for any known residential heating appliance.", "Consistency of the error across multiple zones suggests a central processing issue rather than individual sensor failure."], "weaknesses": ["Does not account for the *trend* of the numbers rising logically over time; a glitch usually results in static errors or random noise, not a coherent ramp-up curve.", "Fails to explain why the system continued to log other valid state changes (locks, lights, window covers) during the same corrupted period."]}], "most_discriminative_evidence": ["The specific timestamp 2026-06-10T07:05:00 showing `living_room_temp_sensor` at 2518 and `bedroom_temp_sensor` at 2414 strongly points towards a physical anomaly (fire) rather than a simple unit mismatch, as such temperatures would cause structural damage regardless of units used.", "The sequence `kitchen_cook_surface | OnOff.OnOff = True` (05:50:33) followed immediately by `kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = None` (05:51:03) indicates the sensor may have been destroyed or blinded by the event it was measuring.", "Manual door lock operation at 06:58:05 (LockState=2 then 1) occurring after temperatures peaked suggests an intentional security measure taken in response to the perceived threat, distinguishing this from passive system failure."], "missing_information": ["Smoke detector status logs and alarm activation timestamps.", "Carbon monoxide (CO) sensor readings.", "Video feed snapshots or motion blur analysis from entrance cameras to confirm occupant behavior upon entry.", "Historical baseline temperature data for this specific home to confirm if 2000+ readings are a known persistent bug or a new anomaly."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C06\", \"C07\", \"C08\", \"C09\"],\n  \"missing_checks\": [\n    \"Smoke detector status logs and alarm activation timestamps.\",\n    \"Carbon monoxide (CO) sensor readings.\",\n    \"Video feed snapshots or motion blur analysis from entrance cameras to confirm occupant behavior upon entry.\",\n    \"Historical baseline temperature data for this specific home to confirm if 2000+ readings are a known persistent bug or a new anomaly.\"\n  ],\n  \"supervisor_notes\": [\n    \"The current investigation is on-topic, correctly identifying the critical thermal anomaly and potential fire risk.\",\n    \"Evidence sufficiency is low because the Investigator explicitly requested 'Smoke detector status logs' and 'Carbon monoxide (CO) sensor readings', which are absent from the currently selected chunks (C00-C05, C16).\",\n    \"The sequence of events suggests an active emergency (high heat, cook surface usage followed by sensor failure); therefore, the evidence collection must expand immediately into the post-incident timeline (Chunks C06-C09) to capture any subsequent safety system triggers (smoke alarms, evacuation attempts) or further state changes that occurred after the initial spike at 07:05.\",\n    \"Without data on smoke/CO sensors, the assessment of 'Life Safety' threat remains speculative rather than confirmed.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C06", "C07", "C08", "C09"], "missing_checks": ["Smoke detector status logs and alarm activation timestamps.", "Carbon monoxide (CO) sensor readings.", "Video feed snapshots or motion blur analysis from entrance cameras to confirm occupant behavior upon entry.", "Historical baseline temperature data for this specific home to confirm if 2000+ readings are a known persistent bug or a new anomaly."], "supervisor_notes": ["The current investigation is on-topic, correctly identifying the critical thermal anomaly and potential fire risk.", "Evidence sufficiency is low because the Investigator explicitly requested 'Smoke detector status logs' and 'Carbon monoxide (CO) sensor readings', which are absent from the currently selected chunks (C00-C05, C16).", "The sequence of events suggests an active emergency (high heat, cook surface usage followed by sensor failure); therefore, the evidence collection must expand immediately into the post-incident timeline (Chunks C06-C09) to capture any subsequent safety system triggers (smoke alarms, evacuation attempts) or further state changes that occurred after the initial spike at 07:05.", "Without data on smoke/CO sensors, the assessment of 'Life Safety' threat remains speculative rather than confirmed."]}, "preview_triage_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Layout\nLayout: 独居老人 (Elderly Living Alone)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>, 床头灯<onoff_light>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房运动传感器<occupancy_sensor>\n- living_room: 客厅温度传感器<temperature_sensor>, 客厅灯<dimmable_light>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 498,\n    \"bedroom\": 529,\n    \"kitchen\": 539,\n    \"bathroom\": 59,\n    \"entrance\": 230\n  },\n  \"attribute_frequency\": {\n    \"Occupancy\": 946,\n    \"MeasuredValue\": 870,\n    \"OnOff\": 22,\n    \"CurrentPositionLiftPercent100ths\": 4,\n    \"LockState\": 4,\n    \"StateValue\": 4,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 946,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-10T00:00:00\",\n    \"end_ts\": \"2026-06-10T01:35:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 24,\n      \"bedroom\": 24,\n      \"kitchen\": 24,\n      \"bathroom\": 4,\n      \"entrance\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"kitchen_occupancy\"\n    ],\n    \"alarmish_count\": 20,\n    \"preview_lines\": [\n      \"[2026-06-10T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2276\",\n      \"[2026-06-10T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2165\",\n      \"[2026-06-10T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2262\",\n      \"[2026-06-10T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-10T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-10T00:00:00] kitchen_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-10T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-10T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-10T00:05:00] li", "preview_verifier_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety | behavior-sequence\",\n  \"focus_rooms\": [\n    \"kitchen\",\n    \"bedroom\",\n    \"living_room\"\n  ],\n  \"focus_devices\": [\n    \"temperature_sensor\",\n    \"occupancy_sensor\",\n    \"cook_surface\",\n    \"door_lock\",\n    \"contact_sensor\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C00\",\n    \"C01\",\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C16\"\n  ],\n  \"suspected_patterns\": [\n    \"Extreme temperature anomalies (values ~2100-2500 vs normal ~20-30) indicating sensor calibration failure or unit mismatch.\",\n    \"Prolonged absence of occupants in living/bedrooms during early morning hours (C00-C03) while kitchen sensors report high activity or temperature.\",\n    \"High frequency of 'alarmish' events correlating with temperature spikes.\",\n    \"Potential fire risk due to unattended cooking indicated by cook_surface state changes in C16 after long periods of occupancy.\"\n  ],\n  \"why_these_chunks\": [\n    \"C00-C03: Show the initial period of total house vacancy combined with bizarrely high temperature readings, suggesting a system baseline issue or environmental hazard before arrival.\",\n    \"C04-C05: Capture the transition where occupants return (high entrance/bathroom occupancy) coinciding with peak temperature values, critical for determining if the heat is human-generated (cooking/heating) or equipment failure.\",\n    \"C16: Contains specific state change data for the cook_surface ('OnOff.OnOff = False'), which is essential for assessing immediate fire safety risks post-cooking.\",\n    \"All chunks containing temperature_sensor data are required to analyze the magnitude and duration of the thermal anomaly.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"System Sensor Calibration Offset / Unit Mismatch\",\n      \"evidence\": [\n        \"All temperature readings across all rooms (Living: ~2276, Bedroom: ~2165, Kitchen: ~2262) are consistently in the 2000-2500 range throughout the entire timeline.\",\n        \"The values remain relatively stable and correlate with expected diurnal heating patterns (slight rise as occupancy increases), suggesting a systematic error rather than random noise.\",\n        \"No single sensor is reporting wildly different values compared to others; the offset appears global.\"\n      ],\n      \"weaknesses\": [\n        \"This hypothesis assumes the hardware is functioning correctly but misconfigured. If the unit is actual"}}
{"episode_id": "SQ4_TP_B_0721", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq4\\SQ4_TP_B_0721.json", "metadata": {"sq_type": "SQ4", "sq_name": "复合安全推理", "variant": "TP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "family_with_children", "base_date": "2026-06-26T00:00:00", "seed": 20261350, "scenario_id": "FG-02", "total_events": 1834, "anomaly_events_count": 3}, "ground_truth": {"scenario_id": "FG-02", "scenario_name": "电器过热起火", "category": "fire_gas", "is_anomaly": true, "threat_type": "fire_risk", "key_evidence": ["温度异常上升但无合理热源（空调关闭/制冷模式，灶具关闭）", "上升速度超过正常烹饪或日照导致的范围"], "expected_response": "火灾风险警报，建议住户检查该区域电器", "difficulty_score": 10, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 2, "D5_fp_similarity": 2}, "target_room": "balcony", "injection_time": "2026-06-26T09:04:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"intrusion\",\n  \"threat_description\": \"An unauthorized intruder entered the residence via the front door between 07:29 and 07:30, activated kitchen appliances while occupants were in the master bedroom, and remained inside with sustained high occupancy readings.\",\n  \"reasoning\": [\n    \"The front door contact state flipped to 'False' (open) at 07:29:20, immediately followed by the entrance occupancy sensor triggering at 07:29:21, confirming physical entry.\",\n    \"Kitchen devices (light and cook surface) were activated sequentially at 06:39 and 06:39:40 while the house was reported empty until that moment, suggesting pre-entry preparation or immediate action upon entry.\",\n    \"Entrance occupancy remained persistently high ('1') from 07:29 onwards, coinciding with a resident remaining in the master bedroom, indicating an intruder moving through the home rather than a transient event.\",\n    \"The temperature spikes observed in later chunks (e.g., reaching ~25.4°C scaled values) correlate with appliance usage and potential environmental changes caused by the presence of multiple people or equipment failure, but the primary threat is the confirmed breach.\"\n  ],\n  \"key_evidence\": [\n    \"Front door contact opened (False) at 07:29:20, 1 second before entrance occupancy spiked to True at 07:29:21.\",\n    \"Sequential activation of kitchen light and cook surface at 06:39 despite zero occupancy prior to 06:35.\",\n    \"Continuous entrance occupancy signal starting at 07:29:21 and persisting throughout the log duration.\",\n    \"Master bedroom occupancy started at 06:35 and persisted, while the intruder accessed other areas including the kitchen.\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately call local law enforcement to report a break-in.\",\n    \"Do not enter the premises until authorities have secured the scene.\",\n    \"Preserve all digital logs, camera footage, and device states for investigation.\",\n    \"Check for signs of forced entry at the front door and any damage to kitchen appliances.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "intrusion", "threat_description": "An unauthorized intruder entered the residence via the front door between 07:29 and 07:30, activated kitchen appliances while occupants were in the master bedroom, and remained inside with sustained high occupancy readings.", "reasoning": ["The front door contact state flipped to 'False' (open) at 07:29:20, immediately followed by the entrance occupancy sensor triggering at 07:29:21, confirming physical entry.", "Kitchen devices (light and cook surface) were activated sequentially at 06:39 and 06:39:40 while the house was reported empty until that moment, suggesting pre-entry preparation or immediate action upon entry.", "Entrance occupancy remained persistently high ('1') from 07:29 onwards, coinciding with a resident remaining in the master bedroom, indicating an intruder moving through the home rather than a transient event.", "The temperature spikes observed in later chunks (e.g., reaching ~25.4°C scaled values) correlate with appliance usage and potential environmental changes caused by the presence of multiple people or equipment failure, but the primary threat is the confirmed breach."], "key_evidence": ["Front door contact opened (False) at 07:29:20, 1 second before entrance occupancy spiked to True at 07:29:21.", "Sequential activation of kitchen light and cook surface at 06:39 despite zero occupancy prior to 06:35.", "Continuous entrance occupancy signal starting at 07:29:21 and persisting throughout the log duration.", "Master bedroom occupancy started at 06:35 and persisted, while the intruder accessed other areas including the kitchen."], "recommended_actions": ["Immediately call local law enforcement to report a break-in.", "Do not enter the premises until authorities have secured the scene.", "Preserve all digital logs, camera footage, and device states for investigation.", "Check for signs of forced entry at the front door and any damage to kitchen appliances."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 72.93203854560852, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1834, "chunk_count": 23, "signals": {"room_activity": {"living_room": 403, "master_bedroom": 515, "second_bedroom": 336, "kitchen": 304, "bathroom": 48, "entrance": 228}, "attribute_frequency": {"MeasuredValue": 1158, "Occupancy": 640, "OnOff": 15, "StateValue": 7, "LockState": 5, "SmokeState": 1, "SystemMode": 1, "OperationalState": 1, "CurrentPositionLiftPercent100ths": 1}, "lock_state_flips": 5, "occupancy_events": 640, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\n    \"kitchen\",\n    \"living_room\",\n    \"entrance\"\n  ],\n  \"focus_devices\": [\n    \"kitchen_temp_sensor\",\n    \"living_room_temp_sensor\",\n    \"master_bedroom_temp_sensor\",\n    \"second_bedroom_temp_sensor\",\n    \"entrance_occupancy\",\n    \"living_room_occupancy\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C06\",\n    \"C17\"\n  ],\n  \"suspected_patterns\": [\n    \"Anomalous temperature scaling: Sensor values range from ~2200 to ~2560, likely representing scaled Celsius (e.g., x10 or raw integer encoding), indicating a potential heating event rather than ambient cooling.\",\n    \"Occupancy-Heat Correlation: High occupancy in living room and master bedroom coincides with peak temperature readings (Chunks C05-C10).\",\n    \"Nighttime Activity Anomaly: Occupancy sensors trigger repeatedly after 21:00 (Chunks C20-C22) when typical residential activity subsides.\",\n    \"Device State Transition: Living room AC switched OFF at 22:21 while occupancy remains high, suggesting manual override or system failure.\"\n  ],\n  \"why_these_chunks\": [\n    \"C02-C04: Show the initial rapid rise in temperature values across all rooms, establishing the baseline of the anomaly.\",\n    \"C05-C06: Capture the peak temperature period and correlate it with specific occupancy events in the bedrooms.\",\n    \"C17: Contains critical device state changes (AC turning off) amidst continued high temperatures and occupancy, indicating a potential safety hazard escalation.\",\n    \"C20-C22: Highlight unusual late-night human presence which could imply unauthorized entry or abnormal household behavior.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "living_room", "entrance"], "focus_devices": ["kitchen_temp_sensor", "living_room_temp_sensor", "master_bedroom_temp_sensor", "second_bedroom_temp_sensor", "entrance_occupancy", "living_room_occupancy"], "focus_chunk_ids": ["C02", "C03", "C04", "C05", "C06", "C17"], "suspected_patterns": ["Anomalous temperature scaling: Sensor values range from ~2200 to ~2560, likely representing scaled Celsius (e.g., x10 or raw integer encoding), indicating a potential heating event rather than ambient cooling.", "Occupancy-Heat Correlation: High occupancy in living room and master bedroom coincides with peak temperature readings (Chunks C05-C10).", "Nighttime Activity Anomaly: Occupancy sensors trigger repeatedly after 21:00 (Chunks C20-C22) when typical residential activity subsides.", "Device State Transition: Living room AC switched OFF at 22:21 while occupancy remains high, suggesting manual override or system failure."], "why_these_chunks": ["C02-C04: Show the initial rapid rise in temperature values across all rooms, establishing the baseline of the anomaly.", "C05-C06: Capture the peak temperature period and correlate it with specific occupancy events in the bedrooms.", "C17: Contains critical device state changes (AC turning off) amidst continued high temperatures and occupancy, indicating a potential safety hazard escalation.", "C20-C22: Highlight unusual late-night human presence which could imply unauthorized entry or abnormal household behavior."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The house is empty with sensors reporting baseline ambient temperatures (scaled by x10) and no human activity.\",\n      \"evidence\": [\"Occupancy sensors reported '0' for all rooms between 03:00 and 06:35.\", \"Temperature values in the 2300-2400 range are consistent with a stable indoor environment if scaled Celsius (~23-24°C).\"],\n      \"weaknesses\": [\"Fails to account for the sudden spike in occupancy at 06:35 in the master bedroom.\", \"Cannot explain the rapid temperature increase observed after 06:40 coinciding with cooking events.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Unauthorized intrusion followed by a fire or extreme heat generation event inside the residence.\",\n      \"threat_type\": \"Fire/Explosion/Intrusion\",\n      \"evidence\": [\"At 07:29, the front door contact flipped to False (open) immediately before entrance occupancy spiked to 1. The lock state flipped twice within seconds, suggesting forced entry or tampering rather than normal manual locking/unlocking patterns.\", \"Starting at 06:39, kitchen devices activated (lights and cook surface), but the system was already in a high-temperature state (~25°C real-world equivalent).\", \"Between 06:40 and 08:44, temperatures rose from ~2500 to >2540 (real-world ~25-25.4°C? Or potentially higher if scaling changes or sensor drift occurs due to heat). *Correction based on data context*: If 2341 = 23.41C, then 2540 = 25.40C. This is not a fire temperature. Re-evaluating A1.\",\n      \"revised_evidence_for_A1\": [\"At 07:29, the front door contact flipped to False (open) immediately before entrance occupancy spiked to 1. The lock state flipped twice within seconds (Manual Unlock -> Auto Lock), indicating an intruder entered via the front door.\", \"Simultaneous activation of kitchen lights and cook surface at 06:39 while the house was supposedly empty suggests either automated scheduling failure or manual activation by an intruder.\", \"Persistent high occupancy readings in the entrance (starting 07:29) and master bedroom (starting 06:35) despite no other room activity indicates someone moving through the house to a specific location.\"]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Sensor Malfunction causing false positives for both occupancy and temperature.\",\n      \"threat_type\": \"False Positive/Data Integrity\",\n      \"evidence\": [\"All temperature sensors show nearly identical values across different rooms simultaneously, which is physically unlikely without perfect thermal equilibrium (suggesting a shared data feed error or calibration offset).\", \"Occupancy sensors trigger sporadically ('flips') without corresponding motion logic in other zones.\", \"The 'MeasuredValue' attribute frequency is extremely high compared to discrete states like 'LockState' or 'SmokeState', suggesting a data stream flooding issue.\"],\n      \"weaknesses\": [\"Does not explain the precise temporal correlation between the front door opening (07:29:20) and the entrance occupancy signal (07:29:21). Physical causality is strong here.\", \"The sequential activation of kitchen appliances (light -> stove) follows a logical human pattern that random noise would not typically replicate.\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"Temporal Sequence at 07:29: Front Door Contact -> False (Open) occurred 2 seconds BEFORE Entrance Occupancy -> True. This confirms physical entry.\",\n    \"Device Activation Cluster: Kitchen Light and Cook Surface turned ON at 06:39 while the house was unoccupied until 06:35. This suggests pre-entry preparation or immediate post-entry action.\",\n    \"Sustained Master Bedroom Occupancy: Once occupied at 06:35, the master bedroom remained occupied continuously until the end of the log, while other rooms cycled or stayed empty.\"\n  ],\n  \"missing_information\": [\n    \"Video footage or audio logs from the time of the intrusion (06:35 - 07:30) to confirm identity and actions.\",\n    \"Historical temperature data prior to 02:40 to determine if the 'high' baseline (2341) was actually abnormal or the new normal.\",\n    \"Confirmation of whether the 'Cook Surface' being ON resulted in smoke detection (SmokeState count is only 1 in structured signals, likely unrelated to this event).\"\n  ]\n}", "investigator_parsed": {"_parse_failed": true, "raw_preview": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The house is empty with sensors reporting baseline ambient temperatures (scaled by x10) and no human activity.\",\n      \"evidence\": [\"Occupancy sensors reported '0' for all rooms between 03:00 and 06:35.\", \"Temperature values in the 2300-2400 range are consistent with a stable indoor environment if scaled Celsius (~23-24°C).\"],\n      \"weaknesses\": [\"Fails to account for the sudden spike in occupancy at 06:35 in the master bedroom.\", \"Cannot explain the rapid temperature increase observed after 06:40 coinciding with cooking events.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Unauthorized intrusion followed by a fire or extreme heat generation event inside the residence.\",\n      \"threat_type\": \"Fire/Explosion/Intrusion\",\n      \"evidence\": [\"At 07:29, the front door contact flipped to False (open) immediately before entrance occupancy spiked to 1. The lock state flipped twice w"}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C07\", \"C08\", \"C09\", \"C10\"],\n  \"missing_checks\": [\n    \"Verify if kitchen temperature spiked significantly during the appliance activation (C06-C10) to confirm heat source vs. sensor drift.\",\n    \"Cross-reference SmokeState logs with the specific time of stove activation and any subsequent temperature anomalies.\"\n  ],\n  \"supervisor_notes\": [\n    \"The current evidence collection is insufficient because it focuses heavily on the intrusion event (C02-C06, C17) and late-night activity (C20-C22), but completely ignores the critical window immediately following the intrusion (approx. 07:30 - 08:44).\",\n    \"The Investigator identified a temperature rise from ~2500 to >2540 between 06:40 and 08:44 as potentially significant (or needing re-evaluation of scaling). Chunks C07, C08, C09, and C10 cover this exact timeframe and are essential to determine if the kitchen fire hypothesis (A1) was validated by actual thermal spikes or if the 'high' temperature was merely a sensor anomaly.\",\n    \"Without these chunks, we cannot rule out that the stove activation led to a fire or excessive heat generation, which contradicts the initial assumption that 25°C is safe based solely on the raw integer values seen earlier.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C07", "C08", "C09", "C10"], "missing_checks": ["Verify if kitchen temperature spiked significantly during the appliance activation (C06-C10) to confirm heat source vs. sensor drift.", "Cross-reference SmokeState logs with the specific time of stove activation and any subsequent temperature anomalies."], "supervisor_notes": ["The current evidence collection is insufficient because it focuses heavily on the intrusion event (C02-C06, C17) and late-night activity (C20-C22), but completely ignores the critical window immediately following the intrusion (approx. 07:30 - 08:44).", "The Investigator identified a temperature rise from ~2500 to >2540 between 06:40 and 08:44 as potentially significant (or needing re-evaluation of scaling). Chunks C07, C08, C09, and C10 cover this exact timeframe and are essential to determine if the kitchen fire hypothesis (A1) was validated by actual thermal spikes or if the 'high' temperature was merely a sensor anomaly.", "Without these chunks, we cannot rule out that the stove activation led to a fire or excessive heat generation, which contradicts the initial assumption that 25°C is safe based solely on the raw integer values seen earlier."]}, "preview_triage_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 403,\n    \"master_bedroom\": 515,\n    \"second_bedroom\": 336,\n    \"kitchen\": 304,\n    \"bathroom\": 48,\n    \"entrance\": 228\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1158,\n    \"Occupancy\": 640,\n    \"OnOff\": 15,\n    \"StateValue\": 7,\n    \"LockState\": 5,\n    \"SmokeState\": 1,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"CurrentPositionLiftPercent100ths\": 1\n  },\n  \"lock_state_flips\": 5,\n  \"occupancy_events\": 640,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-26T00:00:00\",\n    \"end_ts\": \"2026-06-26T01:20:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 20,\n      \"master_bedroom\": 19,\n      \"second_bedroom\": 19,\n      \"kitchen\": 16,\n      \"bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"master_bedroom_occupancy\"\n    ],\n    \"alarmish_count\": 15,\n    \"preview_lines\": [\n      \"[2026-06-26T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2275\",\n      \"[2026-06-26T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2261\",\n      \"[2026-06-26T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2274\",\n      \"[2026-06-26T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2273\",\n      ", "preview_verifier_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\n    \"kitchen\",\n    \"living_room\",\n    \"entrance\"\n  ],\n  \"focus_devices\": [\n    \"kitchen_temp_sensor\",\n    \"living_room_temp_sensor\",\n    \"master_bedroom_temp_sensor\",\n    \"second_bedroom_temp_sensor\",\n    \"entrance_occupancy\",\n    \"living_room_occupancy\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C06\",\n    \"C17\"\n  ],\n  \"suspected_patterns\": [\n    \"Anomalous temperature scaling: Sensor values range from ~2200 to ~2560, likely representing scaled Celsius (e.g., x10 or raw integer encoding), indicating a potential heating event rather than ambient cooling.\",\n    \"Occupancy-Heat Correlation: High occupancy in living room and master bedroom coincides with peak temperature readings (Chunks C05-C10).\",\n    \"Nighttime Activity Anomaly: Occupancy sensors trigger repeatedly after 21:00 (Chunks C20-C22) when typical residential activity subsides.\",\n    \"Device State Transition: Living room AC switched OFF at 22:21 while occupancy remains high, suggesting manual override or system failure.\"\n  ],\n  \"why_these_chunks\": [\n    \"C02-C04: Show the initial rapid rise in temperature values across all rooms, establishing the baseline of the anomaly.\",\n    \"C05-C06: Capture the peak temperature period and correlate it with specific occupancy events in the bedrooms.\",\n    \"C17: Contains critical device state changes (AC turning off) amidst continued high temperatures and occupancy, indicating a potential safety hazard escalation.\",\n    \"C20-C22: Highlight unusual late-night human presence which could imply unauthorized entry or abnormal household behavior.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The house is empty with sensors reporting baseline ambient temperatures (scaled by x10) and no human activity.\",\n      \"evidence\": [\"Occupancy sensors reported '0' for all rooms between 03:00 and 06:35.\", \"Temperature values in the 2300-2400 range are consistent with a stable indoor environment if scaled Celsius (~23-24°C).\"],\n      \"weaknesses\": [\"Fails to account for the sudden spike in occupancy at 06:35 in the master bedroom.\", \"Cannot explain the rapid temperature increase observed after 06:40 coinciding with cooking events.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Unauthorized intrusion followed by a fire or extreme he"}}
{"episode_id": "SQ4_TP_B_0722", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq4\\SQ4_TP_B_0722.json", "metadata": {"sq_type": "SQ4", "sq_name": "复合安全推理", "variant": "TP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "young_professional", "base_date": "2026-06-22T00:00:00", "seed": 20261351, "scenario_id": "BA-01", "total_events": 1665, "anomaly_events_count": 5}, "ground_truth": {"scenario_id": "BA-01", "scenario_name": "深夜异常多房间活动", "category": "behavioral_anomaly", "is_anomaly": true, "threat_type": "behavioral_anomaly", "key_evidence": ["凌晨2:30-2:40短时间内多房间连续活动", "活动轨迹：客厅→厨房→玄关（像在搜索什么）", "卧室全程无活动（住户在睡觉），这些活动不是住户产生的", "注意区分：如果卧室先有活动再到其他房间，则可能是住户起夜"], "expected_response": "高优先级入侵警报", "difficulty_score": 11, "difficulty_level": 3, "difficulty_label": "L3_composite_reasoning", "difficulty_dimensions": {"D1_evidence_count": 3, "D2_signal_directness": 2, "D3_cross_device": 3, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "kitchen", "injection_time": "2026-06-22T07:48:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"All temperature sensors are reporting physically impossible values (2261-2499) due to a critical calibration failure or unit scaling error, rendering thermal safety data invalid.\",\n  \"reasoning\": [\n      \"The reported temperature readings range from approximately 2261 to 2500, which is physically impossible for ambient air temperature in standard units (Celsius max ~35, Kelvin max ~373).\",\n      \"Data analysis reveals a linear drift pattern over time (e.g., living room sensor increasing from 2261 to 2498 over 6 hours), characteristic of a raw counter overflow, ADC fault, or missing decimal point scaling rather than actual thermal changes.\",\n      \"Despite occupancy events and lighting activation (which should cause minor thermal fluctuations), the sensor values continue their erratic upward trend without stabilizing at realistic levels, confirming a hardware or firmware logic failure.\"\n    ],\n  \"key_evidence\": [\n      \"Timestamped logs show consistent integer values >2200 across all sensors (living_room, master_bedroom, second_bedroom, kitchen) throughout the monitoring period.\",\n      \"The values exhibit a smooth, linear increase (drift) inconsistent with real-world thermal physics, suggesting a software conversion bug or sensor stuck state.\"\n    ],\n  \"recommended_actions\": [\n      \"Immediately flag the entire temperature monitoring system as 'UNRELIABLE' and disable any automation rules dependent on these values.\",\n      \"Contact hardware vendor or IT support to verify firmware version and check for recent updates that may have introduced a scaling regression.\",\n      \"Perform physical verification using independent manual thermometers to confirm environmental conditions before re-enabling automated alerts.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "All temperature sensors are reporting physically impossible values (2261-2499) due to a critical calibration failure or unit scaling error, rendering thermal safety data invalid.", "reasoning": ["The reported temperature readings range from approximately 2261 to 2500, which is physically impossible for ambient air temperature in standard units (Celsius max ~35, Kelvin max ~373).", "Data analysis reveals a linear drift pattern over time (e.g., living room sensor increasing from 2261 to 2498 over 6 hours), characteristic of a raw counter overflow, ADC fault, or missing decimal point scaling rather than actual thermal changes.", "Despite occupancy events and lighting activation (which should cause minor thermal fluctuations), the sensor values continue their erratic upward trend without stabilizing at realistic levels, confirming a hardware or firmware logic failure."], "key_evidence": ["Timestamped logs show consistent integer values >2200 across all sensors (living_room, master_bedroom, second_bedroom, kitchen) throughout the monitoring period.", "The values exhibit a smooth, linear increase (drift) inconsistent with real-world thermal physics, suggesting a software conversion bug or sensor stuck state."], "recommended_actions": ["Immediately flag the entire temperature monitoring system as 'UNRELIABLE' and disable any automation rules dependent on these values.", "Contact hardware vendor or IT support to verify firmware version and check for recent updates that may have introduced a scaling regression.", "Perform physical verification using independent manual thermometers to confirm environmental conditions before re-enabling automated alerts."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 67.56038999557495, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1665, "chunk_count": 21, "signals": {"room_activity": {"living_room": 404, "master_bedroom": 336, "second_bedroom": 336, "kitchen": 299, "bathroom": 58, "entrance": 232}, "attribute_frequency": {"MeasuredValue": 1154, "Occupancy": 480, "OnOff": 16, "StateValue": 5, "LockState": 4, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 4, "occupancy_events": 480, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"living_room\", \"kitchen\", \"master_bedroom\", \"second_bedroom\"],\n  \"focus_devices\": [\"living_room_temp_sensor\", \"master_bedroom_temp_sensor\", \"second_bedroom_temp_sensor\", \"kitchen_temp_sensor\", \"entrance_occupancy\", \"living_room_occupancy\", \"bathroom_occupancy\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\", \"C05\", \"C06\", \"C07\", \"C08\", \"C09\", \"C10\", \"C11\", \"C12\", \"C13\", \"C14\", \"C15\", \"C16\", \"C17\", \"C18\", \"C19\", \"C20\"],\n  \"suspected_patterns\": [\n    \"Anomalous temperature readings (e.g., 2261, 2578) likely representing raw sensor values or scaled data rather than Celsius/Kelvin, indicating a need for unit calibration or firmware review.\",\n    \"Persistent occupancy in living areas and entrance throughout the day suggests active monitoring of routine movement patterns.\",\n    \"Sudden spike in 'alarmish_count' during evening hours (C15-C18) coinciding with kitchen activity and high occupancy requires correlation with appliance logs.\",\n    \"Discrepancy between high room event counts and specific device top-lists implies potential sensor polling loops or network latency issues.\"\n  ],\n  \"why_these_chunks\": [\n    \"All chunks are required to establish the full temporal baseline for temperature drift analysis across the 24-hour cycle.\",\n    \"Early chunks (C00-C02) show initial system states and the first occurrences of anomalous temperature values.\",\n    \"Mid-to-late chunks (C15-C18) exhibit the highest 'alarmish_count', suggesting potential safety triggers or sensor faults that must be correlated with occupancy events.\",\n    \"The entire sequence is necessary to verify if the 'lock_state_flips' mentioned in deterministic signals correlate with entrance occupancy changes.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["living_room", "kitchen", "master_bedroom", "second_bedroom"], "focus_devices": ["living_room_temp_sensor", "master_bedroom_temp_sensor", "second_bedroom_temp_sensor", "kitchen_temp_sensor", "entrance_occupancy", "living_room_occupancy", "bathroom_occupancy"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04", "C05", "C06", "C07", "C08", "C09", "C10", "C11", "C12", "C13", "C14", "C15", "C16", "C17", "C18", "C19", "C20"], "suspected_patterns": ["Anomalous temperature readings (e.g., 2261, 2578) likely representing raw sensor values or scaled data rather than Celsius/Kelvin, indicating a need for unit calibration or firmware review.", "Persistent occupancy in living areas and entrance throughout the day suggests active monitoring of routine movement patterns.", "Sudden spike in 'alarmish_count' during evening hours (C15-C18) coinciding with kitchen activity and high occupancy requires correlation with appliance logs.", "Discrepancy between high room event counts and specific device top-lists implies potential sensor polling loops or network latency issues."], "why_these_chunks": ["All chunks are required to establish the full temporal baseline for temperature drift analysis across the 24-hour cycle.", "Early chunks (C00-C02) show initial system states and the first occurrences of anomalous temperature values.", "Mid-to-late chunks (C15-C18) exhibit the highest 'alarmish_count', suggesting potential safety triggers or sensor faults that must be correlated with occupancy events.", "The entire sequence is necessary to verify if the 'lock_state_flips' mentioned in deterministic signals correlate with entrance occupancy changes."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The system is experiencing a global firmware scaling error where temperature readings are multiplied by approximately 10 (e.g., 23°C stored as 2300). The values fluctuate realistically within a home environment range (-5 to +35 scaled) despite the raw numbers appearing extreme.\",\n      \"evidence\": [\"All temperature sensors show consistent, plausible gradients (e.g., kitchen rising faster than bedrooms due to activity/lighting).\", \"Values remain relatively stable and correlated across different rooms over time, indicating a systematic sensor or software issue rather than chaotic noise.\", \"Occupancy events (lights turning on in living room/kitchen/bathroom) coincide with slight local temperature spikes, suggesting real thermal generation if the unit were correct.\"],\n      \"weaknesses\": [\"A safety-critical system should not output raw integers that look like '2500' degrees without immediate normalization logic. If downstream alarms use these raw values, they would trigger false positives indefinitely.\", \"No log entries explicitly mention a 'unit conversion' event or a reboot that might have triggered this default behavior.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Critical Sensor Failure / Calibration Loss: The temperature sensors have lost their calibration or unit configuration, reporting absolute millikelvin or arbitrary integer counts instead of Celsius. This renders all thermal safety data invalid.\",\n      \"threat_type\": \"False Negative Safety Risk (Thermal)\",\n      \"evidence\": [\"Readings consistently exceed 2400-2500, which is physically impossible for ambient air temperature in Kelvin (absolute zero is 0K, boiling point is ~373K) or Celsius.\", \"The magnitude of values (2500) suggests a loss of decimal scaling or an overflow from a different measurement type (e.g., mV converted incorrectly).\", \"Despite high occupancy and light usage (C02-C04), temperatures do not stabilize at expected levels (e.g., >20°C); instead, they drift upwards linearly, indicating the sensor is no longer measuring heat but perhaps counting cycles or drifting voltage without offset correction.\"],\n      \"weaknesses\": [\"Could be mitigated if the smart home hub has a fallback heuristic based on occupancy history, though none is visible in the logs.\", \"If the sensors are actually measuring something else (like a proprietary heat index algorithm), the logic is undocumented and risky.\"]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Environmental Hazard: The house is genuinely overheating to lethal levels (>2400°C), implying a catastrophic fire or industrial accident has occurred inside the walls, undetected by humans until structural failure.\",\n      \"threat_type\": \"Physical Catastrophe\",\n      \"evidence\": [\"Raw values reach 2500+ (if interpreted literally).\", \"Continuous upward trend even during low-occupancy periods (00:00 - 06:00) suggests an external heat source rather than internal human activity.\"],\n      \"weaknesses\": [\"Highly implausible given the stability of the reading pattern; fires cause erratic spikes, not smooth linear drifts.\", \"If it were a fire, smoke detectors or other emergency systems would likely be triggered or logged, which are absent.\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The linear progression of values (e.g., Living Room going from 2261 to 2491 over 6 hours) perfectly matches the mathematical slope of a counter or a faulty ADC reading, whereas a real thermal event would show exponential decay/growth or step changes.\",\n    \"The correlation between 'OnOff' events (lights) and minor value shifts suggests the device is reacting to environmental changes, proving it is 'on', but the scale is wrong.\",\n    \"Absence of any 'SystemMode' change or 'Alarm' state flip in the structured signals despite the temperature crossing any reasonable threshold.\"\n  ],\n  \"missing_information\": [\n    \"The specific protocol used (MQTT payload schema) to determine if the value is raw integer, float, or encoded.\",\n    \"Historical baseline: What were the last known good values before June 22?\",\n    \"Firmware version and recent update logs to rule out a regression bug introduced recently.\",\n    \"Status of Smoke/Carbon Monoxide detectors, as thermal anomalies often correlate with combustion hazards.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The system is experiencing a global firmware scaling error where temperature readings are multiplied by approximately 10 (e.g., 23°C stored as 2300). The values fluctuate realistically within a home environment range (-5 to +35 scaled) despite the raw numbers appearing extreme.", "evidence": ["All temperature sensors show consistent, plausible gradients (e.g., kitchen rising faster than bedrooms due to activity/lighting).", "Values remain relatively stable and correlated across different rooms over time, indicating a systematic sensor or software issue rather than chaotic noise.", "Occupancy events (lights turning on in living room/kitchen/bathroom) coincide with slight local temperature spikes, suggesting real thermal generation if the unit were correct."], "weaknesses": ["A safety-critical system should not output raw integers that look like '2500' degrees without immediate normalization logic. If downstream alarms use these raw values, they would trigger false positives indefinitely.", "No log entries explicitly mention a 'unit conversion' event or a reboot that might have triggered this default behavior."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Critical Sensor Failure / Calibration Loss: The temperature sensors have lost their calibration or unit configuration, reporting absolute millikelvin or arbitrary integer counts instead of Celsius. This renders all thermal safety data invalid.", "threat_type": "False Negative Safety Risk (Thermal)", "evidence": ["Readings consistently exceed 2400-2500, which is physically impossible for ambient air temperature in Kelvin (absolute zero is 0K, boiling point is ~373K) or Celsius.", "The magnitude of values (2500) suggests a loss of decimal scaling or an overflow from a different measurement type (e.g., mV converted incorrectly).", "Despite high occupancy and light usage (C02-C04), temperatures do not stabilize at expected levels (e.g., >20°C); instead, they drift upwards linearly, indicating the sensor is no longer measuring heat but perhaps counting cycles or drifting voltage without offset correction."], "weaknesses": ["Could be mitigated if the smart home hub has a fallback heuristic based on occupancy history, though none is visible in the logs.", "If the sensors are actually measuring something else (like a proprietary heat index algorithm), the logic is undocumented and risky."]}, {"id": "A2", "description": "Environmental Hazard: The house is genuinely overheating to lethal levels (>2400°C), implying a catastrophic fire or industrial accident has occurred inside the walls, undetected by humans until structural failure.", "threat_type": "Physical Catastrophe", "evidence": ["Raw values reach 2500+ (if interpreted literally).", "Continuous upward trend even during low-occupancy periods (00:00 - 06:00) suggests an external heat source rather than internal human activity."], "weaknesses": ["Highly implausible given the stability of the reading pattern; fires cause erratic spikes, not smooth linear drifts.", "If it were a fire, smoke detectors or other emergency systems would likely be triggered or logged, which are absent."]}], "most_discriminative_evidence": ["The linear progression of values (e.g., Living Room going from 2261 to 2491 over 6 hours) perfectly matches the mathematical slope of a counter or a faulty ADC reading, whereas a real thermal event would show exponential decay/growth or step changes.", "The correlation between 'OnOff' events (lights) and minor value shifts suggests the device is reacting to environmental changes, proving it is 'on', but the scale is wrong.", "Absence of any 'SystemMode' change or 'Alarm' state flip in the structured signals despite the temperature crossing any reasonable threshold."], "missing_information": ["The specific protocol used (MQTT payload schema) to determine if the value is raw integer, float, or encoded.", "Historical baseline: What were the last known good values before June 22?", "Firmware version and recent update logs to rule out a regression bug introduced recently.", "Status of Smoke/Carbon Monoxide detectors, as thermal anomalies often correlate with combustion hazards."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [],\n  \"missing_checks\": [\n    \"Verify Smoke/CO detector status logs (explicitly requested in missing information).\",\n    \"Check historical baseline data prior to June 22 to confirm if values were previously normal.\",\n    \"Retrieve Firmware version and update changelogs to investigate scaling regression bugs.\",\n    \"Cross-reference 'alarmish_count' spikes with specific appliance power logs to rule out false positives from cooking activities.\"\n  ],\n  \"supervisor_notes\": [\n    \"The investigation has correctly identified the primary anomaly: temperature sensor calibration/scaling issues leading to impossible readings (~2500).\",\n    \"However, the current evidence is insufficient to fully assess 'safety status' as requested by the query. The analysis focuses heavily on thermal sensors but ignores critical safety systems mentioned in the triage (Smoke/CO detectors).\",\n    \"We must verify if the system failed silently regarding other hazards or if the thermal anomaly is the only issue.\",\n    \"Historical context (baseline) and firmware history are explicitly missing and necessary to determine if this is a new failure mode or a long-standing bug.\",\n    \"No additional chunk IDs need to be retrieved since all 21 chunks (C00-C20) have already been processed by the investigator.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": [], "missing_checks": ["Verify Smoke/CO detector status logs (explicitly requested in missing information).", "Check historical baseline data prior to June 22 to confirm if values were previously normal.", "Retrieve Firmware version and update changelogs to investigate scaling regression bugs.", "Cross-reference 'alarmish_count' spikes with specific appliance power logs to rule out false positives from cooking activities."], "supervisor_notes": ["The investigation has correctly identified the primary anomaly: temperature sensor calibration/scaling issues leading to impossible readings (~2500).", "However, the current evidence is insufficient to fully assess 'safety status' as requested by the query. The analysis focuses heavily on thermal sensors but ignores critical safety systems mentioned in the triage (Smoke/CO detectors).", "We must verify if the system failed silently regarding other hazards or if the thermal anomaly is the only issue.", "Historical context (baseline) and firmware history are explicitly missing and necessary to determine if this is a new failure mode or a long-standing bug.", "No additional chunk IDs need to be retrieved since all 21 chunks (C00-C20) have already been processed by the investigator."]}, "preview_triage_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 404,\n    \"master_bedroom\": 336,\n    \"second_bedroom\": 336,\n    \"kitchen\": 299,\n    \"bathroom\": 58,\n    \"entrance\": 232\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1154,\n    \"Occupancy\": 480,\n    \"OnOff\": 16,\n    \"StateValue\": 5,\n    \"LockState\": 4,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 480,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-22T00:00:00\",\n    \"end_ts\": \"2026-06-22T01:20:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 20,\n      \"master_bedroom\": 19,\n      \"second_bedroom\": 19,\n      \"kitchen\": 16,\n      \"bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"master_bedroom_occupancy\"\n    ],\n    \"alarmish_count\": 15,\n    \"preview_lines\": [\n      \"[2026-06-22T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2261\",\n      \"[2026-06-22T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2264\",\n      \"[2026-06-22T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2280\",\n      \"[2026-06-22T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2270\",\n      \"[2026-06-22T00:00:00] living_room_occupancy | OccupancySensing.", "preview_verifier_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"living_room\", \"kitchen\", \"master_bedroom\", \"second_bedroom\"],\n  \"focus_devices\": [\"living_room_temp_sensor\", \"master_bedroom_temp_sensor\", \"second_bedroom_temp_sensor\", \"kitchen_temp_sensor\", \"entrance_occupancy\", \"living_room_occupancy\", \"bathroom_occupancy\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\", \"C05\", \"C06\", \"C07\", \"C08\", \"C09\", \"C10\", \"C11\", \"C12\", \"C13\", \"C14\", \"C15\", \"C16\", \"C17\", \"C18\", \"C19\", \"C20\"],\n  \"suspected_patterns\": [\n    \"Anomalous temperature readings (e.g., 2261, 2578) likely representing raw sensor values or scaled data rather than Celsius/Kelvin, indicating a need for unit calibration or firmware review.\",\n    \"Persistent occupancy in living areas and entrance throughout the day suggests active monitoring of routine movement patterns.\",\n    \"Sudden spike in 'alarmish_count' during evening hours (C15-C18) coinciding with kitchen activity and high occupancy requires correlation with appliance logs.\",\n    \"Discrepancy between high room event counts and specific device top-lists implies potential sensor polling loops or network latency issues.\"\n  ],\n  \"why_these_chunks\": [\n    \"All chunks are required to establish the full temporal baseline for temperature drift analysis across the 24-hour cycle.\",\n    \"Early chunks (C00-C02) show initial system states and the first occurrences of anomalous temperature values.\",\n    \"Mid-to-late chunks (C15-C18) exhibit the highest 'alarmish_count', suggesting potential safety triggers or sensor faults that must be correlated with occupancy events.\",\n    \"The entire sequence is necessary to verify if the 'lock_state_flips' mentioned in deterministic signals correlate with entrance occupancy changes.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The system is experiencing a global firmware scaling error where temperature readings are multiplied by approximately 10 (e.g., 23°C stored as 2300). The values fluctuate realistically within a home environment range (-5 to +35 scaled) despite the raw numbers appearing extreme.\",\n      \"evidence\": [\"All temperature sensors show consistent, plausible gradients (e.g., kitchen rising faster than bedrooms due to activity/lighting).\", \"Values remain relatively stable and correlated across different rooms over time, indicating a systematic sensor or software issue rather "}}
{"episode_id": "SQ4_TP_B_0768", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq4\\SQ4_TP_B_0768.json", "metadata": {"sq_type": "SQ4", "sq_name": "复合安全推理", "variant": "TP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "family_with_children", "base_date": "2026-06-23T00:00:00", "seed": 20261397, "scenario_id": "BA-03", "total_events": 1840, "anomaly_events_count": 7}, "ground_truth": {"scenario_id": "BA-03", "scenario_name": "异常高频设备交互", "category": "behavioral_anomaly", "is_anomaly": true, "threat_type": "behavioral_anomaly", "key_evidence": ["1分钟内多次灯光开关", "可能原因：智能家居系统被入侵/远程控制；设备自动化规则冲突；或电路问题", "也可能是恐慌信号（住户通过反复开关灯试图引起注意）"], "expected_response": "通知住户检查是否有人误操作或系统异常", "difficulty_score": 10, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 3, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "kitchen", "injection_time": "2026-06-23T17:26:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"All temperature sensors are reporting physically impossible values (2300-2500+) indicative of a global calibration failure or data corruption rather than an actual fire, as the house structure would fail long before reaching such temperatures.\",\n  \"reasoning\": [\n    \"Temperature readings across all rooms consistently exceed 2000°C (e.g., 2400-2559), which is physically impossible for indoor air; even steel melts around 1370°C, meaning the house would be destroyed if these were real measurements.\",\n    \"Despite the 'extreme' heat readings, occupancy logs show residents moving normally between rooms (master_bedroom_occupancy = 1) and interacting with devices (lights on/off), which would not occur in a lethal environment.\",\n    \"The kitchen cooking surface was turned ON at 06:59:36, and while this triggered the start of the anomalous readings, the subsequent rise to >2500 without any corresponding smoke detector triggers or sensor failures (until one specific kitchen sensor hit 'None') suggests the entire stream is corrupted or misinterpreted raw counts (likely Kelvin vs Celsius confusion or integer overflow).\",\n    \"No other safety systems (smoke/CO) have been triggered, and the system has not entered a critical shutdown state until very late in the timeline, indicating the central logic does not recognize these numbers as fire events.\"\n  ],\n  \"key_evidence\": [\n    \"kitchen_temp_sensor reading dropped to 'None' at 07:00:06 while other sensors continued reporting high integers, suggesting localized component saturation or buffer overflow rather than uniform environmental destruction.\",\n    \"Occupancy flags remained active (1) in the master bedroom during periods where temperatures peaked above 2500, proving the environment was habitable.\",\n    \"Front door lock operations and light toggles occurred normally throughout the event, confirming human activity consistent with a non-emergency state.\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately reset all temperature sensors and check firmware for scaling errors (Kelvin vs. Celsius) or calibration drift.\",\n    \"Verify physical temperature using an independent handheld thermometer to confirm no actual fire exists.\",\n    \"Inspect the kitchen area visually for any signs of overheating or damage caused by the faulty sensor triggering unnecessary alarms or user panic.\",\n    \"Review network logs to rule out potential data injection attacks if the malfunction persists after hardware reset.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "All temperature sensors are reporting physically impossible values (2300-2500+) indicative of a global calibration failure or data corruption rather than an actual fire, as the house structure would fail long before reaching such temperatures.", "reasoning": ["Temperature readings across all rooms consistently exceed 2000°C (e.g., 2400-2559), which is physically impossible for indoor air; even steel melts around 1370°C, meaning the house would be destroyed if these were real measurements.", "Despite the 'extreme' heat readings, occupancy logs show residents moving normally between rooms (master_bedroom_occupancy = 1) and interacting with devices (lights on/off), which would not occur in a lethal environment.", "The kitchen cooking surface was turned ON at 06:59:36, and while this triggered the start of the anomalous readings, the subsequent rise to >2500 without any corresponding smoke detector triggers or sensor failures (until one specific kitchen sensor hit 'None') suggests the entire stream is corrupted or misinterpreted raw counts (likely Kelvin vs Celsius confusion or integer overflow).", "No other safety systems (smoke/CO) have been triggered, and the system has not entered a critical shutdown state until very late in the timeline, indicating the central logic does not recognize these numbers as fire events."], "key_evidence": ["kitchen_temp_sensor reading dropped to 'None' at 07:00:06 while other sensors continued reporting high integers, suggesting localized component saturation or buffer overflow rather than uniform environmental destruction.", "Occupancy flags remained active (1) in the master bedroom during periods where temperatures peaked above 2500, proving the environment was habitable.", "Front door lock operations and light toggles occurred normally throughout the event, confirming human activity consistent with a non-emergency state."], "recommended_actions": ["Immediately reset all temperature sensors and check firmware for scaling errors (Kelvin vs. Celsius) or calibration drift.", "Verify physical temperature using an independent handheld thermometer to confirm no actual fire exists.", "Inspect the kitchen area visually for any signs of overheating or damage caused by the faulty sensor triggering unnecessary alarms or user panic.", "Review network logs to rule out potential data injection attacks if the malfunction persists after hardware reset."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 74.59533309936523, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1840, "chunk_count": 23, "signals": {"room_activity": {"living_room": 407, "master_bedroom": 517, "second_bedroom": 336, "kitchen": 303, "bathroom": 48, "entrance": 229}, "attribute_frequency": {"MeasuredValue": 1156, "Occupancy": 642, "OnOff": 22, "StateValue": 7, "LockState": 5, "SystemMode": 1, "OperationalState": 1, "CurrentPositionLiftPercent100ths": 1}, "lock_state_flips": 5, "occupancy_events": 642, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\", \"master_bedroom\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"living_room_temp_sensor\", \"master_bedroom_temp_sensor\", \"kitchen_cook_surface\", \"entrance_occupancy\", \"master_bedroom_occupancy\"],\n  \"focus_chunk_ids\": [\"C02\", \"C03\", \"C04\", \"C05\", \"C06\", \"C17\", \"C18\"],\n  \"suspected_patterns\": [\n    \"Temperature values (e.g., 2273, 2559) are in Kelvin scale (~20°C - 228°C), not Celsius. If interpreted as °C, this indicates a critical sensor failure or data corruption.\",\n    \"High frequency of occupancy events ('flip-flop' pattern) at the entrance and living room suggests potential sensor instability or repeated short visits by individuals/animals.\",\n    \"Late-night activity detected in the master bedroom while other sensors show low activity.\"\n  ],\n  \"why_these_chunks\": [\n    \"C02-C04: Show the steepest rise in temperature readings across all rooms, which is suspicious if the unit is Celsius; otherwise, it's normal diurnal heating but requires validation against expected ranges.\",\n    \"C05-C06: Critical period where high temperatures coincide with the first confirmed human occupancy events in the master bedroom after a long absence.\",\n    \"C17-C18: The only chunks showing active cooking surface usage ('OnOff = True') late at night (18:46, 19:30), which combined with the elevated temperature readings creates a potential fire safety risk scenario.\",\n    \"Throughout C00-C01: Baseline establishment showing 'alarmish_count' spikes without corresponding physical event logs, hinting at system noise or calibration drift that needs correlation with the later active events.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "living_room", "master_bedroom"], "focus_devices": ["kitchen_temp_sensor", "living_room_temp_sensor", "master_bedroom_temp_sensor", "kitchen_cook_surface", "entrance_occupancy", "master_bedroom_occupancy"], "focus_chunk_ids": ["C02", "C03", "C04", "C05", "C06", "C17", "C18"], "suspected_patterns": ["Temperature values (e.g., 2273, 2559) are in Kelvin scale (~20°C - 228°C), not Celsius. If interpreted as °C, this indicates a critical sensor failure or data corruption.", "High frequency of occupancy events ('flip-flop' pattern) at the entrance and living room suggests potential sensor instability or repeated short visits by individuals/animals.", "Late-night activity detected in the master bedroom while other sensors show low activity."], "why_these_chunks": ["C02-C04: Show the steepest rise in temperature readings across all rooms, which is suspicious if the unit is Celsius; otherwise, it's normal diurnal heating but requires validation against expected ranges.", "C05-C06: Critical period where high temperatures coincide with the first confirmed human occupancy events in the master bedroom after a long absence.", "C17-C18: The only chunks showing active cooking surface usage ('OnOff = True') late at night (18:46, 19:30), which combined with the elevated temperature readings creates a potential fire safety risk scenario.", "Throughout C00-C01: Baseline establishment showing 'alarmish_count' spikes without corresponding physical event logs, hinting at system noise or calibration drift that needs correlation with the later active events."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The entire house is experiencing a severe sensor calibration failure or firmware bug where all temperature readings are erroneously multiplied by a factor of ~10 (reporting Kelvin values like 2400K instead of Celsius). The system has no actual fire hazard.\",\n      \"evidence\": [\"All temperature values across all rooms consistently fall between 2340 and 2547, which corresponds to physical temperatures of ~2000°C to ~2270°C if interpreted as Celsius, but ~20°C to ~2300K (physical ~1700°C) if interpreted as Kelvin. However, the *relative* stability and gradual drift suggest a scaling error rather than chaotic noise.\", \"Occupancy events show logical human patterns: lights turn on/off, doors lock/unlock in sequence (C05-C06), and occupancy flags flip realistically (0 to 1).\", \"No alarm triggers occurred during the period despite the 'alarmish_count' spike mentioned in the triage output, suggesting the logic layer filtered out the data corruption.\"],\n      \"weaknesses\": [\"If the values were truly Kelvin, 2400K (~2127°C) is physically impossible for indoor air; the sensors would melt long before reporting this. Therefore, the unit is likely Celsius, making the absolute values physically impossible unless there is an active fire consuming the house structure itself, which contradicts the lack of visible smoke/damage logs.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Active Class A/B Fire Event: An uncontrolled fire is burning within the residence, causing extreme heat that exceeds standard sensor ranges, resulting in saturation or overflow values reported as high integers. The 'None' readings indicate sensor burnout.\",\n      \"threat_type\": \"Fire Safety / Structural Integrity\",\n      \"evidence\": [\"Temperature readings escalate from ~2340 to >2500 over a 6-hour period. If these are raw counts proportional to temperature, they indicate rising thermal energy.\", \"At 07:00:06 and 07:03:00, `kitchen_temp_sensor` returns `None`, indicating total sensor failure due to extreme heat or power loss.\", \"Kitchen cooking surface was turned ON at 06:59:36. While late-night cooking is risky, the subsequent temperature escalation and sensor failure point beyond simple overheating.\", \"Multiple `entrance_occupancy` spikes (07:28, 07:33, etc.) combined with door locking suggests residents are attempting to secure the perimeter or evacuate, though the timing relative to peak temps is ambiguous.\"],\n      \"weaknesses\": [\"The timeline shows occupancy occurring *after* temperatures hit critical levels. Residents entering a room with 2000°C+ air would result in immediate detection via motion sensors failing due to heat haze or direct exposure, yet occupancy is logged clearly until the very end.\", \"No other environmental signals (smoke detectors, CO sensors, window contact breaches indicating forced entry) are explicitly linked to the fire event in the provided chunks, only temperature and occupancy.\"]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Data Corruption / Injection Attack: The temperature stream has been artificially manipulated or corrupted by a network intrusion, creating a false narrative of a fire to trigger panic or bypass security protocols.\",\n      \"threat_type\": \"Cyber Security / False Alarm\",\n      \"evidence\": [\"The correlation between specific timestamps and the 'high' numbers is too perfect across disparate sensors without corresponding local heat source logs.\", \"The `temperature_patterns` array in structured signals is empty, implying the system flagged the data series as invalid or anomalous internally.\", \"Sensor failure (`None`) occurs exactly when the numeric value would be highest, consistent with a buffer overflow caused by injected data.\"],\n      \"weaknesses\": [\"In a real attack, one might expect randomized noise or inconsistent patterns across sensors. Here, all sensors rise in unison, which mimics a physical phenomenon more closely than random injection.\", \"The presence of legitimate device events (locks, lights, cooktops) interspersed with the bad data suggests the attacker has partial access, not total control, making a complete fabrication difficult.\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The transition of `kitchen_temp_sensor` to `None` at 07:00:06 while other sensors still report high integer values suggests either a localized component failure (burnout) or a deliberate cutoff in a corrupted stream.\",\n    \"The specific timestamp `2026-06-23T06:59:36` for `kitchen_cook_surface` turning ON coincides with the start of the steep temperature ascent, creating a plausible causal link for a kitchen fire scenario if the values represent valid heat accumulation.\",\n    \"The complete absence of any 'SmokeDetected' or 'FireAlarmTriggered' events in the logs, despite temperatures exceeding realistic limits, implies the safety logic is either blind to the temperature anomaly or the anomaly is being misinterpreted as non-critical.\"\n  ],\n  \"missing_information\": [\n    \"Actual temperature units (Celsius vs. Fahrenheit vs. Raw Counts) defined in the schema.\",\n    \"Logs from Smoke/CO detectors and Water Leak sensors to confirm or deny fire/water damage.\",\n    \"Camera footage or audio logs to verify if occupants are fleeing, hiding, or interacting normally with the environment.\",\n    \"Historical baseline temperature data to determine if the current 'baseline' of 2300 is already abnormal for this specific hardware setup.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The entire house is experiencing a severe sensor calibration failure or firmware bug where all temperature readings are erroneously multiplied by a factor of ~10 (reporting Kelvin values like 2400K instead of Celsius). The system has no actual fire hazard.", "evidence": ["All temperature values across all rooms consistently fall between 2340 and 2547, which corresponds to physical temperatures of ~2000°C to ~2270°C if interpreted as Celsius, but ~20°C to ~2300K (physical ~1700°C) if interpreted as Kelvin. However, the *relative* stability and gradual drift suggest a scaling error rather than chaotic noise.", "Occupancy events show logical human patterns: lights turn on/off, doors lock/unlock in sequence (C05-C06), and occupancy flags flip realistically (0 to 1).", "No alarm triggers occurred during the period despite the 'alarmish_count' spike mentioned in the triage output, suggesting the logic layer filtered out the data corruption."], "weaknesses": ["If the values were truly Kelvin, 2400K (~2127°C) is physically impossible for indoor air; the sensors would melt long before reporting this. Therefore, the unit is likely Celsius, making the absolute values physically impossible unless there is an active fire consuming the house structure itself, which contradicts the lack of visible smoke/damage logs."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Active Class A/B Fire Event: An uncontrolled fire is burning within the residence, causing extreme heat that exceeds standard sensor ranges, resulting in saturation or overflow values reported as high integers. The 'None' readings indicate sensor burnout.", "threat_type": "Fire Safety / Structural Integrity", "evidence": ["Temperature readings escalate from ~2340 to >2500 over a 6-hour period. If these are raw counts proportional to temperature, they indicate rising thermal energy.", "At 07:00:06 and 07:03:00, `kitchen_temp_sensor` returns `None`, indicating total sensor failure due to extreme heat or power loss.", "Kitchen cooking surface was turned ON at 06:59:36. While late-night cooking is risky, the subsequent temperature escalation and sensor failure point beyond simple overheating.", "Multiple `entrance_occupancy` spikes (07:28, 07:33, etc.) combined with door locking suggests residents are attempting to secure the perimeter or evacuate, though the timing relative to peak temps is ambiguous."], "weaknesses": ["The timeline shows occupancy occurring *after* temperatures hit critical levels. Residents entering a room with 2000°C+ air would result in immediate detection via motion sensors failing due to heat haze or direct exposure, yet occupancy is logged clearly until the very end.", "No other environmental signals (smoke detectors, CO sensors, window contact breaches indicating forced entry) are explicitly linked to the fire event in the provided chunks, only temperature and occupancy."]}, {"id": "A2", "description": "Data Corruption / Injection Attack: The temperature stream has been artificially manipulated or corrupted by a network intrusion, creating a false narrative of a fire to trigger panic or bypass security protocols.", "threat_type": "Cyber Security / False Alarm", "evidence": ["The correlation between specific timestamps and the 'high' numbers is too perfect across disparate sensors without corresponding local heat source logs.", "The `temperature_patterns` array in structured signals is empty, implying the system flagged the data series as invalid or anomalous internally.", "Sensor failure (`None`) occurs exactly when the numeric value would be highest, consistent with a buffer overflow caused by injected data."], "weaknesses": ["In a real attack, one might expect randomized noise or inconsistent patterns across sensors. Here, all sensors rise in unison, which mimics a physical phenomenon more closely than random injection.", "The presence of legitimate device events (locks, lights, cooktops) interspersed with the bad data suggests the attacker has partial access, not total control, making a complete fabrication difficult."]}], "most_discriminative_evidence": ["The transition of `kitchen_temp_sensor` to `None` at 07:00:06 while other sensors still report high integer values suggests either a localized component failure (burnout) or a deliberate cutoff in a corrupted stream.", "The specific timestamp `2026-06-23T06:59:36` for `kitchen_cook_surface` turning ON coincides with the start of the steep temperature ascent, creating a plausible causal link for a kitchen fire scenario if the values represent valid heat accumulation.", "The complete absence of any 'SmokeDetected' or 'FireAlarmTriggered' events in the logs, despite temperatures exceeding realistic limits, implies the safety logic is either blind to the temperature anomaly or the anomaly is being misinterpreted as non-critical."], "missing_information": ["Actual temperature units (Celsius vs. Fahrenheit vs. Raw Counts) defined in the schema.", "Logs from Smoke/CO detectors and Water Leak sensors to confirm or deny fire/water damage.", "Camera footage or audio logs to verify if occupants are fleeing, hiding, or interacting normally with the environment.", "Historical baseline temperature data to determine if the current 'baseline' of 2300 is already abnormal for this specific hardware setup."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C07\", \"C08\", \"C09\", \"C10\"],\n  \"missing_checks\": [\n    \"Verify if high temperature readings correlate with specific fire events in C07-C10.\",\n    \"Check for smoke/CO alarm triggers or sensor failures in subsequent chunks.\",\n    \"Confirm occupancy patterns to determine if residents are evacuating or trapped.\"\n  ],\n  \"supervisor_notes\": [\n    \"The investigation has drifted slightly into speculative hypotheses (cyber attack vs. physical fire) without sufficient empirical data from the mid-to-late timeline (C07-C22).\",\n    \"Critical gaps exist: We need to see what happens after the 'None' reading at C06. Is there a total system shutdown? Do smoke alarms trigger later?\",\n    \"The current evidence relies heavily on extrapolating from the initial spike; we need concrete logs of evacuation attempts, fire suppression activation, or continued sensor degradation in the next set of chunks to validate Anomaly A1.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C07", "C08", "C09", "C10"], "missing_checks": ["Verify if high temperature readings correlate with specific fire events in C07-C10.", "Check for smoke/CO alarm triggers or sensor failures in subsequent chunks.", "Confirm occupancy patterns to determine if residents are evacuating or trapped."], "supervisor_notes": ["The investigation has drifted slightly into speculative hypotheses (cyber attack vs. physical fire) without sufficient empirical data from the mid-to-late timeline (C07-C22).", "Critical gaps exist: We need to see what happens after the 'None' reading at C06. Is there a total system shutdown? Do smoke alarms trigger later?", "The current evidence relies heavily on extrapolating from the initial spike; we need concrete logs of evacuation attempts, fire suppression activation, or continued sensor degradation in the next set of chunks to validate Anomaly A1."]}, "preview_triage_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 407,\n    \"master_bedroom\": 517,\n    \"second_bedroom\": 336,\n    \"kitchen\": 303,\n    \"bathroom\": 48,\n    \"entrance\": 229\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1156,\n    \"Occupancy\": 642,\n    \"OnOff\": 22,\n    \"StateValue\": 7,\n    \"LockState\": 5,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"CurrentPositionLiftPercent100ths\": 1\n  },\n  \"lock_state_flips\": 5,\n  \"occupancy_events\": 642,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-23T00:00:00\",\n    \"end_ts\": \"2026-06-23T01:20:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 20,\n      \"master_bedroom\": 19,\n      \"second_bedroom\": 19,\n      \"kitchen\": 16,\n      \"bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"master_bedroom_occupancy\"\n    ],\n    \"alarmish_count\": 15,\n    \"preview_lines\": [\n      \"[2026-06-23T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2273\",\n      \"[2026-06-23T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2281\",\n      \"[2026-06-23T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2277\",\n      \"[2026-06-23T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2262\",\n      \"[2026-06-23T00:00:00", "preview_verifier_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\", \"master_bedroom\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"living_room_temp_sensor\", \"master_bedroom_temp_sensor\", \"kitchen_cook_surface\", \"entrance_occupancy\", \"master_bedroom_occupancy\"],\n  \"focus_chunk_ids\": [\"C02\", \"C03\", \"C04\", \"C05\", \"C06\", \"C17\", \"C18\"],\n  \"suspected_patterns\": [\n    \"Temperature values (e.g., 2273, 2559) are in Kelvin scale (~20°C - 228°C), not Celsius. If interpreted as °C, this indicates a critical sensor failure or data corruption.\",\n    \"High frequency of occupancy events ('flip-flop' pattern) at the entrance and living room suggests potential sensor instability or repeated short visits by individuals/animals.\",\n    \"Late-night activity detected in the master bedroom while other sensors show low activity.\"\n  ],\n  \"why_these_chunks\": [\n    \"C02-C04: Show the steepest rise in temperature readings across all rooms, which is suspicious if the unit is Celsius; otherwise, it's normal diurnal heating but requires validation against expected ranges.\",\n    \"C05-C06: Critical period where high temperatures coincide with the first confirmed human occupancy events in the master bedroom after a long absence.\",\n    \"C17-C18: The only chunks showing active cooking surface usage ('OnOff = True') late at night (18:46, 19:30), which combined with the elevated temperature readings creates a potential fire safety risk scenario.\",\n    \"Throughout C00-C01: Baseline establishment showing 'alarmish_count' spikes without corresponding physical event logs, hinting at system noise or calibration drift that needs correlation with the later active events.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The entire house is experiencing a severe sensor calibration failure or firmware bug where all temperature readings are erroneously multiplied by a factor of ~10 (reporting Kelvin values like 2400K instead of Celsius). The system has no actual fire hazard.\",\n      \"evidence\": [\"All temperature values across all rooms consistently fall between 2340 and 2547, which corresponds to physical temperatures of ~2000°C to ~2270°C if interpreted as Celsius, but ~20°C to ~2300K (physical ~1700°C) if interpreted as Kelvin. However, the *relative* stability and gradual drift suggest a scaling error rather than chaotic noise.\", \"Occupancy events show logical human "}}
{"episode_id": "SQ4_TP_C_0737", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq4\\SQ4_TP_C_0737.json", "metadata": {"sq_type": "SQ4", "sq_name": "复合安全推理", "variant": "TP", "layout_id": "C", "layout_name": "三室两厅 (3BR)", "profile_id": "family_with_children", "base_date": "2026-06-21T00:00:00", "seed": 20261366, "scenario_id": "CH-01", "total_events": 1492, "anomaly_events_count": 4}, "ground_truth": {"scenario_id": "CH-01", "scenario_name": "儿童独自在家异常", "category": "child_specific", "is_anomaly": true, "threat_type": "child_safety", "key_evidence": ["工作日上午学校时段", "家长已出门（LockOperation 记录）", "仅儿童房有活动信号，其他房间无人", "活动模式像小孩（仅在一个房间）"], "expected_response": "通知家长确认孩子是否生病在家/逃学", "difficulty_score": 10, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 2, "D5_fp_similarity": 2}, "target_room": "balcony", "injection_time": "2026-06-21T21:03:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"The home monitoring system is reporting physically impossible temperature readings (>2000°C) across all sensors due to a critical firmware or data corruption error, posing no immediate environmental fire risk but causing system integrity failure.\",\n  \"reasoning\": [\n    \"All temperature sensors (kitchen, living_room, bedrooms) report values consistently between ~2260 and ~2550, which are physically impossible for any standard indoor residential environment (normal range: -10°C to 50°C).\",\n    \"The anomaly is global and simultaneous, affecting every sensor in the house from the very first timestamp (2026-06-21T00:00:00), indicating a central processing unit, broadcast command, or calibration issue rather than localized heat sources like a fire.\",\n    \"Occupancy sensors confirm the house has been empty (all zeros) throughout the entire incident period, ruling out human activity (cooking, heating) as the cause of the extreme readings.\",\n    \"No other safety systems (smoke alarms, locks, water leaks) show correlated anomalies or state changes, isolating the fault strictly to the temperature measurement logic.\"\n  ],\n  \"key_evidence\": [\n    \"MeasuredValues range from 2262 to 2551 over an 8.5-hour period, far exceeding any known physical limit for indoor air temperature.\",\n    \"Consistency of Invalidity: Every single temperature reading across 8 different rooms contains the same impossible characteristic simultaneously.\",\n    \"Contradictory State: The house is reported as fully unoccupied during the anomalous period, eliminating human activity as the source.\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately reboot the central home automation hub or gateway to reset sensor communication protocols.\",\n    \"Check device logs for firmware errors, buffer overflows, or recent configuration changes that may have triggered the data corruption.\",\n    \"Perform a manual physical inspection of one sensor to verify actual ambient temperature if possible, or replace suspected faulty hardware after reboot.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "The home monitoring system is reporting physically impossible temperature readings (>2000°C) across all sensors due to a critical firmware or data corruption error, posing no immediate environmental fire risk but causing system integrity failure.", "reasoning": ["All temperature sensors (kitchen, living_room, bedrooms) report values consistently between ~2260 and ~2550, which are physically impossible for any standard indoor residential environment (normal range: -10°C to 50°C).", "The anomaly is global and simultaneous, affecting every sensor in the house from the very first timestamp (2026-06-21T00:00:00), indicating a central processing unit, broadcast command, or calibration issue rather than localized heat sources like a fire.", "Occupancy sensors confirm the house has been empty (all zeros) throughout the entire incident period, ruling out human activity (cooking, heating) as the cause of the extreme readings.", "No other safety systems (smoke alarms, locks, water leaks) show correlated anomalies or state changes, isolating the fault strictly to the temperature measurement logic."], "key_evidence": ["MeasuredValues range from 2262 to 2551 over an 8.5-hour period, far exceeding any known physical limit for indoor air temperature.", "Consistency of Invalidity: Every single temperature reading across 8 different rooms contains the same impossible characteristic simultaneously.", "Contradictory State: The house is reported as fully unoccupied during the anomalous period, eliminating human activity as the source."], "recommended_actions": ["Immediately reboot the central home automation hub or gateway to reset sensor communication protocols.", "Check device logs for firmware errors, buffer overflows, or recent configuration changes that may have triggered the data corruption.", "Perform a manual physical inspection of one sensor to verify actual ambient temperature if possible, or replace suspected faulty hardware after reboot."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 56.74982666969299, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1492, "chunk_count": 19, "signals": {"room_activity": {"living_room": 336, "master_bedroom": 336, "kids_room": 338, "kitchen": 288, "dining_room": 48, "second_bedroom": 48, "master_bathroom": 48, "entrance": 50}, "attribute_frequency": {"MeasuredValue": 1152, "Occupancy": 337, "OnOff": 1}, "lock_state_flips": 0, "occupancy_events": 337, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\"],\n  \"focus_devices\": [\"temperature_sensor\", \"smoke_co_alarm\", \"water_leak_detector\", \"cook_surface\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\", \"C05\", \"C06\", \"C07\"],\n  \"suspected_patterns\": [\n    \"Abnormal temperature readings (values > 2000) across all rooms indicating sensor calibration failure or data corruption.\",\n    \"High frequency of 'alarmish' events correlating with temperature spikes, suggesting a potential false alarm cascade due to the faulty sensor data.\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunks C00-C07 contain the initial and most severe temperature anomalies (ranging from ~2278 to ~2553), which are physically impossible for standard indoor environments and indicate a critical system health issue rather than an environmental hazard. These chunks require inspection to determine if this is a firmware bug, hardware failure, or data transmission error before any safety protocols are triggered.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "living_room"], "focus_devices": ["temperature_sensor", "smoke_co_alarm", "water_leak_detector", "cook_surface"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04", "C05", "C06", "C07"], "suspected_patterns": ["Abnormal temperature readings (values > 2000) across all rooms indicating sensor calibration failure or data corruption.", "High frequency of 'alarmish' events correlating with temperature spikes, suggesting a potential false alarm cascade due to the faulty sensor data."], "why_these_chunks": ["Chunks C00-C07 contain the initial and most severe temperature anomalies (ranging from ~2278 to ~2553), which are physically impossible for standard indoor environments and indicate a critical system health issue rather than an environmental hazard. These chunks require inspection to determine if this is a firmware bug, hardware failure, or data transmission error before any safety protocols are triggered."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"System-wide sensor calibration drift or firmware bug causing uniform offset.\",\n      \"evidence\": [\"All temperature sensors report values between 2260-2495, which are physically impossible for indoor environments (likely intended to be ~20-30).\", \"The magnitude of the error is consistent across all room types (living_room, kitchen, bedrooms) suggesting a global configuration error rather than localized heat sources.\"],\n      \"weaknesses\": [\"If this were a simple offset, one would expect some variation based on actual room conditions, but the values remain stubbornly high and fluctuate erratically without a clear physical cause like a fire.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Critical Data Corruption / Sensor Firmware Failure.\",\n      \"threat_type\": \"System Integrity / False Positive Cascade Risk\",\n      \"evidence\": [\"MeasuredValues range from 2262 to 2495 over a 6-hour period. Standard indoor temperatures rarely exceed 35°C (89°F), making these readings (>2200 units) physically impossible.\", \"The 'attribute_frequency' shows 'MeasuredValue': 1152 events, indicating the system is actively generating massive amounts of invalid data points rather than just failing once.\", \"Occupancy sensors consistently report 0 (empty house) while temperature sensors generate this chaotic stream, ruling out occupancy-based heating as a cause.\", \"No lock_state_flips occurred, suggesting doors/windows are sealed, yet 'temperature' logic fails completely.\"],\n      \"weaknesses\": [\"We cannot definitively prove it isn't an external industrial furnace operating in the basement if the house layout is non-standard, though the values are too high even for that.\"]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Potential Data Transmission Protocol Error (Overflow/Corruption).\",\n      \"threat_type\": \"Information Security / Reliability\",\n      \"evidence\": [\"The timestamps are precise to the second, but the payload values (2278, 2294, etc.) show no correlation with time or known environmental cycles.\", \"The specific chunk IDs C00-C04 cover the entire anomaly duration, showing a sustained failure mode rather than a transient glitch.\"],\n      \"weaknesses\": [\"Could be misinterpreted as a real hazard by downstream safety systems if not filtered correctly.\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The absolute value magnitude: Indoor temperatures > 2200 are physically impossible under any standard domestic scenario, immediately classifying this as a hardware/software fault rather than an environmental event.\",\n    \"Consistency of Invalidity: Every single temperature reading across 8 different rooms contains the same impossible characteristic, pointing to a central processing unit issue or broadcast command failure rather than individual sensor failures.\",\n    \"Contradictory State: The house is reported as fully unoccupied (all Occupancy = 0) during the entire anomalous period, eliminating human activity (cooking, heating) as the source of the extreme readings.\"\n  ],\n  \"missing_information\": [\n    \"Historical baseline data: What were the normal readings before 2026-06-21T00:00:00?\",\n    \"Sensor hardware logs: Did the sensors reboot, reset, or enter an error state at the start of the log?\",\n    \"Network topology: Is there a centralized controller sending a 'setpoint' or 'override' command that could have triggered this?\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "System-wide sensor calibration drift or firmware bug causing uniform offset.", "evidence": ["All temperature sensors report values between 2260-2495, which are physically impossible for indoor environments (likely intended to be ~20-30).", "The magnitude of the error is consistent across all room types (living_room, kitchen, bedrooms) suggesting a global configuration error rather than localized heat sources."], "weaknesses": ["If this were a simple offset, one would expect some variation based on actual room conditions, but the values remain stubbornly high and fluctuate erratically without a clear physical cause like a fire."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Critical Data Corruption / Sensor Firmware Failure.", "threat_type": "System Integrity / False Positive Cascade Risk", "evidence": ["MeasuredValues range from 2262 to 2495 over a 6-hour period. Standard indoor temperatures rarely exceed 35°C (89°F), making these readings (>2200 units) physically impossible.", "The 'attribute_frequency' shows 'MeasuredValue': 1152 events, indicating the system is actively generating massive amounts of invalid data points rather than just failing once.", "Occupancy sensors consistently report 0 (empty house) while temperature sensors generate this chaotic stream, ruling out occupancy-based heating as a cause.", "No lock_state_flips occurred, suggesting doors/windows are sealed, yet 'temperature' logic fails completely."], "weaknesses": ["We cannot definitively prove it isn't an external industrial furnace operating in the basement if the house layout is non-standard, though the values are too high even for that."]}, {"id": "A2", "description": "Potential Data Transmission Protocol Error (Overflow/Corruption).", "threat_type": "Information Security / Reliability", "evidence": ["The timestamps are precise to the second, but the payload values (2278, 2294, etc.) show no correlation with time or known environmental cycles.", "The specific chunk IDs C00-C04 cover the entire anomaly duration, showing a sustained failure mode rather than a transient glitch."], "weaknesses": ["Could be misinterpreted as a real hazard by downstream safety systems if not filtered correctly."]}], "most_discriminative_evidence": ["The absolute value magnitude: Indoor temperatures > 2200 are physically impossible under any standard domestic scenario, immediately classifying this as a hardware/software fault rather than an environmental event.", "Consistency of Invalidity: Every single temperature reading across 8 different rooms contains the same impossible characteristic, pointing to a central processing unit issue or broadcast command failure rather than individual sensor failures.", "Contradictory State: The house is reported as fully unoccupied (all Occupancy = 0) during the entire anomalous period, eliminating human activity (cooking, heating) as the source of the extreme readings."], "missing_information": ["Historical baseline data: What were the normal readings before 2026-06-21T00:00:00?", "Sensor hardware logs: Did the sensors reboot, reset, or enter an error state at the start of the log?", "Network topology: Is there a centralized controller sending a 'setpoint' or 'override' command that could have triggered this?"]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C08\", \"C09\", \"C10\"],\n  \"missing_checks\": [\n    \"Verify sensor reboot logs or error states at the start of the anomaly.\",\n    \"Check for centralized controller 'override' commands in historical data prior to C00.\",\n    \"Review network topology to rule out broadcast command failures.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identifies the temperature readings (>2000) as physically impossible and indicative of a system integrity issue rather than an environmental hazard.\",\n    \"However, the current evidence only covers chunks C00-C07 (the initial onset). To fully diagnose the root cause, we need earlier context (C08-C10) to establish a baseline and check for preceding commands or hardware resets that triggered this global failure mode.\",\n    \"The hypothesis regarding a 'firmware bug' vs. 'data corruption' cannot be distinguished without seeing the state immediately before the anomaly began.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C08", "C09", "C10"], "missing_checks": ["Verify sensor reboot logs or error states at the start of the anomaly.", "Check for centralized controller 'override' commands in historical data prior to C00.", "Review network topology to rule out broadcast command failures."], "supervisor_notes": ["The analysis correctly identifies the temperature readings (>2000) as physically impossible and indicative of a system integrity issue rather than an environmental hazard.", "However, the current evidence only covers chunks C00-C07 (the initial onset). To fully diagnose the root cause, we need earlier context (C08-C10) to establish a baseline and check for preceding commands or hardware resets that triggered this global failure mode.", "The hypothesis regarding a 'firmware bug' vs. 'data corruption' cannot be distinguished without seeing the state immediately before the anomaly began."]}, "preview_triage_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Layout\nLayout: 三室两厅 (3BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kids_room: 儿童房温度传感器<temperature_sensor>, 儿童房灯<dimmable_light>, 儿童房窗帘<window_covering>, 儿童房窗户传感器<contact_sensor>, 儿童房运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅副灯<dimmable_light>, 客厅氛围灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘1<window_covering>, 客厅窗户传感器1<contact_sensor>, 客厅窗户传感器2<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n- master_bathroom: 主卫漏水传感器<water_leak_detector>, 主卫灯<onoff_light>, 主卫运动传感器<occupancy_sensor>\n- master_bedroom: 主卧床头灯<onoff_light>, 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>\n- second_bedroom: 次卧灯<dimmable_light>, 次卧空调<air_conditioner>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 336,\n    \"master_bedroom\": 336,\n    \"kids_room\": 338,\n    \"kitchen\": 288,\n    \"dining_room\": 48,\n    \"second_bedroom\": 48,\n    \"master_bathroom\": 48,\n    \"entrance\": 50\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1152,\n    \"Occupancy\": 337,\n    \"OnOff\": 1\n  },\n  \"lock_state_flips\": 0,\n  \"occupancy_events\": 337,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-21T00:00:00\",\n    \"end_ts\": \"2026-06-21T01:10:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 18,\n      \"master_bedroom\": 18,\n      \"kids_room\": 18,\n      \"kitchen\": 14,\n      \"dining_room\": 3,\n      \"second_bedroom\": 3,\n      \"master_bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"kids_room_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"dining_room_occupancy\"\n    ],\n    \"alarmish_count\": 21,\n    \"preview_lines\": [\n      \"[2026-06-21T00:00:00] living_room_temp_sensor | TemperatureMeasurement.", "preview_verifier_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\"],\n  \"focus_devices\": [\"temperature_sensor\", \"smoke_co_alarm\", \"water_leak_detector\", \"cook_surface\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\", \"C05\", \"C06\", \"C07\"],\n  \"suspected_patterns\": [\n    \"Abnormal temperature readings (values > 2000) across all rooms indicating sensor calibration failure or data corruption.\",\n    \"High frequency of 'alarmish' events correlating with temperature spikes, suggesting a potential false alarm cascade due to the faulty sensor data.\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunks C00-C07 contain the initial and most severe temperature anomalies (ranging from ~2278 to ~2553), which are physically impossible for standard indoor environments and indicate a critical system health issue rather than an environmental hazard. These chunks require inspection to determine if this is a firmware bug, hardware failure, or data transmission error before any safety protocols are triggered.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"System-wide sensor calibration drift or firmware bug causing uniform offset.\",\n      \"evidence\": [\"All temperature sensors report values between 2260-2495, which are physically impossible for indoor environments (likely intended to be ~20-30).\", \"The magnitude of the error is consistent across all room types (living_room, kitchen, bedrooms) suggesting a global configuration error rather than localized heat sources.\"],\n      \"weaknesses\": [\"If this were a simple offset, one would expect some variation based on actual room conditions, but the values remain stubbornly high and fluctuate erratically without a clear physical cause like a fire.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Critical Data Corruption / Sensor Firmware Failure.\",\n      \"threat_type\": \"System Integrity / False Positive Cascade Risk\",\n      \"evidence\": [\"MeasuredValues range from 2262 to 2495 over a 6-hour period. Standard indoor temperatures rarely exceed 35°C (89°F), making these readings (>2200 units) physically impossible.\", \"The 'attribute_frequency' shows 'MeasuredValue': 1152 events, indicating the system is actively generating massive amounts of invalid data points rather than just failing once.\", \"Occupancy sensors consistently report 0 (empty house) while temperature sensor"}}
{"episode_id": "SQ4_TP_D_0745", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq4\\SQ4_TP_D_0745.json", "metadata": {"sq_type": "SQ4", "sq_name": "复合安全推理", "variant": "TP", "layout_id": "D", "layout_name": "独居老人 (Elderly Living Alone)", "profile_id": "elderly_living_alone", "base_date": "2026-06-12T00:00:00", "seed": 20261374, "scenario_id": "EL-03", "total_events": 1858, "anomaly_events_count": 6}, "ground_truth": {"scenario_id": "EL-03", "scenario_name": "忘记关火", "category": "elderly_specific", "is_anomaly": true, "threat_type": "unattended_cooking", "key_evidence": ["灶具开着 + 厨房无人 + 老人在其他房间", "跟 FG-01 类似但在老人场景下更危险（认知衰退风险更高）"], "expected_response": "立即语音提醒老人关火", "difficulty_score": 10, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 2, "D5_fp_similarity": 2}, "target_room": "kitchen", "injection_time": "2026-06-12T11:54:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"The kitchen temperature sensor is critically malfunctioning by returning 'None' values immediately after the cook surface is activated or deactivated, creating a dangerous blind spot for fire monitoring.\",\n  \"reasoning\": [\n      \"Analysis of chunk C03 reveals a cooking event starting at 06:10:39 where the `kitchen_cook_surface` turns ON, but the `kitchen_temp_sensor` immediately returns 'None' at 06:11:09, preventing heat verification during active use.\",\n      \"A repeat failure occurs in chunk C04 at 06:33:00 when the cook surface turns OFF, followed instantly by a 'None' reading from the temperature sensor at 06:34:00, confirming a systematic hardware or communication fault rather than random noise.\",\n      \"Similar anomalies are observed in chunks C09 and C16, where every instance of appliance state change (ON/OFF) triggers immediate data loss from the thermal sensor, rendering the kitchen effectively unmonitored for overheating or fire hazards.\"\n    ],\n  \"key_evidence\": [\n      \"[2026-06-12T06:10:39] kitchen_cook_surface | OnOff.OnOff = True followed by [2026-06-12T06:11:09] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = None\",\n      \"[2026-06-12T06:33:00] kitchen_cook_surface | OnOff.OnOff = False followed by [2026-06-12T06:34:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = None\"\n    ],\n  \"recommended_actions\": [\n      \"Immediately inspect and replace the kitchen temperature sensor to restore continuous thermal monitoring.\",\n      \"Conduct a manual safety check of the kitchen area to ensure no lingering heat sources or smoke detectors have been compromised due to the lack of automated alerts.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "The kitchen temperature sensor is critically malfunctioning by returning 'None' values immediately after the cook surface is activated or deactivated, creating a dangerous blind spot for fire monitoring.", "reasoning": ["Analysis of chunk C03 reveals a cooking event starting at 06:10:39 where the `kitchen_cook_surface` turns ON, but the `kitchen_temp_sensor` immediately returns 'None' at 06:11:09, preventing heat verification during active use.", "A repeat failure occurs in chunk C04 at 06:33:00 when the cook surface turns OFF, followed instantly by a 'None' reading from the temperature sensor at 06:34:00, confirming a systematic hardware or communication fault rather than random noise.", "Similar anomalies are observed in chunks C09 and C16, where every instance of appliance state change (ON/OFF) triggers immediate data loss from the thermal sensor, rendering the kitchen effectively unmonitored for overheating or fire hazards."], "key_evidence": ["[2026-06-12T06:10:39] kitchen_cook_surface | OnOff.OnOff = True followed by [2026-06-12T06:11:09] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = None", "[2026-06-12T06:33:00] kitchen_cook_surface | OnOff.OnOff = False followed by [2026-06-12T06:34:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = None"], "recommended_actions": ["Immediately inspect and replace the kitchen temperature sensor to restore continuous thermal monitoring.", "Conduct a manual safety check of the kitchen area to ensure no lingering heat sources or smoke detectors have been compromised due to the lack of automated alerts."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 61.544997692108154, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1858, "chunk_count": 24, "signals": {"room_activity": {"living_room": 498, "bedroom": 530, "kitchen": 536, "bathroom": 63, "entrance": 231}, "attribute_frequency": {"Occupancy": 947, "MeasuredValue": 871, "OnOff": 23, "CurrentPositionLiftPercent100ths": 4, "LockState": 4, "StateValue": 4, "CurrentLevel": 1}, "lock_state_flips": 4, "occupancy_events": 947, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"bedroom\", \"living_room\"],\n  \"focus_devices\": [\"kitchen_cook_surface\", \"temperature_sensor\", \"occupancy_sensor\", \"front_door_contact\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C03\", \"C09\", \"C16\"],\n  \"suspected_patterns\": [\n    \"Sustained high indoor temperatures (24-25°C range) potentially indicating HVAC failure or overheating in a home with an elderly resident.\",\n    \"Intermittent loss of sensor data ('None' values) on critical kitchen temperature sensors, suggesting hardware malfunction or signal interference during active cooking.\",\n    \"Activity spike at night/late evening (high entrance occupancy and motion) which may indicate wandering behavior, fatigue, or unauthorized access for a lone senior.\",\n    \"Cooking activity detected late in the sequence without immediate subsequent cooling events, raising burn/fire risk.\"\n  ],\n  \"why_these_chunks\": [\n    \"C00/C01: Establish the baseline of abnormally high ambient temperatures across all rooms early in the timeline.\",\n    \"C03: Shows peak temperature readings (>24°C), confirming the thermal anomaly persists.\",\n    \"C09: Critical safety event where the cook surface turns ON while the temperature sensor returns 'None', creating a blind spot for heat monitoring.\",\n    \"C16: Another instance of sensor data loss ('None') coinciding with the cook surface turning OFF, indicating unreliable telemetry during appliance state changes.\",\n    \"C00-C23: Longitudinal analysis required to track the progression from empty house to active living patterns late at night.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "bedroom", "living_room"], "focus_devices": ["kitchen_cook_surface", "temperature_sensor", "occupancy_sensor", "front_door_contact"], "focus_chunk_ids": ["C00", "C01", "C03", "C09", "C16"], "suspected_patterns": ["Sustained high indoor temperatures (24-25°C range) potentially indicating HVAC failure or overheating in a home with an elderly resident.", "Intermittent loss of sensor data ('None' values) on critical kitchen temperature sensors, suggesting hardware malfunction or signal interference during active cooking.", "Activity spike at night/late evening (high entrance occupancy and motion) which may indicate wandering behavior, fatigue, or unauthorized access for a lone senior.", "Cooking activity detected late in the sequence without immediate subsequent cooling events, raising burn/fire risk."], "why_these_chunks": ["C00/C01: Establish the baseline of abnormally high ambient temperatures across all rooms early in the timeline.", "C03: Shows peak temperature readings (>24°C), confirming the thermal anomaly persists.", "C09: Critical safety event where the cook surface turns ON while the temperature sensor returns 'None', creating a blind spot for heat monitoring.", "C16: Another instance of sensor data loss ('None') coinciding with the cook surface turning OFF, indicating unreliable telemetry during appliance state changes.", "C00-C23: Longitudinal analysis required to track the progression from empty house to active living patterns late at night."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The house is currently occupied by a single resident who has been active throughout the day, engaging in normal cooking activities and moving between rooms. The high ambient temperatures are due to external weather (June) and lack of HVAC cooling.\",\n      \"evidence\": [\n        \"Occupancy sensors show consistent presence in bedroom, kitchen, living room, bathroom, and entrance from 05:30 onwards.\",\n        \"Cook surface was activated at 06:10 and 11:54, typical for meal preparation.\",\n        \"Window covering was closed at 05:32, which is normal behavior to retain heat during cooler morning hours or block sun.\"\n      ],\n      \"weaknesses\": [\n        \"Temperature values are unphysically high (22-25°C range represented as 2200-2500), suggesting a sensor calibration offset rather than actual thermal readings.\",\n        \"Kitchen temperature sensor returns 'None' immediately after cook surface activation, indicating a potential hardware fault or communication drop.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Critical failure of the kitchen temperature monitoring system creates a blind spot for fire safety, allowing the cook surface to operate without valid thermal feedback.\",\n      \"threat_type\": \"Fire Hazard / Sensor Malfunction\",\n      \"evidence\": [\n        \"At 06:10:39, kitchen_cook_surface turns ON.\",\n        \"Immediately at 06:11:09, kitchen_temp_sensor reports 'None'.\",\n        \"This pattern repeats at 11:07:30 (Cook ON) -> 11:08:00 (Temp None) and 11:26:00 (Cook OFF) -> 11:27:00 (Temp None).\",\n        \"The sensor fails specifically during active appliance states, not just when idle.\"\n      ],\n      \"weaknesses\": [\n        \"No evidence of smoke detection triggering an alarm yet.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Severe HVAC failure leading to dangerous overheating, indicated by sustained and rising indoor temperatures that exceed safe human comfort levels significantly.\",\n      \"threat_type\": \"Environmental Hazard / Health Risk\",\n      \"evidence\": [\n        \"Living room temperature rises steadily from ~22°C (2200) at 00:00 to ~25°C (2500) by 11:00 and remains elevated.\",\n        \"Peak reading at 11:10 shows 2552 (25.5°C equivalent if scaled correctly, or simply anomalously high raw data), while bedroom is also high at 2439.\",\n        \"Despite occupancy starting at 05:30, there is no corresponding drop in temperature or activation of cooling systems; instead, temperatures continue to climb into the mid-20s range.\"\n      ],\n      \"weaknesses\": [\n        \"Raw temperature units are ambiguous; could be millidegrees Celsius (which would make these normal) unless the system interprets them as standard degrees.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The temporal correlation between `kitchen_cook_surface.OnOff = True` and `kitchen_temp_sensor.MeasuredValue = None` occurring repeatedly across different time blocks (C03, C09, C16) strongly indicates a systematic sensor failure rather than random noise.\",\n    \"The continuous upward trend in temperature readings across all rooms (C00 to C03) despite the start of occupancy suggests a lack of environmental control (AC/Heater malfunction).\"\n  ],\n  \"missing_information\": [\n    \"Actual unit of measurement for the TemperatureMeasurement values (e.g., are they °C, m°C, or relative index?).\",\n    \"Status of the HVAC system (On/Off) and thermostat setpoints.\",\n    \"Presence of any smoke detector alerts or carbon monoxide sensor readings.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The house is currently occupied by a single resident who has been active throughout the day, engaging in normal cooking activities and moving between rooms. The high ambient temperatures are due to external weather (June) and lack of HVAC cooling.", "evidence": ["Occupancy sensors show consistent presence in bedroom, kitchen, living room, bathroom, and entrance from 05:30 onwards.", "Cook surface was activated at 06:10 and 11:54, typical for meal preparation.", "Window covering was closed at 05:32, which is normal behavior to retain heat during cooler morning hours or block sun."], "weaknesses": ["Temperature values are unphysically high (22-25°C range represented as 2200-2500), suggesting a sensor calibration offset rather than actual thermal readings.", "Kitchen temperature sensor returns 'None' immediately after cook surface activation, indicating a potential hardware fault or communication drop."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Critical failure of the kitchen temperature monitoring system creates a blind spot for fire safety, allowing the cook surface to operate without valid thermal feedback.", "threat_type": "Fire Hazard / Sensor Malfunction", "evidence": ["At 06:10:39, kitchen_cook_surface turns ON.", "Immediately at 06:11:09, kitchen_temp_sensor reports 'None'.", "This pattern repeats at 11:07:30 (Cook ON) -> 11:08:00 (Temp None) and 11:26:00 (Cook OFF) -> 11:27:00 (Temp None).", "The sensor fails specifically during active appliance states, not just when idle."], "weaknesses": ["No evidence of smoke detection triggering an alarm yet."]}, {"id": "A2", "description": "Severe HVAC failure leading to dangerous overheating, indicated by sustained and rising indoor temperatures that exceed safe human comfort levels significantly.", "threat_type": "Environmental Hazard / Health Risk", "evidence": ["Living room temperature rises steadily from ~22°C (2200) at 00:00 to ~25°C (2500) by 11:00 and remains elevated.", "Peak reading at 11:10 shows 2552 (25.5°C equivalent if scaled correctly, or simply anomalously high raw data), while bedroom is also high at 2439.", "Despite occupancy starting at 05:30, there is no corresponding drop in temperature or activation of cooling systems; instead, temperatures continue to climb into the mid-20s range."], "weaknesses": ["Raw temperature units are ambiguous; could be millidegrees Celsius (which would make these normal) unless the system interprets them as standard degrees."]}], "most_discriminative_evidence": ["The temporal correlation between `kitchen_cook_surface.OnOff = True` and `kitchen_temp_sensor.MeasuredValue = None` occurring repeatedly across different time blocks (C03, C09, C16) strongly indicates a systematic sensor failure rather than random noise.", "The continuous upward trend in temperature readings across all rooms (C00 to C03) despite the start of occupancy suggests a lack of environmental control (AC/Heater malfunction)."], "missing_information": ["Actual unit of measurement for the TemperatureMeasurement values (e.g., are they °C, m°C, or relative index?).", "Status of the HVAC system (On/Off) and thermostat setpoints.", "Presence of any smoke detector alerts or carbon monoxide sensor readings."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C02\", \"C04\", \"C17\", \"C18\"],\n  \"missing_checks\": [\n    \"Verify HVAC system status (On/Off) and thermostat setpoints to confirm A2 hypothesis.\",\n    \"Check for smoke detector alerts or carbon monoxide sensor readings as requested in 'missing_information'.\",\n    \"Clarify the unit of measurement for TemperatureMeasurement values (°C vs m°C) to validate the thermal anomaly severity.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis is on-topic but relies heavily on hypotheses regarding sensor calibration errors (N1/A2) without confirming the data units. Chunk C02/C04 are needed to see if temperature trends persist or reset early in the timeline before the suspected anomalies.\",\n    \"Critical safety checks for smoke/CO sensors and HVAC status are missing from the current evidence scope. Chunks C17/C18 likely contain late-night event logs which are necessary to verify the 'activity spike' and potential wandering behavior mentioned in the triage profile.\",\n    \"Without explicit confirmation of the temperature unit scale (millidegrees vs degrees), the 'dangerous overheating' conclusion (A2) remains speculative and potentially misleading.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C02", "C04", "C17", "C18"], "missing_checks": ["Verify HVAC system status (On/Off) and thermostat setpoints to confirm A2 hypothesis.", "Check for smoke detector alerts or carbon monoxide sensor readings as requested in 'missing_information'.", "Clarify the unit of measurement for TemperatureMeasurement values (°C vs m°C) to validate the thermal anomaly severity."], "supervisor_notes": ["The analysis is on-topic but relies heavily on hypotheses regarding sensor calibration errors (N1/A2) without confirming the data units. Chunk C02/C04 are needed to see if temperature trends persist or reset early in the timeline before the suspected anomalies.", "Critical safety checks for smoke/CO sensors and HVAC status are missing from the current evidence scope. Chunks C17/C18 likely contain late-night event logs which are necessary to verify the 'activity spike' and potential wandering behavior mentioned in the triage profile.", "Without explicit confirmation of the temperature unit scale (millidegrees vs degrees), the 'dangerous overheating' conclusion (A2) remains speculative and potentially misleading."]}, "preview_triage_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Layout\nLayout: 独居老人 (Elderly Living Alone)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>, 床头灯<onoff_light>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房运动传感器<occupancy_sensor>\n- living_room: 客厅温度传感器<temperature_sensor>, 客厅灯<dimmable_light>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 498,\n    \"bedroom\": 530,\n    \"kitchen\": 536,\n    \"bathroom\": 63,\n    \"entrance\": 231\n  },\n  \"attribute_frequency\": {\n    \"Occupancy\": 947,\n    \"MeasuredValue\": 871,\n    \"OnOff\": 23,\n    \"CurrentPositionLiftPercent100ths\": 4,\n    \"LockState\": 4,\n    \"StateValue\": 4,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 947,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-12T00:00:00\",\n    \"end_ts\": \"2026-06-12T01:35:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 24,\n      \"bedroom\": 24,\n      \"kitchen\": 24,\n      \"bathroom\": 4,\n      \"entrance\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"kitchen_occupancy\"\n    ],\n    \"alarmish_count\": 20,\n    \"preview_lines\": [\n      \"[2026-06-12T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2280\",\n      \"[2026-06-12T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2170\",\n      \"[2026-06-12T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2277\",\n      \"[2026-06-12T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-12T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-12T00:00:00] kitchen_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-12T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-12T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-12T00:05:00] li", "preview_verifier_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"bedroom\", \"living_room\"],\n  \"focus_devices\": [\"kitchen_cook_surface\", \"temperature_sensor\", \"occupancy_sensor\", \"front_door_contact\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C03\", \"C09\", \"C16\"],\n  \"suspected_patterns\": [\n    \"Sustained high indoor temperatures (24-25°C range) potentially indicating HVAC failure or overheating in a home with an elderly resident.\",\n    \"Intermittent loss of sensor data ('None' values) on critical kitchen temperature sensors, suggesting hardware malfunction or signal interference during active cooking.\",\n    \"Activity spike at night/late evening (high entrance occupancy and motion) which may indicate wandering behavior, fatigue, or unauthorized access for a lone senior.\",\n    \"Cooking activity detected late in the sequence without immediate subsequent cooling events, raising burn/fire risk.\"\n  ],\n  \"why_these_chunks\": [\n    \"C00/C01: Establish the baseline of abnormally high ambient temperatures across all rooms early in the timeline.\",\n    \"C03: Shows peak temperature readings (>24°C), confirming the thermal anomaly persists.\",\n    \"C09: Critical safety event where the cook surface turns ON while the temperature sensor returns 'None', creating a blind spot for heat monitoring.\",\n    \"C16: Another instance of sensor data loss ('None') coinciding with the cook surface turning OFF, indicating unreliable telemetry during appliance state changes.\",\n    \"C00-C23: Longitudinal analysis required to track the progression from empty house to active living patterns late at night.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The house is currently occupied by a single resident who has been active throughout the day, engaging in normal cooking activities and moving between rooms. The high ambient temperatures are due to external weather (June) and lack of HVAC cooling.\",\n      \"evidence\": [\n        \"Occupancy sensors show consistent presence in bedroom, kitchen, living room, bathroom, and entrance from 05:30 onwards.\",\n        \"Cook surface was activated at 06:10 and 11:54, typical for meal preparation.\",\n        \"Window covering was closed at 05:32, which is normal behavior to retain heat during cooler morning hours or block sun.\"\n      ],\n      \"weaknesses\": [\n        \"Temperature values are unphysically high (22-25°C range represented as 2200-2"}}
{"episode_id": "SQ4_TP_D_0752", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq4\\SQ4_TP_D_0752.json", "metadata": {"sq_type": "SQ4", "sq_name": "复合安全推理", "variant": "TP", "layout_id": "D", "layout_name": "独居老人 (Elderly Living Alone)", "profile_id": "elderly_living_alone", "base_date": "2026-06-11T00:00:00", "seed": 20261381, "scenario_id": "EL-02", "total_events": 1851, "anomaly_events_count": 2}, "ground_truth": {"scenario_id": "EL-02", "scenario_name": "居家意外（任意位置跌倒/晕倒）", "category": "elderly_specific", "is_anomaly": true, "threat_type": "possible_fall", "key_evidence": ["最后一次运动在非卧室房间（如客厅、厨房）", "随后异常长时间无任何活动", "不在正常午睡时段（比如上午10点或下午4点）"], "expected_response": "紧急联系老人，如无应答联系紧急联系人或120", "difficulty_score": 12, "difficulty_level": 3, "difficulty_label": "L3_composite_reasoning", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 3, "D3_cross_device": 2, "D4_temporal_span": 3, "D5_fp_similarity": 2}, "target_room": "kitchen", "injection_time": "2026-06-11T10:39:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"The system data indicates a critical sensor scaling error causing unreliable temperature readings and masking potential environmental hazards, as no cooling or alarm systems were triggered despite rising values.\",\n  \"reasoning\": [\n      \"Analysis of raw log values (e.g., 2269, 2381) reveals they are statistically improbable for direct Celsius measurements, indicating a firmware bug where values are multiplied by 10 but not scaled down internally.\",\n      \"Despite the apparent steady rise in 'temperature' from ~22°C to ~25°C, no HVAC activation, window opening, or safety alarms occurred, suggesting thresholds are misconfigured relative to the erroneous raw data.\",\n      \"The combination of unverified thermal data and lack of automated mitigation creates a false sense of security, rendering the current safety monitoring ineffective.\"\n    ],\n  \"key_evidence\": [\n      \"Temperature readings show integer patterns consistent with `value * 10` truncation errors (e.g., 2269 instead of 22.69).\",\n      \"No actuator responses (HVAC, windows) or alarm states were logged during the period of increasing numerical temperature values.\",\n      \"Triage logic explicitly identified 'persistent_high_temperature_anomaly' linked to this scaling issue.\"\n    ],\n  \"recommended_actions\": [\n      \"Immediately verify physical room temperatures with independent manual thermometers.\",\n      \"Contact the smart home service provider to correct the sensor scaling factor in the configuration.\",\n      \"Temporarily disable automatic threshold triggers until the sensor data is validated to prevent future false negatives or positives.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "The system data indicates a critical sensor scaling error causing unreliable temperature readings and masking potential environmental hazards, as no cooling or alarm systems were triggered despite rising values.", "reasoning": ["Analysis of raw log values (e.g., 2269, 2381) reveals they are statistically improbable for direct Celsius measurements, indicating a firmware bug where values are multiplied by 10 but not scaled down internally.", "Despite the apparent steady rise in 'temperature' from ~22°C to ~25°C, no HVAC activation, window opening, or safety alarms occurred, suggesting thresholds are misconfigured relative to the erroneous raw data.", "The combination of unverified thermal data and lack of automated mitigation creates a false sense of security, rendering the current safety monitoring ineffective."], "key_evidence": ["Temperature readings show integer patterns consistent with `value * 10` truncation errors (e.g., 2269 instead of 22.69).", "No actuator responses (HVAC, windows) or alarm states were logged during the period of increasing numerical temperature values.", "Triage logic explicitly identified 'persistent_high_temperature_anomaly' linked to this scaling issue."], "recommended_actions": ["Immediately verify physical room temperatures with independent manual thermometers.", "Contact the smart home service provider to correct the sensor scaling factor in the configuration.", "Temporarily disable automatic threshold triggers until the sensor data is validated to prevent future false negatives or positives."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 61.98651194572449, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1851, "chunk_count": 24, "signals": {"room_activity": {"living_room": 497, "bedroom": 529, "kitchen": 536, "bathroom": 57, "entrance": 232}, "attribute_frequency": {"Occupancy": 943, "MeasuredValue": 870, "OnOff": 21, "CurrentPositionLiftPercent100ths": 4, "LockState": 4, "StateValue": 4, "CurrentLevel": 1}, "lock_state_flips": 4, "occupancy_events": 943, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\"],\n  \"focus_devices\": [\"temperature_sensor\", \"occupancy_sensor\", \"cook_surface\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\"],\n  \"suspected_patterns\": [\n    \"persistent_high_temperature_anomaly\",\n    \"occupancy_without_ventilation_correlation\"\n  ],\n  \"why_these_chunks\": [\n    \"C00-C03 show continuous temperature readings starting at ~22.6°C (x10) and rising steadily to >25°C, indicating a sensor scaling error or extreme heating event.\",\n    \"C04 marks the first appearance of 'Occupancy=1' in the kitchen while temperatures peak above 25°C, creating a high-risk scenario for an elderly person cooking without adequate cooling or ventilation.\",\n    \"The sustained high 'alarmish_count' across these chunks correlates with the thermal anomaly, suggesting system flags related to environmental safety.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "living_room"], "focus_devices": ["temperature_sensor", "occupancy_sensor", "cook_surface"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04"], "suspected_patterns": ["persistent_high_temperature_anomaly", "occupancy_without_ventilation_correlation"], "why_these_chunks": ["C00-C03 show continuous temperature readings starting at ~22.6°C (x10) and rising steadily to >25°C, indicating a sensor scaling error or extreme heating event.", "C04 marks the first appearance of 'Occupancy=1' in the kitchen while temperatures peak above 25°C, creating a high-risk scenario for an elderly person cooking without adequate cooling or ventilation.", "The sustained high 'alarmish_count' across these chunks correlates with the thermal anomaly, suggesting system flags related to environmental safety."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The temperature sensors are functioning correctly, reporting ambient room temperatures in the 22-25°C range, while 'Occupancy' events represent discrete user interactions or sensor noise rather than continuous presence.\",\n      \"evidence\": [\"All room temperatures fluctuate between ~2100 and ~2500 units across all chunks.\", \"Occupancy events for specific rooms (e.g., kitchen, bedroom) appear intermittently after initial periods of zero.\", \"No explicit error codes or alarm states are present in the raw logs.\"],\n      \"weaknesses\": [\"Temperature values are integers ending in even numbers (e.g., 2269, 2315) which is statistically improbable for analog thermal sensors without rounding logic, suggesting a scaling factor error.\", \"Continuous high-frequency updates of similar magnitude suggest a stuck loop or misconfiguration rather than natural environmental variance.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Critical Sensor Scaling Error: Temperature readings are multiplied by a factor of 10 (or similar), displaying values like 2381 instead of ~23.8°C. This indicates a firmware bug or configuration drift that renders thermal data unreliable for safety monitoring.\",\n      \"threat_type\": \"Data Integrity Failure / False Negative Risk\",\n      \"evidence\": [\"Initial reading at C00: 2269 (likely 22.69°C).\", \"Progressive rise to C04: 2520 (likely 25.20°C).\", \"Pattern of values ending in single digits (e.g., 2269, 2315) consistent with integer truncation of a scaled float.\", \"Triage output explicitly notes 'sensor scaling error'.\", \"Despite rising temps, no active cooling alarms trigger until potentially too late or never, due to threshold miscalculation based on raw values.\"],\n      \"weaknesses\": [\"Cannot confirm if the system has internal logic to handle this scale; perhaps thresholds are also scaled internally.\", \"Could be a unit conversion issue (e.g., Kelvin vs Celsius) though 25K is impossible.\"]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Elderly/Sole Occupant Thermal Hazard: An occupant (likely elderly given the slow movement patterns and focus on kitchen/bedroom) is exposed to rising heat levels (>25°C) without effective ventilation, indicated by closed windows and delayed light activation.\",\n      \"threat_type\": \"Environmental Safety Hazard / Heat Stress\",\n      \"evidence\": [\"Bedroom occupancy starts at 05:28; lights turn on shortly after (05:28:07).\", \"Window covering remains fully closed (Position=0) throughout the heating period.\", \"Kitchen cook surface turns ON at 05:56:32, adding heat source.\", \"Temperatures continue to climb steadily (23°C -> 25°C) over several hours without significant mitigation.\", \"Front door lock flips frequently (4 times), suggesting entry/exit attempts but no clear departure pattern before the end of the log.\"],\n      \"weaknesses\": [\"Absence of explicit age data for occupants.\", \"Potential for automated HVAC systems to override manual window settings if connected.\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The mathematical improbability of random sensor readings ending in odd/even sequences like '2269', '2315', '2478' which strongly implies a `value * 10` integer cast error.\",\n    \"The temporal correlation between the start of cooking (05:56) and the sustained rise in kitchen temperature despite the absence of reported ventilation changes (window position stays 0).\",\n    \"The Triage Output's explicit identification of 'persistent_high_temperature_anomaly' correlating with the raw data spikes.\"\n  ],\n  \"missing_information\": [\n    \"The actual configured temperature thresholds for alarms (are they set to raw 2500 or scaled 25.0?).\",\n    \"HVAC system status and automatic response logs (did the AC kick in?).\",\n    \"Demographic profile of the household members to assess vulnerability to heat stress.\",\n    \"Historical baseline data to determine if 25°C is an abnormal spike for this location/time of day.\"]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The temperature sensors are functioning correctly, reporting ambient room temperatures in the 22-25°C range, while 'Occupancy' events represent discrete user interactions or sensor noise rather than continuous presence.", "evidence": ["All room temperatures fluctuate between ~2100 and ~2500 units across all chunks.", "Occupancy events for specific rooms (e.g., kitchen, bedroom) appear intermittently after initial periods of zero.", "No explicit error codes or alarm states are present in the raw logs."], "weaknesses": ["Temperature values are integers ending in even numbers (e.g., 2269, 2315) which is statistically improbable for analog thermal sensors without rounding logic, suggesting a scaling factor error.", "Continuous high-frequency updates of similar magnitude suggest a stuck loop or misconfiguration rather than natural environmental variance."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Critical Sensor Scaling Error: Temperature readings are multiplied by a factor of 10 (or similar), displaying values like 2381 instead of ~23.8°C. This indicates a firmware bug or configuration drift that renders thermal data unreliable for safety monitoring.", "threat_type": "Data Integrity Failure / False Negative Risk", "evidence": ["Initial reading at C00: 2269 (likely 22.69°C).", "Progressive rise to C04: 2520 (likely 25.20°C).", "Pattern of values ending in single digits (e.g., 2269, 2315) consistent with integer truncation of a scaled float.", "Triage output explicitly notes 'sensor scaling error'.", "Despite rising temps, no active cooling alarms trigger until potentially too late or never, due to threshold miscalculation based on raw values."], "weaknesses": ["Cannot confirm if the system has internal logic to handle this scale; perhaps thresholds are also scaled internally.", "Could be a unit conversion issue (e.g., Kelvin vs Celsius) though 25K is impossible."]}, {"id": "A2", "description": "Elderly/Sole Occupant Thermal Hazard: An occupant (likely elderly given the slow movement patterns and focus on kitchen/bedroom) is exposed to rising heat levels (>25°C) without effective ventilation, indicated by closed windows and delayed light activation.", "threat_type": "Environmental Safety Hazard / Heat Stress", "evidence": ["Bedroom occupancy starts at 05:28; lights turn on shortly after (05:28:07).", "Window covering remains fully closed (Position=0) throughout the heating period.", "Kitchen cook surface turns ON at 05:56:32, adding heat source.", "Temperatures continue to climb steadily (23°C -> 25°C) over several hours without significant mitigation.", "Front door lock flips frequently (4 times), suggesting entry/exit attempts but no clear departure pattern before the end of the log."], "weaknesses": ["Absence of explicit age data for occupants.", "Potential for automated HVAC systems to override manual window settings if connected."]}], "most_discriminative_evidence": ["The mathematical improbability of random sensor readings ending in odd/even sequences like '2269', '2315', '2478' which strongly implies a `value * 10` integer cast error.", "The temporal correlation between the start of cooking (05:56) and the sustained rise in kitchen temperature despite the absence of reported ventilation changes (window position stays 0).", "The Triage Output's explicit identification of 'persistent_high_temperature_anomaly' correlating with the raw data spikes."], "missing_information": ["The actual configured temperature thresholds for alarms (are they set to raw 2500 or scaled 25.0?).", "HVAC system status and automatic response logs (did the AC kick in?).", "Demographic profile of the household members to assess vulnerability to heat stress.", "Historical baseline data to determine if 25°C is an abnormal spike for this location/time of day."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C05\", \"C06\"],\n  \"missing_checks\": [\"Verify HVAC status and automatic cooling responses in subsequent chunks to confirm lack of mitigation.\", \"Check for alarm trigger states or notifications in later logs once temperatures exceed typical thresholds (if scaled).\", \"Correlate door lock events with occupancy data to confirm if the occupant is trapped or attempting to leave but failing.\"],\n  \"supervisor_notes\": [\n      \"The analysis has correctly identified a potential sensor scaling error (values like 2269 implying ~22.7°C) and a heat hazard scenario involving an elderly occupant in the kitchen.\",\n      \"However, the evidence collection is currently insufficient because it stops at C04. The Investigator Output explicitly lists 'HVAC system status' and 'Historical baseline data' as missing information.\",\n      \"Chunks C05 and C06 are required to observe whether the temperature continues to rise unchecked (confirming the hazard) or if any automated systems eventually intervene, which would alter the risk assessment.\",\n      \"Additionally, checking further chunks is necessary to see if the 'front door lock' activity correlates with an actual exit attempt that might have been blocked or failed.\"\n    ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C05", "C06"], "missing_checks": ["Verify HVAC status and automatic cooling responses in subsequent chunks to confirm lack of mitigation.", "Check for alarm trigger states or notifications in later logs once temperatures exceed typical thresholds (if scaled).", "Correlate door lock events with occupancy data to confirm if the occupant is trapped or attempting to leave but failing."], "supervisor_notes": ["The analysis has correctly identified a potential sensor scaling error (values like 2269 implying ~22.7°C) and a heat hazard scenario involving an elderly occupant in the kitchen.", "However, the evidence collection is currently insufficient because it stops at C04. The Investigator Output explicitly lists 'HVAC system status' and 'Historical baseline data' as missing information.", "Chunks C05 and C06 are required to observe whether the temperature continues to rise unchecked (confirming the hazard) or if any automated systems eventually intervene, which would alter the risk assessment.", "Additionally, checking further chunks is necessary to see if the 'front door lock' activity correlates with an actual exit attempt that might have been blocked or failed."]}, "preview_triage_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Layout\nLayout: 独居老人 (Elderly Living Alone)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>, 床头灯<onoff_light>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房运动传感器<occupancy_sensor>\n- living_room: 客厅温度传感器<temperature_sensor>, 客厅灯<dimmable_light>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 497,\n    \"bedroom\": 529,\n    \"kitchen\": 536,\n    \"bathroom\": 57,\n    \"entrance\": 232\n  },\n  \"attribute_frequency\": {\n    \"Occupancy\": 943,\n    \"MeasuredValue\": 870,\n    \"OnOff\": 21,\n    \"CurrentPositionLiftPercent100ths\": 4,\n    \"LockState\": 4,\n    \"StateValue\": 4,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 943,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-11T00:00:00\",\n    \"end_ts\": \"2026-06-11T01:35:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 24,\n      \"bedroom\": 24,\n      \"kitchen\": 24,\n      \"bathroom\": 4,\n      \"entrance\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"kitchen_occupancy\"\n    ],\n    \"alarmish_count\": 20,\n    \"preview_lines\": [\n      \"[2026-06-11T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2269\",\n      \"[2026-06-11T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2163\",\n      \"[2026-06-11T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2266\",\n      \"[2026-06-11T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-11T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-11T00:00:00] kitchen_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-11T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-11T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-11T00:05:00] li", "preview_verifier_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\"],\n  \"focus_devices\": [\"temperature_sensor\", \"occupancy_sensor\", \"cook_surface\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\"],\n  \"suspected_patterns\": [\n    \"persistent_high_temperature_anomaly\",\n    \"occupancy_without_ventilation_correlation\"\n  ],\n  \"why_these_chunks\": [\n    \"C00-C03 show continuous temperature readings starting at ~22.6°C (x10) and rising steadily to >25°C, indicating a sensor scaling error or extreme heating event.\",\n    \"C04 marks the first appearance of 'Occupancy=1' in the kitchen while temperatures peak above 25°C, creating a high-risk scenario for an elderly person cooking without adequate cooling or ventilation.\",\n    \"The sustained high 'alarmish_count' across these chunks correlates with the thermal anomaly, suggesting system flags related to environmental safety.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The temperature sensors are functioning correctly, reporting ambient room temperatures in the 22-25°C range, while 'Occupancy' events represent discrete user interactions or sensor noise rather than continuous presence.\",\n      \"evidence\": [\"All room temperatures fluctuate between ~2100 and ~2500 units across all chunks.\", \"Occupancy events for specific rooms (e.g., kitchen, bedroom) appear intermittently after initial periods of zero.\", \"No explicit error codes or alarm states are present in the raw logs.\"],\n      \"weaknesses\": [\"Temperature values are integers ending in even numbers (e.g., 2269, 2315) which is statistically improbable for analog thermal sensors without rounding logic, suggesting a scaling factor error.\", \"Continuous high-frequency updates of similar magnitude suggest a stuck loop or misconfiguration rather than natural environmental variance.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Critical Sensor Scaling Error: Temperature readings are multiplied by a factor of 10 (or similar), displaying values like 2381 instead of ~23.8°C. This indicates a firmware bug or configuration drift that renders thermal data unreliable for safety monitoring.\",\n      \"threat_type\": \"Data Integrity Failure / False Negative Risk\",\n      \"evidence\": [\"Initial reading at C00: 2269 (likely 22.69°C).\", \"Progressive rise to C04: 2520 (likely 25.20°C).\", \"Pattern of values en"}}
{"episode_id": "SQ4_TP_C_0727", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq4\\SQ4_TP_C_0727.json", "metadata": {"sq_type": "SQ4", "sq_name": "复合安全推理", "variant": "TP", "layout_id": "C", "layout_name": "三室两厅 (3BR)", "profile_id": "family_with_children", "base_date": "2026-06-25T00:00:00", "seed": 20261356, "scenario_id": "CH-04", "total_events": 2293, "anomaly_events_count": 3}, "ground_truth": {"scenario_id": "CH-04", "scenario_name": "儿童尝试开门外出", "category": "child_specific", "is_anomaly": true, "threat_type": "child_safety", "key_evidence": ["玄关运动 + 门锁解锁失败", "密码错误（小孩可能记不准密码）", "无成人在玄关区域", "跟 INS-02 的区别：这里不是暴力破解，只有1-2次尝试，且家中有其他房间的活动（说明有人在家）"], "expected_response": "通知家长孩子在尝试开门", "difficulty_score": 9, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "kids_room", "injection_time": "2026-06-25T14:12:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"The entire home environment is reporting physically impossible temperature readings (2300-2540 scale) that indicate a critical sensor calibration failure or system overflow, rather than a real environmental hazard.\",\n  \"reasoning\": [\n      \"Analysis of temperature data from C01 to C08 shows consistent values ranging between 2298 and 2542 across all rooms over an 8-hour period. If interpreted as Celsius or Fahrenheit, these represent temperatures far exceeding the melting point of metals and the boiling point of lead, which would result in immediate house destruction and loss of life, contradicting the presence of occupants.\",\n      \"The uniformity of this anomaly across multiple sensors (kitchen, living room, bedrooms) and the steady nature of the reading (slowly drifting upwards by ~1 unit per hour) rules out localized equipment failures like a single broken appliance causing heat buildup.\",\n      \"Given the physical impossibility of indoor temperatures reaching >2500°C/F, the only logical conclusion is that the sensor firmware is outputting raw integer values in an incorrect unit (e.g., millikelvin where 2500mK is near absolute zero, or a floating-point overflow representing a normal temperature like 25.00), rendering the safety status based on these numbers invalid.\",\n      \"While the front door lock jamming (C06) was noted in the triage, the subsequent successful manual locking and auto-lock confirms the primary risk is the false positive regarding thermal conditions due to sensor malfunction.\"\n    ],\n  \"key_evidence\": [\n      \"Temperature readings consistently hover between 2300 and 2540 for 8 hours despite occupancy and lighting changes.\",\n      \"No corresponding physical damage events (fire, structural collapse) occurred during the reported high-temperature windows.\",\n      \"All room sensors report nearly identical magnitude values simultaneously, indicating a shared software/firmware baseline issue rather than individual sensor drift.\"\n    ],\n  \"recommended_actions\": [\n      \"Immediately reset all temperature sensors via the smart home hub to clear potential cache errors.\",\n      \"Verify the actual ambient temperature using independent analog thermometers placed in key locations (kitchen, bedroom).\",\n      \"Check device firmware logs for 'overflow', 'unit mismatch', or 'calibration fail' error codes.\",\n      \"Update the IoT ecosystem firmware to patch known scaling bugs.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "The entire home environment is reporting physically impossible temperature readings (2300-2540 scale) that indicate a critical sensor calibration failure or system overflow, rather than a real environmental hazard.", "reasoning": ["Analysis of temperature data from C01 to C08 shows consistent values ranging between 2298 and 2542 across all rooms over an 8-hour period. If interpreted as Celsius or Fahrenheit, these represent temperatures far exceeding the melting point of metals and the boiling point of lead, which would result in immediate house destruction and loss of life, contradicting the presence of occupants.", "The uniformity of this anomaly across multiple sensors (kitchen, living room, bedrooms) and the steady nature of the reading (slowly drifting upwards by ~1 unit per hour) rules out localized equipment failures like a single broken appliance causing heat buildup.", "Given the physical impossibility of indoor temperatures reaching >2500°C/F, the only logical conclusion is that the sensor firmware is outputting raw integer values in an incorrect unit (e.g., millikelvin where 2500mK is near absolute zero, or a floating-point overflow representing a normal temperature like 25.00), rendering the safety status based on these numbers invalid.", "While the front door lock jamming (C06) was noted in the triage, the subsequent successful manual locking and auto-lock confirms the primary risk is the false positive regarding thermal conditions due to sensor malfunction."], "key_evidence": ["Temperature readings consistently hover between 2300 and 2540 for 8 hours despite occupancy and lighting changes.", "No corresponding physical damage events (fire, structural collapse) occurred during the reported high-temperature windows.", "All room sensors report nearly identical magnitude values simultaneously, indicating a shared software/firmware baseline issue rather than individual sensor drift."], "recommended_actions": ["Immediately reset all temperature sensors via the smart home hub to clear potential cache errors.", "Verify the actual ambient temperature using independent analog thermometers placed in key locations (kitchen, bedroom).", "Check device firmware logs for 'overflow', 'unit mismatch', or 'calibration fail' error codes.", "Update the IoT ecosystem firmware to patch known scaling bugs."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 74.78669428825378, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 2293, "chunk_count": 29, "signals": {"room_activity": {"living_room": 402, "master_bedroom": 516, "kids_room": 518, "kitchen": 303, "dining_room": 221, "second_bedroom": 48, "master_bathroom": 54, "entrance": 230, "second_bathroom": 1}, "attribute_frequency": {"MeasuredValue": 1156, "Occupancy": 1087, "OnOff": 26, "StateValue": 7, "LockState": 5, "CurrentPositionLiftPercent100ths": 3, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 5, "occupancy_events": 1087, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"entrance\", \"kids_room\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"kitchen_window_contact\", \"front_door_lock\", \"kids_room_window_covering\"],\n  \"focus_chunk_ids\": [\"C06\", \"C15\", \"C24\"],\n  \"suspected_patterns\": [\n    \"Sustained high temperature readings across all rooms (2300-2500+ scale) indicating potential HVAC failure or sensor calibration drift.\",\n    \"Kitchen window contact state change to False while occupancy is present, suggesting an open window in a heated area.\",\n    \"Front door lock operation errors followed by successful manual locking, indicating mechanical jamming or user struggle.\",\n    \"Kids room window covering fully closed at night despite interior heat, potentially trapping hot air or preventing ventilation.\"\n  ],\n  \"why_these_chunks\": [\n    \"C06: Shows the kitchen window opening event during active hours and temperatures climbing above 2500.\",\n    \"C15: Contains critical 'LockOperationError' events for the front door, signaling a security/functional hazard.\",\n    \"C24: Captures the kids room window closing to 100% at night coinciding with peak indoor temperatures, creating a potential heat trap.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "entrance", "kids_room"], "focus_devices": ["kitchen_temp_sensor", "kitchen_window_contact", "front_door_lock", "kids_room_window_covering"], "focus_chunk_ids": ["C06", "C15", "C24"], "suspected_patterns": ["Sustained high temperature readings across all rooms (2300-2500+ scale) indicating potential HVAC failure or sensor calibration drift.", "Kitchen window contact state change to False while occupancy is present, suggesting an open window in a heated area.", "Front door lock operation errors followed by successful manual locking, indicating mechanical jamming or user struggle.", "Kids room window covering fully closed at night despite interior heat, potentially trapping hot air or preventing ventilation."], "why_these_chunks": ["C06: Shows the kitchen window opening event during active hours and temperatures climbing above 2500.", "C15: Contains critical 'LockOperationError' events for the front door, signaling a security/functional hazard.", "C24: Captures the kids room window closing to 100% at night coinciding with peak indoor temperatures, creating a potential heat trap."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Sensors are reporting values in a valid but non-standard scale (likely millikelvin or a specific proprietary unit where 2500+ corresponds to ~23°C), indicating stable thermal conditions.\",\n      \"evidence\": [\"Temperature readings remain consistent within narrow ranges across different rooms (e.g., Kitchen 2460-2533, Kids 2248-2527) without erratic spikes or drops typical of sensor failure.\", \"Occupancy patterns align with daily routines: high activity in mornings/afternoons, lights off at night (C24).\"],\n      \"weaknesses\": [\"The absolute magnitude of the numbers (>2000) is counter-intuitive for standard Celsius/Fahrenheit sensors used in consumer devices, requiring external calibration data to verify.\"],\n      \"threat_type\": null\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"Front door lock errors were caused by user distraction or mechanical friction unrelated to security compromise.\",\n      \"evidence\": [\"Error occurred during an active occupancy period (C15) followed immediately by successful manual locking (LockState=1).\", \"Door contact state flipped correctly (False then True) shortly after the error, suggesting the door was manipulated normally.\"],\n      \"weaknesses\": [\"Multiple consecutive errors (OperationError=1) suggest a persistent mechanical issue rather than a one-time glitch.\"],\n      \"threat_type\": null\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Critical HVAC Failure or Sensor Calibration Drift causing potentially lethal heat accumulation indoors.\",\n      \"threat_type\": \"Life Safety / Environmental Hazard\",\n      \"evidence\": [\"Massive temperature divergence between time blocks: C06/C24 show values >2200 while C15 shows ~2400. If scale is linear Celsius, this implies indoor temps of 2500°C (impossible) or a catastrophic drift if the scale is offset. Assuming standard deviation logic fails, the variance suggests system collapse.\", \"In C06, temperatures climb steadily from ~2500 to 2533 while kitchen window opens (State=False), exacerbating heat gain.\", \"In C24, despite lights going off and window closing, temperatures remain elevated (~2250) compared to the 'cooler' C15 block (~2450), suggesting no cooling cycle engaged.\"],\n      \"weaknesses\": [\"If the sensor unit is actually mK (millikelvin), 2500 mK = -272.95°C (near absolute zero), which would also be fatal but physically impossible for a living space unless frozen solid, contradicting 'occupancy'. The most likely scenario is a 'floating point' overflow or unit mismatch where 2500 represents a normal temp, making the *change* the anomaly, not the value itself. However, assuming the prompt implies these are raw readings that should be interpreted as dangerous anomalies per the triage output.\", \"No humidity or CO2 data provided to confirm suffocation risk.\"],\n      \"threat_type\": \"Environmental\"\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Security Compromise via Lock Jamming and Forced Entry Attempt.\",\n      \"threat_type\": \"Breach / Unauthorized Access\",\n      \"evidence\": [\"C15 shows two consecutive 'LockOperationError' events at 14:12:05 and 14:12:15 before any successful lock event.\", \"These errors coincide with high occupancy in the entrance/dining room, increasing vulnerability if entry failed.\", \"The sequence suggests a struggle to secure the perimeter while occupants are present inside.\"],\n      \"weaknesses\": [\"Successful auto-lock follows immediately, mitigating immediate breach risk.\", \"No forced entry alarms (door contact held open) were triggered during the error window.\"],\n      \"threat_type\": \"Physical Security\"\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The stark contrast in temperature readings between Chunk C15 (~2400 range) and Chunks C06/C24 (~2200-2500 range) indicates a systemic shift in environmental control or sensor baseline that defies normal diurnal cycles.\",\n    \"The specific timestamp correlation in C15: Two rapid-fire 'LockOperationError' events occurring while the house is occupied, distinguishing it from random mechanical noise.\"\n  ],\n  \"missing_information\": [\n    \"The unit of measurement for TemperatureMeasurement.MeasuredValue (e.g., Kelvin, Centi-Kelvin, or arbitrary units) is unknown; interpreting 2500 as 'hot' vs 'cold' depends entirely on this.\",\n    \"HVAC System Mode logs (Heating, Cooling, Auto, Off) to determine if the thermostat is actively failing or simply misreading.\",\n    \"Battery levels for the door lock motor to rule out power-induced operation errors.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Sensors are reporting values in a valid but non-standard scale (likely millikelvin or a specific proprietary unit where 2500+ corresponds to ~23°C), indicating stable thermal conditions.", "evidence": ["Temperature readings remain consistent within narrow ranges across different rooms (e.g., Kitchen 2460-2533, Kids 2248-2527) without erratic spikes or drops typical of sensor failure.", "Occupancy patterns align with daily routines: high activity in mornings/afternoons, lights off at night (C24)."], "weaknesses": ["The absolute magnitude of the numbers (>2000) is counter-intuitive for standard Celsius/Fahrenheit sensors used in consumer devices, requiring external calibration data to verify."], "threat_type": null}, {"id": "N2", "description": "Front door lock errors were caused by user distraction or mechanical friction unrelated to security compromise.", "evidence": ["Error occurred during an active occupancy period (C15) followed immediately by successful manual locking (LockState=1).", "Door contact state flipped correctly (False then True) shortly after the error, suggesting the door was manipulated normally."], "weaknesses": ["Multiple consecutive errors (OperationError=1) suggest a persistent mechanical issue rather than a one-time glitch."], "threat_type": null}], "anomaly_hypotheses": [{"id": "A1", "description": "Critical HVAC Failure or Sensor Calibration Drift causing potentially lethal heat accumulation indoors.", "threat_type": "Environmental", "evidence": ["Massive temperature divergence between time blocks: C06/C24 show values >2200 while C15 shows ~2400. If scale is linear Celsius, this implies indoor temps of 2500°C (impossible) or a catastrophic drift if the scale is offset. Assuming standard deviation logic fails, the variance suggests system collapse.", "In C06, temperatures climb steadily from ~2500 to 2533 while kitchen window opens (State=False), exacerbating heat gain.", "In C24, despite lights going off and window closing, temperatures remain elevated (~2250) compared to the 'cooler' C15 block (~2450), suggesting no cooling cycle engaged."], "weaknesses": ["If the sensor unit is actually mK (millikelvin), 2500 mK = -272.95°C (near absolute zero), which would also be fatal but physically impossible for a living space unless frozen solid, contradicting 'occupancy'. The most likely scenario is a 'floating point' overflow or unit mismatch where 2500 represents a normal temp, making the *change* the anomaly, not the value itself. However, assuming the prompt implies these are raw readings that should be interpreted as dangerous anomalies per the triage output.", "No humidity or CO2 data provided to confirm suffocation risk."]}, {"id": "A2", "description": "Security Compromise via Lock Jamming and Forced Entry Attempt.", "threat_type": "Physical Security", "evidence": ["C15 shows two consecutive 'LockOperationError' events at 14:12:05 and 14:12:15 before any successful lock event.", "These errors coincide with high occupancy in the entrance/dining room, increasing vulnerability if entry failed.", "The sequence suggests a struggle to secure the perimeter while occupants are present inside."], "weaknesses": ["Successful auto-lock follows immediately, mitigating immediate breach risk.", "No forced entry alarms (door contact held open) were triggered during the error window."]}], "most_discriminative_evidence": ["The stark contrast in temperature readings between Chunk C15 (~2400 range) and Chunks C06/C24 (~2200-2500 range) indicates a systemic shift in environmental control or sensor baseline that defies normal diurnal cycles.", "The specific timestamp correlation in C15: Two rapid-fire 'LockOperationError' events occurring while the house is occupied, distinguishing it from random mechanical noise."], "missing_information": ["The unit of measurement for TemperatureMeasurement.MeasuredValue (e.g., Kelvin, Centi-Kelvin, or arbitrary units) is unknown; interpreting 2500 as 'hot' vs 'cold' depends entirely on this.", "HVAC System Mode logs (Heating, Cooling, Auto, Off) to determine if the thermostat is actively failing or simply misreading.", "Battery levels for the door lock motor to rule out power-induced operation errors."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C01\", \"C02\", \"C03\", \"C04\", \"C05\", \"C07\", \"C08\", \"C09\", \"C10\", \"C11\", \"C12\", \"C13\", \"C14\", \"C16\", \"C17\", \"C18\", \"C19\", \"C20\", \"C21\", \"C22\", \"C23\", \"C25\", \"C26\", \"C27\", \"C28\"],\n  \"missing_checks\": [\n    \"HVAC System Mode logs to verify if cooling/heating is active or stuck.\",\n    \"Temperature unit definition (e.g., raw mK vs scaled Celsius) to validate the magnitude of readings.\",\n    \"Door lock battery status and error code specifics to distinguish mechanical jam from power failure.\",\n    \"Occupancy sensor data for all rooms during the temperature anomaly windows to confirm presence/absence correlation.\",\n    \"Historical baseline data for temperature sensors to determine if '2500' is a drift or normal baseline.\",\n    \"Security log details regarding forced entry attempts during the C15 lock errors.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis is highly focused on the triage-selected chunks (C06, C15, C24), which is appropriate for initial anomaly detection. However, declaring the evidence 'sufficient' to judge the *current* safety status is premature.\",\n    \"Without broader context (chunks outside C06/C15/C24), we cannot establish if the high temperatures are a systemic household failure affecting all zones simultaneously or isolated incidents. The lack of surrounding data prevents verifying diurnal patterns or ruling out sensor calibration drift across the whole system.\",\n    \"The hypothesis about the temperature unit scale relies entirely on assumptions not present in the selected chunks. We need chunks containing metadata or historical readings to define the unit of measurement definitively.\",\n    \"To fully assess the security risk of the front door lock errors, we need to see the sequence before and after C15 to ensure no prior tampering or subsequent breach occurred.\",\n    \"Conclusion: The investigation has identified potential risks but lacks the temporal and spatial breadth required to confirm severity or root cause. More chunks are needed to move from 'suspected pattern' to 'confirmed safety status'.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C01", "C02", "C03", "C04", "C05", "C07", "C08", "C09", "C10", "C11", "C12", "C13", "C14", "C16", "C17", "C18", "C19", "C20", "C21", "C22", "C23", "C25", "C26", "C27", "C28"], "missing_checks": ["HVAC System Mode logs to verify if cooling/heating is active or stuck.", "Temperature unit definition (e.g., raw mK vs scaled Celsius) to validate the magnitude of readings.", "Door lock battery status and error code specifics to distinguish mechanical jam from power failure.", "Occupancy sensor data for all rooms during the temperature anomaly windows to confirm presence/absence correlation.", "Historical baseline data for temperature sensors to determine if '2500' is a drift or normal baseline.", "Security log details regarding forced entry attempts during the C15 lock errors."], "supervisor_notes": ["The analysis is highly focused on the triage-selected chunks (C06, C15, C24), which is appropriate for initial anomaly detection. However, declaring the evidence 'sufficient' to judge the *current* safety status is premature.", "Without broader context (chunks outside C06/C15/C24), we cannot establish if the high temperatures are a systemic household failure affecting all zones simultaneously or isolated incidents. The lack of surrounding data prevents verifying diurnal patterns or ruling out sensor calibration drift across the whole system.", "The hypothesis about the temperature unit scale relies entirely on assumptions not present in the selected chunks. We need chunks containing metadata or historical readings to define the unit of measurement definitively.", "To fully assess the security risk of the front door lock errors, we need to see the sequence before and after C15 to ensure no prior tampering or subsequent breach occurred.", "Conclusion: The investigation has identified potential risks but lacks the temporal and spatial breadth required to confirm severity or root cause. More chunks are needed to move from 'suspected pattern' to 'confirmed safety status'."]}, "preview_triage_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Layout\nLayout: 三室两厅 (3BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kids_room: 儿童房温度传感器<temperature_sensor>, 儿童房灯<dimmable_light>, 儿童房窗帘<window_covering>, 儿童房窗户传感器<contact_sensor>, 儿童房运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅副灯<dimmable_light>, 客厅氛围灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘1<window_covering>, 客厅窗户传感器1<contact_sensor>, 客厅窗户传感器2<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n- master_bathroom: 主卫漏水传感器<water_leak_detector>, 主卫灯<onoff_light>, 主卫运动传感器<occupancy_sensor>\n- master_bedroom: 主卧床头灯<onoff_light>, 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>\n- second_bedroom: 次卧灯<dimmable_light>, 次卧空调<air_conditioner>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 402,\n    \"master_bedroom\": 516,\n    \"kids_room\": 518,\n    \"kitchen\": 303,\n    \"dining_room\": 221,\n    \"second_bedroom\": 48,\n    \"master_bathroom\": 54,\n    \"entrance\": 230,\n    \"second_bathroom\": 1\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1156,\n    \"Occupancy\": 1087,\n    \"OnOff\": 26,\n    \"StateValue\": 7,\n    \"LockState\": 5,\n    \"CurrentPositionLiftPercent100ths\": 3,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 5,\n  \"occupancy_events\": 1087,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-25T00:00:00\",\n    \"end_ts\": \"2026-06-25T01:10:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 18,\n      \"master_bedroom\": 18,\n      \"kids_room\": 18,\n      \"kitchen\": 14,\n      \"dining_room\": 3,\n      \"second_bedroom\": 3,\n      \"master_bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"kids_room_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n ", "preview_verifier_prompt": "## Query\n以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"entrance\", \"kids_room\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"kitchen_window_contact\", \"front_door_lock\", \"kids_room_window_covering\"],\n  \"focus_chunk_ids\": [\"C06\", \"C15\", \"C24\"],\n  \"suspected_patterns\": [\n    \"Sustained high temperature readings across all rooms (2300-2500+ scale) indicating potential HVAC failure or sensor calibration drift.\",\n    \"Kitchen window contact state change to False while occupancy is present, suggesting an open window in a heated area.\",\n    \"Front door lock operation errors followed by successful manual locking, indicating mechanical jamming or user struggle.\",\n    \"Kids room window covering fully closed at night despite interior heat, potentially trapping hot air or preventing ventilation.\"\n  ],\n  \"why_these_chunks\": [\n    \"C06: Shows the kitchen window opening event during active hours and temperatures climbing above 2500.\",\n    \"C15: Contains critical 'LockOperationError' events for the front door, signaling a security/functional hazard.\",\n    \"C24: Captures the kids room window closing to 100% at night coinciding with peak indoor temperatures, creating a potential heat trap.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Sensors are reporting values in a valid but non-standard scale (likely millikelvin or a specific proprietary unit where 2500+ corresponds to ~23°C), indicating stable thermal conditions.\",\n      \"evidence\": [\"Temperature readings remain consistent within narrow ranges across different rooms (e.g., Kitchen 2460-2533, Kids 2248-2527) without erratic spikes or drops typical of sensor failure.\", \"Occupancy patterns align with daily routines: high activity in mornings/afternoons, lights off at night (C24).\"],\n      \"weaknesses\": [\"The absolute magnitude of the numbers (>2000) is counter-intuitive for standard Celsius/Fahrenheit sensors used in consumer devices, requiring external calibration data to verify.\"],\n      \"threat_type\": null\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"Front door lock errors were caused by user distraction or mechanical friction unrelated to security compromise.\",\n      \"evidence\": [\"Error occurred during an active occupancy period (C15) followed immediately by successful manual locking (LockState=1).\", \"Door contact state flipped correctly (False then True) shortly after the e"}}
{"episode_id": "SQ5_FP_B_1116", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq5\\SQ5_FP_B_1116.json", "metadata": {"sq_type": "SQ5", "sq_name": "应急响应规划", "variant": "FP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "family_with_children", "base_date": "2026-06-17T00:00:00", "seed": 20261745, "scenario_id": "INS-04", "total_events": 1839, "anomaly_events_count": 4}, "ground_truth": {"scenario_id": "INS-04-FP", "scenario_name": "INS-04-FP: 清洁工/保姆上门", "category": "intrusion", "is_anomaly": false, "threat_type": "none", "key_difference": "通过门锁合法进入（有 LockOperation 事件+有效 UserIndex），不是通过窗户", "difficulty_score": 11, "difficulty_level": 3, "difficulty_label": "L3_composite_reasoning", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 3, "D4_temporal_span": 2, "D5_fp_similarity": 2}, "target_room": "master_bedroom", "injection_time": "2026-06-17T22:51:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_drift\",\n  \"threat_description\": \"System-wide sensor calibration failure causing physically impossible temperature readings (>200°C) and data loss, rendering environmental safety monitoring ineffective.\",\n  \"reasoning\": [\n      \"Analysis of early morning chunks (C00-C04) reveals that all temperature sensors consistently reported values between 2273 and 2500 starting from the beginning of the log period (00:00), indicating a persistent systemic scaling error or hardware fault rather than a transient event.\",\n      \"The 'anomaly' events identified in later chunks (kitchen activation at 18:49, door lock sequence at 22:50) occur against this broken baseline; however, the continuous impossibility of ambient air reaching ~24°C * 10 = 240°C confirms the root cause is sensor drift/malfunction.\",\n      \"While the kitchen cook surface turned on and the sensor subsequently returned 'None', the pre-existing invalid data means no actual fire risk could be detected by the system during that specific window due to the sensor's inability to provide valid feedback.\"\n    ],\n  \"key_evidence\": [\n      \"Chunks C00 through C04 show consistent temperature readings >2200 across all rooms from 00:00, which is physically impossible for Celsius ambient air.\",\n      \"At 18:50:00 and 19:16:00, the kitchen_temp_sensor returned 'None' immediately after cooking events, likely due to thermal overload or communication failure exacerbated by the faulty baseline.\",\n      \"All occupancy sensors correctly reported 0 during sleep hours and 1 during active hours, confirming the issue is isolated to temperature sensor logic/calibration.\"\n    ],\n  \"recommended_actions\": [\n      \"Immediately replace or recalibrate all temperature sensors to restore accurate environmental monitoring.\",\n      \"Verify the integrity of the sensor firmware and check for unit mismatch configurations (e.g., Kelvin vs. Celsius or integer scaling factors).\",\n      \"Perform a physical inspection of the kitchen temperature sensor and wiring given the history of returning 'None' values.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_drift", "threat_description": "System-wide sensor calibration failure causing physically impossible temperature readings (>200°C) and data loss, rendering environmental safety monitoring ineffective.", "reasoning": ["Analysis of early morning chunks (C00-C04) reveals that all temperature sensors consistently reported values between 2273 and 2500 starting from the beginning of the log period (00:00), indicating a persistent systemic scaling error or hardware fault rather than a transient event.", "The 'anomaly' events identified in later chunks (kitchen activation at 18:49, door lock sequence at 22:50) occur against this broken baseline; however, the continuous impossibility of ambient air reaching ~24°C * 10 = 240°C confirms the root cause is sensor drift/malfunction.", "While the kitchen cook surface turned on and the sensor subsequently returned 'None', the pre-existing invalid data means no actual fire risk could be detected by the system during that specific window due to the sensor's inability to provide valid feedback."], "key_evidence": ["Chunks C00 through C04 show consistent temperature readings >2200 across all rooms from 00:00, which is physically impossible for Celsius ambient air.", "At 18:50:00 and 19:16:00, the kitchen_temp_sensor returned 'None' immediately after cooking events, likely due to thermal overload or communication failure exacerbated by the faulty baseline.", "All occupancy sensors correctly reported 0 during sleep hours and 1 during active hours, confirming the issue is isolated to temperature sensor logic/calibration."], "recommended_actions": ["Immediately replace or recalibrate all temperature sensors to restore accurate environmental monitoring.", "Verify the integrity of the sensor firmware and check for unit mismatch configurations (e.g., Kelvin vs. Celsius or integer scaling factors).", "Perform a physical inspection of the kitchen temperature sensor and wiring given the history of returning 'None' values."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 62.3176953792572, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1839, "chunk_count": 23, "signals": {"room_activity": {"living_room": 400, "master_bedroom": 519, "second_bedroom": 336, "kitchen": 303, "bathroom": 48, "entrance": 233}, "attribute_frequency": {"MeasuredValue": 1156, "Occupancy": 646, "OnOff": 16, "StateValue": 7, "LockState": 5, "SystemMode": 1, "OperationalState": 1, "CurrentPositionLiftPercent100ths": 1}, "lock_state_flips": 5, "occupancy_events": 646, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\", \"entrance\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"kitchen_cook_surface\", \"entrance_occupancy\", \"living_room_occupancy\", \"master_bedroom_occupancy\", \"master_bedroom_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C17\", \"C18\", \"C19\", \"C20\", \"C21\", \"C22\"],\n  \"suspected_patterns\": [\n    \"Temperature values in Celsius are reported as scaled integers (approx. x100), showing a peak around 253°C which is physically impossible for ambient air, suggesting a sensor calibration drift or scaling error that needs verification.\",\n    \"Sudden spike in 'alarmish_count' coinciding with the activation of kitchen cook surface and lights, indicating potential overheating or fire risk logic triggering.\",\n    \"Continuous high occupancy readings at entrance during evening hours without corresponding motion events in other rooms, potentially indicating unauthorized entry or sensor malfunction.\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunks C17-C18 show the specific event sequence: Kitchen light turns on, followed immediately by cook surface activation and a massive jump in alarm count, while temperature sensors report extreme values.\",\n    \"Chunks C19-C22 cover the subsequent evening period where these anomalous conditions persist or evolve, requiring inspection to determine if it was a transient glitch or an ongoing safety threat.\",\n    \"These chunks contain the highest concentration of non-temperature events (OnOff states) and the most erratic temperature data points compared to the stable overnight baseline in earlier chunks.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "living_room", "entrance"], "focus_devices": ["kitchen_temp_sensor", "kitchen_cook_surface", "entrance_occupancy", "living_room_occupancy", "master_bedroom_occupancy", "master_bedroom_temp_sensor"], "focus_chunk_ids": ["C17", "C18", "C19", "C20", "C21", "C22"], "suspected_patterns": ["Temperature values in Celsius are reported as scaled integers (approx. x100), showing a peak around 253°C which is physically impossible for ambient air, suggesting a sensor calibration drift or scaling error that needs verification.", "Sudden spike in 'alarmish_count' coinciding with the activation of kitchen cook surface and lights, indicating potential overheating or fire risk logic triggering.", "Continuous high occupancy readings at entrance during evening hours without corresponding motion events in other rooms, potentially indicating unauthorized entry or sensor malfunction."], "why_these_chunks": ["Chunks C17-C18 show the specific event sequence: Kitchen light turns on, followed immediately by cook surface activation and a massive jump in alarm count, while temperature sensors report extreme values.", "Chunks C19-C22 cover the subsequent evening period where these anomalous conditions persist or evolve, requiring inspection to determine if it was a transient glitch or an ongoing safety threat.", "These chunks contain the highest concentration of non-temperature events (OnOff states) and the most erratic temperature data points compared to the stable overnight baseline in earlier chunks."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"System-wide sensor calibration drift or unit mismatch causing consistently high integer values.\",\n      \"evidence\": [\"All temperature sensors report values between 2240 and 2309 throughout the night, which are physically impossible for Celsius ambient air but consistent across devices.\", \"The values decrease slightly over time (from ~2300 to ~2240), mimicking a cooling trend if divided by a factor (e.g., x10 or x100).\"],\n      \"weaknesses\": [\"If these values were real temperatures (Kelvin?), the house would be at -27°C or hotter, contradicting normal summer evening conditions. If they are scaled Celsius (x10), 2250 = 225°C is still impossible for air. This suggests a persistent data error rather than a dynamic physical event.\"]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"Occupancy sensor malfunction generating false positives at the entrance.\",\n      \"evidence\": [\"Entrance occupancy reports '1' continuously from 18:44 to 23:00.\", \"No corresponding motion events in other rooms suggest residents are elsewhere, yet the entrance sensor remains active without deactivation when no one enters/leaves.\"],\n      \"weaknesses\": [\"The pattern is extremely regular; it could be a pet, a static object, or a sensor stuck in 'on' state due to firmware glitch rather than an intruder.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Fire hazard triggered by kitchen equipment with corrupted sensor feedback.\",\n      \"threat_type\": \"Fire Risk / Sensor Failure\",\n      \"evidence\": [\"At 18:49:30, the kitchen cook surface turned ON.\", \"Immediately after, temperature readings remained abnormally high (~2290-2300) instead of spiking to realistic cooking temps (if scaled correctly) or showing thermal runaway.\", \"At 19:16:00, the kitchen temp sensor reported 'None', indicating a total communication loss or hardware failure right after the cooking session.\", \"The triage output noted a spike in 'alarmish_count' coinciding with this event, though the raw log doesn't show the alarm flag explicitly, the context implies safety logic was engaged.\"],\n      \"weaknesses\": [\"The temperature values never showed a sharp *increase* relative to baseline during cooking; they stayed flat/high. If the baseline is already broken, we cannot confirm overheating based on delta.\"]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Unauthorized entry simulation or sensor spoofing.\",\n      \"threat_type\": \"Breach / Intrusion\",\n      \"evidence\": [\"Continuous '1' reading at entrance_occupancy while all other room occupancies fluctuate normally or drop to 0.\", \"At 22:50:22, the front door lock operated automatically (LockOperationType=0), followed immediately by manual locking (Type=1). This sequence is unusual for a resident who typically locks manually before leaving or upon return unless there is an external trigger.\"],\n      \"weaknesses\": [\"Automatic lock operation (Type=0) often occurs when a window closes or a specific automation rule triggers, not necessarily an intrusion. The subsequent manual lock by UserIndex=5 confirms human presence nearby.\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The absolute impossibility of all temperature readings (>2000) regardless of time or activity, strongly pointing to a systemic scaling error or sensor fault rather than environmental anomalies.\",\n    \"The specific sequence in C21 where the front door lock performs an automatic operation immediately before manual locking, combined with continuous entrance occupancy, creates the strongest correlation for a potential breach scenario, even if likely automated.\"\n  ],\n  \"missing_information\": [\n    \"The actual numeric value of the 'alarmish_count' mentioned in the Triage Output to determine if a fire alert was actually triggered.\",\n    \"Calibration settings for the temperature sensors to understand if the x10/x100 hypothesis is confirmed.\",\n    \"Logs for the 'front_door_contact' prior to the automatic lock event to see if a window or sensor triggered the auto-lock.\"]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "System-wide sensor calibration drift or unit mismatch causing consistently high integer values.", "evidence": ["All temperature sensors report values between 2240 and 2309 throughout the night, which are physically impossible for Celsius ambient air but consistent across devices.", "The values decrease slightly over time (from ~2300 to ~2240), mimicking a cooling trend if divided by a factor (e.g., x10 or x100)."], "weaknesses": ["If these values were real temperatures (Kelvin?), the house would be at -27°C or hotter, contradicting normal summer evening conditions. If they are scaled Celsius (x10), 2250 = 225°C is still impossible for air. This suggests a persistent data error rather than a dynamic physical event."]}, {"id": "N2", "description": "Occupancy sensor malfunction generating false positives at the entrance.", "evidence": ["Entrance occupancy reports '1' continuously from 18:44 to 23:00.", "No corresponding motion events in other rooms suggest residents are elsewhere, yet the entrance sensor remains active without deactivation when no one enters/leaves."], "weaknesses": ["The pattern is extremely regular; it could be a pet, a static object, or a sensor stuck in 'on' state due to firmware glitch rather than an intruder."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Fire hazard triggered by kitchen equipment with corrupted sensor feedback.", "threat_type": "Fire Risk / Sensor Failure", "evidence": ["At 18:49:30, the kitchen cook surface turned ON.", "Immediately after, temperature readings remained abnormally high (~2290-2300) instead of spiking to realistic cooking temps (if scaled correctly) or showing thermal runaway.", "At 19:16:00, the kitchen temp sensor reported 'None', indicating a total communication loss or hardware failure right after the cooking session.", "The triage output noted a spike in 'alarmish_count' coinciding with this event, though the raw log doesn't show the alarm flag explicitly, the context implies safety logic was engaged."], "weaknesses": ["The temperature values never showed a sharp *increase* relative to baseline during cooking; they stayed flat/high. If the baseline is already broken, we cannot confirm overheating based on delta."]}, {"id": "A2", "description": "Unauthorized entry simulation or sensor spoofing.", "threat_type": "Breach / Intrusion", "evidence": ["Continuous '1' reading at entrance_occupancy while all other room occupancies fluctuate normally or drop to 0.", "At 22:50:22, the front door lock operated automatically (LockOperationType=0), followed immediately by manual locking (Type=1). This sequence is unusual for a resident who typically locks manually before leaving or upon return unless there is an external trigger."], "weaknesses": ["Automatic lock operation (Type=0) often occurs when a window closes or a specific automation rule triggers, not necessarily an intrusion. The subsequent manual lock by UserIndex=5 confirms human presence nearby."]}], "most_discriminative_evidence": ["The absolute impossibility of all temperature readings (>2000) regardless of time or activity, strongly pointing to a systemic scaling error or sensor fault rather than environmental anomalies.", "The specific sequence in C21 where the front door lock performs an automatic operation immediately before manual locking, combined with continuous entrance occupancy, creates the strongest correlation for a potential breach scenario, even if likely automated."], "missing_information": ["The actual numeric value of the 'alarmish_count' mentioned in the Triage Output to determine if a fire alert was actually triggered.", "Calibration settings for the temperature sensors to understand if the x10/x100 hypothesis is confirmed.", "Logs for the 'front_door_contact' prior to the automatic lock event to see if a window or sensor triggered the auto-lock."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\"],\n  \"missing_checks\": [\n    \"Verify baseline temperature readings in early evening chunks (C00-C04) to confirm if the ~2290 value is a sudden spike or a persistent system error from the start of logging.\",\n    \"Exhaustive review of 'front_door_contact' logs in chunks prior to the automatic lock event (specifically C17-C21) to rule out window-triggered automation.\",\n    \"Check for any other 'alarmish_count' spikes in chunks outside C17-C22 to determine if this was an isolated incident or part of a recurring pattern.\",\n    \"Cross-reference UserIndex=5's manual lock time with the automatic lock time in C21 to confirm user presence and intent.\"\n  ],\n  \"supervisor_notes\": [\n    \"The Investigator correctly identified the likely sensor scaling error but has not yet ruled out whether this error existed before the suspected anomaly window. Evidence in C00-C04 is required to establish the true baseline.\",\n    \"The hypothesis regarding unauthorized entry relies heavily on the specific sequence in C21. While plausible, it must be corroborated by checking if the automatic lock was triggered by environmental factors (windows/contacts) documented in the earlier chunks leading up to C17.\",\n    \"The current evidence set focuses only on the post-incident period (C17-C22). To fully assess safety response needs, we must confirm if the kitchen sensor failure persisted through the night or resolved itself, which requires reviewing the full timeline including the pre-event baseline.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C00", "C01", "C02", "C03", "C04"], "missing_checks": ["Verify baseline temperature readings in early evening chunks (C00-C04) to confirm if the ~2290 value is a sudden spike or a persistent system error from the start of logging.", "Exhaustive review of 'front_door_contact' logs in chunks prior to the automatic lock event (specifically C17-C21) to rule out window-triggered automation.", "Check for any other 'alarmish_count' spikes in chunks outside C17-C22 to determine if this was an isolated incident or part of a recurring pattern.", "Cross-reference UserIndex=5's manual lock time with the automatic lock time in C21 to confirm user presence and intent."], "supervisor_notes": ["The Investigator correctly identified the likely sensor scaling error but has not yet ruled out whether this error existed before the suspected anomaly window. Evidence in C00-C04 is required to establish the true baseline.", "The hypothesis regarding unauthorized entry relies heavily on the specific sequence in C21. While plausible, it must be corroborated by checking if the automatic lock was triggered by environmental factors (windows/contacts) documented in the earlier chunks leading up to C17.", "The current evidence set focuses only on the post-incident period (C17-C22). To fully assess safety response needs, we must confirm if the kitchen sensor failure persisted through the night or resolved itself, which requires reviewing the full timeline including the pre-event baseline."]}, "preview_triage_prompt": "## Query\n请根据以下设备日志，评估家庭当前是否需要采取任何安全响应措施。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 400,\n    \"master_bedroom\": 519,\n    \"second_bedroom\": 336,\n    \"kitchen\": 303,\n    \"bathroom\": 48,\n    \"entrance\": 233\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1156,\n    \"Occupancy\": 646,\n    \"OnOff\": 16,\n    \"StateValue\": 7,\n    \"LockState\": 5,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"CurrentPositionLiftPercent100ths\": 1\n  },\n  \"lock_state_flips\": 5,\n  \"occupancy_events\": 646,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-17T00:00:00\",\n    \"end_ts\": \"2026-06-17T01:20:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 20,\n      \"master_bedroom\": 19,\n      \"second_bedroom\": 19,\n      \"kitchen\": 16,\n      \"bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"master_bedroom_occupancy\"\n    ],\n    \"alarmish_count\": 15,\n    \"preview_lines\": [\n      \"[2026-06-17T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2273\",\n      \"[2026-06-17T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2279\",\n      \"[2026-06-17T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2272\",\n      \"[2026-06-17T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2273\",\n      \"[2026-06-17T00:00:00] living_room_o", "preview_verifier_prompt": "## Query\n请根据以下设备日志，评估家庭当前是否需要采取任何安全响应措施。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\", \"entrance\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"kitchen_cook_surface\", \"entrance_occupancy\", \"living_room_occupancy\", \"master_bedroom_occupancy\", \"master_bedroom_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C17\", \"C18\", \"C19\", \"C20\", \"C21\", \"C22\"],\n  \"suspected_patterns\": [\n    \"Temperature values in Celsius are reported as scaled integers (approx. x100), showing a peak around 253°C which is physically impossible for ambient air, suggesting a sensor calibration drift or scaling error that needs verification.\",\n    \"Sudden spike in 'alarmish_count' coinciding with the activation of kitchen cook surface and lights, indicating potential overheating or fire risk logic triggering.\",\n    \"Continuous high occupancy readings at entrance during evening hours without corresponding motion events in other rooms, potentially indicating unauthorized entry or sensor malfunction.\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunks C17-C18 show the specific event sequence: Kitchen light turns on, followed immediately by cook surface activation and a massive jump in alarm count, while temperature sensors report extreme values.\",\n    \"Chunks C19-C22 cover the subsequent evening period where these anomalous conditions persist or evolve, requiring inspection to determine if it was a transient glitch or an ongoing safety threat.\",\n    \"These chunks contain the highest concentration of non-temperature events (OnOff states) and the most erratic temperature data points compared to the stable overnight baseline in earlier chunks.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"System-wide sensor calibration drift or unit mismatch causing consistently high integer values.\",\n      \"evidence\": [\"All temperature sensors report values between 2240 and 2309 throughout the night, which are physically impossible for Celsius ambient air but consistent across devices.\", \"The values decrease slightly over time (from ~2300 to ~2240), mimicking a cooling trend if divided by a factor (e.g., x10 or x100).\"],\n      \"weaknesses\": [\"If these values were real temperatures (Kelvin?), the house would be at -27°C or hotter, contradicting normal summer evening conditions. If they are scaled Celsius (x10), 2250 = 225°C is still impossible for air. This suggests a persistent data error rather than a dynamic physical event.\"]\n"}}
{"episode_id": "SQ5_FP_B_1124", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq5\\SQ5_FP_B_1124.json", "metadata": {"sq_type": "SQ5", "sq_name": "应急响应规划", "variant": "FP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "young_professional", "base_date": "2026-06-09T00:00:00", "seed": 20261753, "scenario_id": "WD-01", "total_events": 1665, "anomaly_events_count": 4}, "ground_truth": {"scenario_id": "WD-01-FP", "scenario_name": "WD-01-FP: 洗澡溅水", "category": "water_damage", "is_anomaly": false, "threat_type": "none", "key_difference": "有人在卫生间正常使用中触发，且短时间内恢复为 false", "difficulty_score": 6, "difficulty_level": 1, "difficulty_label": "L1_basic_detection", "difficulty_dimensions": {"D1_evidence_count": 1, "D2_signal_directness": 1, "D3_cross_device": 1, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "bathroom", "injection_time": "2026-06-09T08:35:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"The temperature sensor in the kitchen and other rooms is reporting physically impossible values (2400-2700) due to a calibration failure or unit encoding error, resulting in invalid safety data.\",\n  \"reasoning\": [\n      \"Baseline morning temperatures (~2270) are consistent with a raw ADC count or offset value for ~23°C, as standard Celsius readings would be lethal (-190°C).\",\n      \"During the evening event, the kitchen sensor spiked to 2707 while the living room remained stable at ~2300; if these were valid Celsius degrees, the house would have been incinerated by fire.\",\n      \"The sensor returned 'None' immediately after the peak (18:52:00), indicating hardware saturation or disconnection, which confirms a physical malfunction rather than an environmental heat wave.\",\n      \"All other device logs (occupancy, lights, locks) function normally, isolating the anomaly strictly to the temperature measurement subsystem.\"\n    ],\n  \"key_evidence\": [\n      \"Kitchen temp jumped from ~2600 to 2707 while other rooms stayed around 2300, proving the high reading is localized and invalid.\",\n      \"Temperature values returned 'None' at 18:52:00 and 19:38:00 following peaks, confirming sensor overload or failure.\",\n      \"No smoke detectors or carbon monoxide sensors triggered during the period when temperatures were ostensibly over 2400°C.\"\n    ],\n  \"recommended_actions\": [\n      \"Immediately replace or recalibrate the kitchen temperature sensor and verify all other temperature sensors for similar drift.\",\n      \"Check the firmware version of the smart home hub and update it, as this may be a known bug in the data parsing protocol.\",\n      \"Visually inspect the kitchen area for any signs of appliance overheating or electrical issues that might have caused the sensor to fail.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "The temperature sensor in the kitchen and other rooms is reporting physically impossible values (2400-2700) due to a calibration failure or unit encoding error, resulting in invalid safety data.", "reasoning": ["Baseline morning temperatures (~2270) are consistent with a raw ADC count or offset value for ~23°C, as standard Celsius readings would be lethal (-190°C).", "During the evening event, the kitchen sensor spiked to 2707 while the living room remained stable at ~2300; if these were valid Celsius degrees, the house would have been incinerated by fire.", "The sensor returned 'None' immediately after the peak (18:52:00), indicating hardware saturation or disconnection, which confirms a physical malfunction rather than an environmental heat wave.", "All other device logs (occupancy, lights, locks) function normally, isolating the anomaly strictly to the temperature measurement subsystem."], "key_evidence": ["Kitchen temp jumped from ~2600 to 2707 while other rooms stayed around 2300, proving the high reading is localized and invalid.", "Temperature values returned 'None' at 18:52:00 and 19:38:00 following peaks, confirming sensor overload or failure.", "No smoke detectors or carbon monoxide sensors triggered during the period when temperatures were ostensibly over 2400°C."], "recommended_actions": ["Immediately replace or recalibrate the kitchen temperature sensor and verify all other temperature sensors for similar drift.", "Check the firmware version of the smart home hub and update it, as this may be a known bug in the data parsing protocol.", "Visually inspect the kitchen area for any signs of appliance overheating or electrical issues that might have caused the sensor to fail."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 58.42751979827881, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1665, "chunk_count": 21, "signals": {"room_activity": {"living_room": 400, "master_bedroom": 336, "second_bedroom": 336, "kitchen": 298, "bathroom": 63, "entrance": 232}, "attribute_frequency": {"MeasuredValue": 1154, "Occupancy": 479, "OnOff": 15, "StateValue": 7, "LockState": 4, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 4, "occupancy_events": 479, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"temperature_sensor\", \"occupancy_sensor\", \"door_lock\"],\n  \"focus_chunk_ids\": [\"C00\", \"C04\", \"C15\", \"C16\", \"C17\", \"C20\"],\n  \"suspected_patterns\": [\n    \"Critical temperature spike (22xx -> 25xx) in kitchen correlating with high occupancy and low lock flips.\",\n    \"Potential fire hazard indicated by sustained high temperatures in the absence of smoke alarm triggers in preview logs.\",\n    \"Inconsistent state reporting: High 'MeasuredValue' for temperature sensors often suggests a unit fault or calibration drift rather than actual environmental heat, but must be verified against safety thresholds.\"\n  ],\n  \"why_these_chunks\": [\n    \"C00-C03 show baseline temperatures around 22-23 degrees Celsius with no anomalies.\",\n    \"C04 marks the onset of the anomaly where kitchen temperature jumps to ~24.5 degrees while occupancy is zero.\",\n    \"C15-C17 show the peak anomaly where kitchen temperature reaches 25+ degrees while entrance/living room occupancy is high, suggesting potential appliance failure or sensor malfunction leading to a safety risk assessment.\",\n    \"C20 shows the temperature stabilizing but still elevated compared to the start of the day, requiring verification if this is a persistent fault.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen"], "focus_devices": ["temperature_sensor", "occupancy_sensor", "door_lock"], "focus_chunk_ids": ["C00", "C04", "C15", "C16", "C17", "C20"], "suspected_patterns": ["Critical temperature spike (22xx -> 25xx) in kitchen correlating with high occupancy and low lock flips.", "Potential fire hazard indicated by sustained high temperatures in the absence of smoke alarm triggers in preview logs.", "Inconsistent state reporting: High 'MeasuredValue' for temperature sensors often suggests a unit fault or calibration drift rather than actual environmental heat, but must be verified against safety thresholds."], "why_these_chunks": ["C00-C03 show baseline temperatures around 22-23 degrees Celsius with no anomalies.", "C04 marks the onset of the anomaly where kitchen temperature jumps to ~24.5 degrees while occupancy is zero.", "C15-C17 show the peak anomaly where kitchen temperature reaches 25+ degrees while entrance/living room occupancy is high, suggesting potential appliance failure or sensor malfunction leading to a safety risk assessment.", "C20 shows the temperature stabilizing but still elevated compared to the start of the day, requiring verification if this is a persistent fault."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The temperature readings are valid but reflect a significant external heatwave or solar load event, causing indoor temperatures to rise across all zones during the day (C04) and remain elevated in the evening before cooling down.\",\n      \"evidence\": [\"All room sensors show correlated increases in 'MeasuredValue' from ~2270-2300 (morning baseline) to ~2450-2500 (midday peak), consistent with passive heating.\", \"Evening logs (C16-C17) show a natural return to normal ranges (~2250-2300) after appliances were turned off, suggesting thermal inertia rather than sensor failure.\", \"Occupancy patterns align with human activity cycles (empty house at night/morning, active in evening).\"],\n      \"weaknesses\": [\"The magnitude of the increase (approx. +200 units per hour) is physically unrealistic for ambient air temperature unless the unit represents Kelvin (which would imply -90°C to -60°C changes) or a raw ADC value mislabeled as Celsius. Standard household sensors do not report values in the 2400+ range for Celsius.\"],\n      \"threat_level\": \"Low\"\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Critical Sensor Calibration Failure / Unit Fault: The 'TemperatureMeasurement.MeasuredValue' attribute is reporting values in an incorrect scale (likely raw integer/ADC counts instead of degrees Celsius), rendering all environmental data invalid for safety assessment.\",\n      \"evidence\": [\"Baseline morning temps are ~2270-2300. A standard summer morning temp should be ~22-23°C. If this were Celsius, it would be lethal (-100°C+).\", \"Midday spike reaches ~2700. If Celsius, this is physically impossible for a residential kitchen without immediate catastrophic destruction.\", \"Evening recovery drops to ~2250. If Celsius, this implies the house cooled from 1000°C back to near-freezing levels instantly upon turning off the stove.\", \"Other attributes like 'Occupancy' (0 or 1) and 'OnOff' (True/False) function correctly, isolating the error to the numeric temperature encoding.\"],\n      \"threat_type\": \"Data Integrity Error (Non-Safety Threat)\",\n      \"evidence_weaknesses\": [\"The system may have a hidden multiplier (e.g., dividing by 10) that was not applied in the log export, masking the true Celsius value.\", \"There is no explicit 'Unit' field in the log to confirm the expected scale.\"],\n      \"threat_level\": \"None (Operational Risk)\"\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Appliance Overheating Event (Hypothetical): Assuming the numbers *are* valid (e.g., a specific industrial protocol offset), the kitchen experienced a dangerous temperature spike requiring investigation.\",\n      \"evidence\": [\"Kitchen sensor jumps to 2639 while living rooms stay stable at ~2300.\", \"This coincides with 'kitchen_cook_surface' turning ON at 18:51:30 and reaching peak shortly after.\", \"Sensor returns 'None' at 18:52:00 and 19:38:00, indicating potential hardware overload or disconnection during the high-heat event.\"],\n      \"threat_type\": \"Fire Hazard / Equipment Failure\",\n      \"evidence_weaknesses\": [\"The absolute values are still inconsistent with any known temperature scale for domestic use; if these are real temperatures, the house burned down.\", \"No smoke alarm triggers ('SmokeDetector') or fire suppression events are logged in the provided chunks.\"],\n      \"threat_level\": \"Medium (Conditional on Data Validity)\"\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The magnitude of the numerical change (~2000 units over 4 hours) is incompatible with physical reality for Celsius temperature in a residential setting.\",\n    \"Correlation between 'kitchen_cook_surface' activation and the start of the anomalous high readings in C15, despite the global nature of the other spikes in C04.\",\n    \"Presence of `None` values for temperature immediately following peaks (18:52:00, 19:38:00), suggesting sensor saturation or disconnect.\"\n  ],\n  \"missing_information\": [\n    \"Definition of the unit for 'TemperatureMeasurement.MeasuredValue' (Celsius, Fahrenheit, Kelvin, or Raw ADC?).\",\n    \"Historical baseline data to determine if 2270 is a known 'zero-point' offset for this specific device model.\",\n    \"Logs from Smoke Detectors or Carbon Monoxide sensors to rule out actual combustion events.\",\n    \"Device firmware version and calibration history for the kitchen temperature sensor.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "The temperature readings are valid but reflect a significant external heatwave or solar load event, causing indoor temperatures to rise across all zones during the day (C04) and remain elevated in the evening before cooling down.", "evidence": ["All room sensors show correlated increases in 'MeasuredValue' from ~2270-2300 (morning baseline) to ~2450-2500 (midday peak), consistent with passive heating.", "Evening logs (C16-C17) show a natural return to normal ranges (~2250-2300) after appliances were turned off, suggesting thermal inertia rather than sensor failure.", "Occupancy patterns align with human activity cycles (empty house at night/morning, active in evening)."], "weaknesses": ["The magnitude of the increase (approx. +200 units per hour) is physically unrealistic for ambient air temperature unless the unit represents Kelvin (which would imply -90°C to -60°C changes) or a raw ADC value mislabeled as Celsius. Standard household sensors do not report values in the 2400+ range for Celsius."], "threat_level": "Low"}], "anomaly_hypotheses": [{"id": "A1", "description": "Critical Sensor Calibration Failure / Unit Fault: The 'TemperatureMeasurement.MeasuredValue' attribute is reporting values in an incorrect scale (likely raw integer/ADC counts instead of degrees Celsius), rendering all environmental data invalid for safety assessment.", "evidence": ["Baseline morning temps are ~2270-2300. A standard summer morning temp should be ~22-23°C. If this were Celsius, it would be lethal (-100°C+).", "Midday spike reaches ~2700. If Celsius, this is physically impossible for a residential kitchen without immediate catastrophic destruction.", "Evening recovery drops to ~2250. If Celsius, this implies the house cooled from 1000°C back to near-freezing levels instantly upon turning off the stove.", "Other attributes like 'Occupancy' (0 or 1) and 'OnOff' (True/False) function correctly, isolating the error to the numeric temperature encoding."], "threat_type": "Data Integrity Error (Non-Safety Threat)", "evidence_weaknesses": ["The system may have a hidden multiplier (e.g., dividing by 10) that was not applied in the log export, masking the true Celsius value.", "There is no explicit 'Unit' field in the log to confirm the expected scale."], "threat_level": "None (Operational Risk)"}, {"id": "A2", "description": "Appliance Overheating Event (Hypothetical): Assuming the numbers *are* valid (e.g., a specific industrial protocol offset), the kitchen experienced a dangerous temperature spike requiring investigation.", "evidence": ["Kitchen sensor jumps to 2639 while living rooms stay stable at ~2300.", "This coincides with 'kitchen_cook_surface' turning ON at 18:51:30 and reaching peak shortly after.", "Sensor returns 'None' at 18:52:00 and 19:38:00, indicating potential hardware overload or disconnection during the high-heat event."], "threat_type": "Fire Hazard / Equipment Failure", "evidence_weaknesses": ["The absolute values are still inconsistent with any known temperature scale for domestic use; if these are real temperatures, the house burned down.", "No smoke alarm triggers ('SmokeDetector') or fire suppression events are logged in the provided chunks."], "threat_level": "Medium (Conditional on Data Validity)"}], "most_discriminative_evidence": ["The magnitude of the numerical change (~2000 units over 4 hours) is incompatible with physical reality for Celsius temperature in a residential setting.", "Correlation between 'kitchen_cook_surface' activation and the start of the anomalous high readings in C15, despite the global nature of the other spikes in C04.", "Presence of `None` values for temperature immediately following peaks (18:52:00, 19:38:00), suggesting sensor saturation or disconnect."], "missing_information": ["Definition of the unit for 'TemperatureMeasurement.MeasuredValue' (Celsius, Fahrenheit, Kelvin, or Raw ADC?).", "Historical baseline data to determine if 2270 is a known 'zero-point' offset for this specific device model.", "Logs from Smoke Detectors or Carbon Monoxide sensors to rule out actual combustion events.", "Device firmware version and calibration history for the kitchen temperature sensor."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C05\", \"C21\"],\n  \"missing_checks\": [\n    \"Verify sensor unit definition (Celsius vs Raw ADC) in device metadata or firmware logs.\",\n    \"Cross-reference with Smoke Detector and CO Sensor logs to rule out actual fire events.\",\n    \"Check for 'None' values or saturation errors immediately following the temperature spike peaks.\"\n  ],\n  \"supervisor_notes\": [\n    \"The investigation correctly identified that the raw numerical values (~2270-2700) are physically impossible for Celsius temperatures in a home, pointing strongly to a sensor calibration or unit encoding error rather than a real heat hazard.\",\n    \"However, the current evidence is insufficient to definitively classify this as a non-safety data integrity issue without ruling out rare edge cases (e.g., specific industrial protocol offsets).\",\n    \"Additional chunks C05 and C21 are needed to confirm if the 'None' values (sensor disconnect/saturation) persist after the peak, which would validate the hardware fault hypothesis.\",\n    \"Crucially, the provided chunk list only goes up to C20. The Investigator requested historical baseline data (potentially earlier than C00) and explicit Smoke/CO logs which were not included in the selected chunks. The supervisor must flag that the available log range may be too narrow to establish a full baseline trend without assuming C00-C03 represent the entire history.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C05", "C21"], "missing_checks": ["Verify sensor unit definition (Celsius vs Raw ADC) in device metadata or firmware logs.", "Cross-reference with Smoke Detector and CO Sensor logs to rule out actual fire events.", "Check for 'None' values or saturation errors immediately following the temperature spike peaks."], "supervisor_notes": ["The investigation correctly identified that the raw numerical values (~2270-2700) are physically impossible for Celsius temperatures in a home, pointing strongly to a sensor calibration or unit encoding error rather than a real heat hazard.", "However, the current evidence is insufficient to definitively classify this as a non-safety data integrity issue without ruling out rare edge cases (e.g., specific industrial protocol offsets).", "Additional chunks C05 and C21 are needed to confirm if the 'None' values (sensor disconnect/saturation) persist after the peak, which would validate the hardware fault hypothesis.", "Crucially, the provided chunk list only goes up to C20. The Investigator requested historical baseline data (potentially earlier than C00) and explicit Smoke/CO logs which were not included in the selected chunks. The supervisor must flag that the available log range may be too narrow to establish a full baseline trend without assuming C00-C03 represent the entire history."]}, "preview_triage_prompt": "## Query\n请根据以下设备日志，评估家庭当前是否需要采取任何安全响应措施。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 400,\n    \"master_bedroom\": 336,\n    \"second_bedroom\": 336,\n    \"kitchen\": 298,\n    \"bathroom\": 63,\n    \"entrance\": 232\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1154,\n    \"Occupancy\": 479,\n    \"OnOff\": 15,\n    \"StateValue\": 7,\n    \"LockState\": 4,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 479,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-09T00:00:00\",\n    \"end_ts\": \"2026-06-09T01:20:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 20,\n      \"master_bedroom\": 19,\n      \"second_bedroom\": 19,\n      \"kitchen\": 16,\n      \"bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"master_bedroom_occupancy\"\n    ],\n    \"alarmish_count\": 15,\n    \"preview_lines\": [\n      \"[2026-06-09T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2274\",\n      \"[2026-06-09T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2263\",\n      \"[2026-06-09T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2263\",\n      \"[2026-06-09T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2277\",\n      \"[2026-06-09T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",", "preview_verifier_prompt": "## Query\n请根据以下设备日志，评估家庭当前是否需要采取任何安全响应措施。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"temperature_sensor\", \"occupancy_sensor\", \"door_lock\"],\n  \"focus_chunk_ids\": [\"C00\", \"C04\", \"C15\", \"C16\", \"C17\", \"C20\"],\n  \"suspected_patterns\": [\n    \"Critical temperature spike (22xx -> 25xx) in kitchen correlating with high occupancy and low lock flips.\",\n    \"Potential fire hazard indicated by sustained high temperatures in the absence of smoke alarm triggers in preview logs.\",\n    \"Inconsistent state reporting: High 'MeasuredValue' for temperature sensors often suggests a unit fault or calibration drift rather than actual environmental heat, but must be verified against safety thresholds.\"\n  ],\n  \"why_these_chunks\": [\n    \"C00-C03 show baseline temperatures around 22-23 degrees Celsius with no anomalies.\",\n    \"C04 marks the onset of the anomaly where kitchen temperature jumps to ~24.5 degrees while occupancy is zero.\",\n    \"C15-C17 show the peak anomaly where kitchen temperature reaches 25+ degrees while entrance/living room occupancy is high, suggesting potential appliance failure or sensor malfunction leading to a safety risk assessment.\",\n    \"C20 shows the temperature stabilizing but still elevated compared to the start of the day, requiring verification if this is a persistent fault.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"The temperature readings are valid but reflect a significant external heatwave or solar load event, causing indoor temperatures to rise across all zones during the day (C04) and remain elevated in the evening before cooling down.\",\n      \"evidence\": [\"All room sensors show correlated increases in 'MeasuredValue' from ~2270-2300 (morning baseline) to ~2450-2500 (midday peak), consistent with passive heating.\", \"Evening logs (C16-C17) show a natural return to normal ranges (~2250-2300) after appliances were turned off, suggesting thermal inertia rather than sensor failure.\", \"Occupancy patterns align with human activity cycles (empty house at night/morning, active in evening).\"],\n      \"weaknesses\": [\"The magnitude of the increase (approx. +200 units per hour) is physically unrealistic for ambient air temperature unless the unit represents Kelvin (which would imply -90°C to -60°C changes) or a raw ADC value mislabeled as Celsius. Standard household sensors do not report values in the 2400+ range for Celsius.\"],\n      \"threat_l"}}
{"episode_id": "SQ5_TN_A_1173", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq5\\SQ5_TN_A_1173.json", "metadata": {"sq_type": "SQ5", "sq_name": "应急响应规划", "variant": "TN", "layout_id": "A", "layout_name": "一室一厅 (Studio/1BR)", "profile_id": "young_professional", "base_date": "2026-06-05T00:00:00", "seed": 20261802, "scenario_id": null, "total_events": 1119, "anomaly_events_count": 0}, "ground_truth": {"scenario_id": "TN", "scenario_name": "Normal — no anomaly", "category": "none", "is_anomaly": false, "threat_type": "none", "variant": "TN", "difficulty_score": 0, "difficulty_level": 0, "difficulty_label": "TN_baseline", "difficulty_dimensions": {"D1_evidence_count": 0, "D2_signal_directness": 0, "D3_cross_device": 0, "D4_temporal_span": 0, "D5_fp_similarity": 0}}, "raw_response": "{\n  \"is_anomaly\": false,\n  \"confidence\": \"medium\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"The event was a benign window opening by a resident coinciding with an unrelated sensor data anomaly, as confirmed by normal post-event stability and lack of forced entry indicators.\",\n  \"reasoning\": [\n      \"Step 1: The critical event at 19:43:30 shows the kitchen window contact state changing to False (Open), which initially raises security concerns given the presence of occupants in the living room.\",\n      \"Step 2: Analysis of C10 reveals no prior 'LockState' flips or alarm triggers before the window opened, suggesting it was not part of a break-in sequence or forced entry attempt; furthermore, residents were present nearby, making manual ventilation highly probable.\",\n      \"Step 3: Post-event logs (C11/C12) show that temperature readings recovered quickly and stabilized within a normal range, while occupancy remained consistent, indicating no sustained intrusion or environmental hazard; the initial 'None' reading and subsequent spike are attributed to transient sensor malfunction rather than physical tampering.\",\n      \"key_evidence\": [\n          \"kitchen_window_contact transitioned to False at 19:43:30 without accompanying LockState changes or alarm events.\",\n          \"Temperature sensors recovered stable readings (approx. 22-26°C equivalent) within minutes of the window opening, inconsistent with a significant breach.\",\n          \"Occupancy sensors continuously confirmed residents were active in the living room during the window opening event.\"\n      ],\n      \"recommended_actions\": [\n          \"Verify the functionality of the kitchen temperature sensor if future anomalies occur.\",\n          \"No immediate security response required; continue standard monitoring.\"\n      ]\n}", "model_response": {"is_anomaly": null, "confidence": "unknown", "threat_type": "parse_failed", "reasoning": ["{\n  \"is_anomaly\": false,\n  \"confidence\": \"medium\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"The event was a benign window opening by a resident coinciding with an unrelated sensor data anomaly, as confirmed by normal post-event stability and lack of forced entry indicators.\",\n  \"reasoning\": [\n      \"Step 1: The critical event at 19:43:30 shows the kitchen window contact state changing to False (Open), which initially raises security concerns given the presence of occupants"], "_parse_failed": true}, "scores": {"parse_success": false, "detection_correct": false, "detection_label": "UNPARSEABLE", "is_miss": false, "is_false_alarm": false, "threat_type_correct": null, "reasoning_steps": 1, "has_evidence": false, "has_actions": false, "confidence": "unknown"}, "latency": 48.82313394546509, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1119, "chunk_count": 14, "signals": {"room_activity": {"living_room": 401, "bedroom": 353, "kitchen": 298, "bathroom": 53, "entrance": 14}, "attribute_frequency": {"MeasuredValue": 866, "Occupancy": 217, "OnOff": 18, "StateValue": 5, "LockState": 4, "CurrentPositionLiftPercent100ths": 2, "SystemMode": 1, "OperationalState": 1, "CurrentLevel": 1}, "lock_state_flips": 4, "occupancy_events": 217, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"single-event-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_window_contact\", \"kitchen_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C11\"],\n  \"suspected_patterns\": [\n    \"Kitchen window opened while occupants are present in the living room\",\n    \"Sensor data loss (None) coinciding with security event\",\n    \"Rapid temperature fluctuation potentially indicating HVAC response to open window or external environment\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C11 is the only chunk containing a critical security state change: 'kitchen_window_contact' transitioning to False (open) at 19:43:30.\",\n    \"This event occurred while occupancy sensors confirmed residents were active in the living room ('Occupancy = 1'), creating a potential security vulnerability.\",\n    \"The concurrent 'TemperatureMeasurement.MeasuredValue = None' suggests a sensor failure or disconnection, which complicates thermal monitoring and requires immediate verification.\",\n    \"Other chunks show stable environmental readings or normal occupancy patterns without triggering safety alarms.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "single-event-safety", "focus_rooms": ["kitchen"], "focus_devices": ["kitchen_window_contact", "kitchen_temp_sensor"], "focus_chunk_ids": ["C11"], "suspected_patterns": ["Kitchen window opened while occupants are present in the living room", "Sensor data loss (None) coinciding with security event", "Rapid temperature fluctuation potentially indicating HVAC response to open window or external environment"], "why_these_chunks": ["Chunk C11 is the only chunk containing a critical security state change: 'kitchen_window_contact' transitioning to False (open) at 19:43:30.", "This event occurred while occupancy sensors confirmed residents were active in the living room ('Occupancy = 1'), creating a potential security vulnerability.", "The concurrent 'TemperatureMeasurement.MeasuredValue = None' suggests a sensor failure or disconnection, which complicates thermal monitoring and requires immediate verification.", "Other chunks show stable environmental readings or normal occupancy patterns without triggering safety alarms."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Routine evening activity with a temporary HVAC sensor glitch.\",\n      \"evidence\": [\n        \"Occupancy sensors consistently show residents in the living room (Value=1) throughout the window open period.\",\n        \"Dishwasher activation at 20:01 suggests normal household chores are occurring.\",\n        \"Temperature readings, once recovered, remain within a plausible range for an indoor environment (approx. 22°C / 71°F if dividing by 32, or raw integer values representing standard ambient temps depending on protocol scaling).\",\n        \"The 'None' reading occurred only once before data resumed.\"\n      ],\n      \"weaknesses\": [\n        \"Does not explain the specific correlation between the window opening event and the immediate loss of temperature telemetry.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Unauthorized entry or forced entry into the kitchen while occupants were present elsewhere.\",\n      \"threat_type\": \"Physical Intrusion / Security Breach\",\n      \"evidence\": [\n        \"At 19:43:30, `kitchen_window_contact` state changed to `False` (Open).\",\n        \"This event coincided exactly with a total loss of telemetry (`MeasuredValue = None`) from the `kitchen_temp_sensor`, suggesting physical interference or power cut/disconnection upon tampering.\",\n        \"Residency was confirmed in the adjacent `living_room` immediately after the breach (19:44:17), creating a scenario where intruders could access the kitchen while residents are distracted nearby.\",\n        \"The subsequent return of temperature data shows a rapid drop from ~2636 to ~2500 over 2 minutes, which could indicate external air ingress cooling the space faster than the internal heating/HVAC can compensate.\"\n      ],\n      \"weaknesses\": [\n        \"It is possible the window was opened by a resident for ventilation and the sensor failure was unrelated hardware noise.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Sensor malfunctions causing false security alerts due to environmental factors.\",\n      \"threat_type\": \"System Fault / False Positive\",\n      \"evidence\": [\n        \"Temperature values are presented as high integers (e.g., 2636, 2266) which are physically impossible for direct Celsius readings, implying a raw integer encoding issue common in IoT logs; this might obscure real-time value interpretation.\",\n        \"The 'None' reading could be a brief network packet loss rather than physical damage.\"\n      ],\n      \"weaknesses\": [\n        \"Even if the window was opened by a resident, the simultaneous sensor blackout is highly suspicious and warrants verification to rule out tampering.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"Temporal proximity of `kitchen_window_contact = False` and `kitchen_temp_sensor.MeasuredValue = None` (30 second gap within same minute).\",\n    \"Presence of occupants in the `living_room` during the window opening event, increasing the risk factor of non-resident access.\",\n    \"Absence of any 'LockState' flip logs during this specific 19:43-19:45 window, despite the window being opened.\"\n  ],\n  \"missing_information\": [\n    \"Did the user manually acknowledge the window opening?\",\n    \"Was there any audio logging or video feed confirming who entered/operated the window?\",\n    \"Is there a history of the `kitchen_temp_sensor` frequently returning 'None' or erratic high integer values?\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Routine evening activity with a temporary HVAC sensor glitch.", "evidence": ["Occupancy sensors consistently show residents in the living room (Value=1) throughout the window open period.", "Dishwasher activation at 20:01 suggests normal household chores are occurring.", "Temperature readings, once recovered, remain within a plausible range for an indoor environment (approx. 22°C / 71°F if dividing by 32, or raw integer values representing standard ambient temps depending on protocol scaling).", "The 'None' reading occurred only once before data resumed."], "weaknesses": ["Does not explain the specific correlation between the window opening event and the immediate loss of temperature telemetry."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Unauthorized entry or forced entry into the kitchen while occupants were present elsewhere.", "threat_type": "Physical Intrusion / Security Breach", "evidence": ["At 19:43:30, `kitchen_window_contact` state changed to `False` (Open).", "This event coincided exactly with a total loss of telemetry (`MeasuredValue = None`) from the `kitchen_temp_sensor`, suggesting physical interference or power cut/disconnection upon tampering.", "Residency was confirmed in the adjacent `living_room` immediately after the breach (19:44:17), creating a scenario where intruders could access the kitchen while residents are distracted nearby.", "The subsequent return of temperature data shows a rapid drop from ~2636 to ~2500 over 2 minutes, which could indicate external air ingress cooling the space faster than the internal heating/HVAC can compensate."], "weaknesses": ["It is possible the window was opened by a resident for ventilation and the sensor failure was unrelated hardware noise."]}, {"id": "A2", "description": "Sensor malfunctions causing false security alerts due to environmental factors.", "threat_type": "System Fault / False Positive", "evidence": ["Temperature values are presented as high integers (e.g., 2636, 2266) which are physically impossible for direct Celsius readings, implying a raw integer encoding issue common in IoT logs; this might obscure real-time value interpretation.", "The 'None' reading could be a brief network packet loss rather than physical damage."], "weaknesses": ["Even if the window was opened by a resident, the simultaneous sensor blackout is highly suspicious and warrants verification to rule out tampering."]}], "most_discriminative_evidence": ["Temporal proximity of `kitchen_window_contact = False` and `kitchen_temp_sensor.MeasuredValue = None` (30 second gap within same minute).", "Presence of occupants in the `living_room` during the window opening event, increasing the risk factor of non-resident access.", "Absence of any 'LockState' flip logs during this specific 19:43-19:45 window, despite the window being opened."], "missing_information": ["Did the user manually acknowledge the window opening?", "Was there any audio logging or video feed confirming who entered/operated the window?", "Is there a history of the `kitchen_temp_sensor` frequently returning 'None' or erratic high integer values?"]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C10\", \"C12\"],\n  \"missing_checks\": [\n    \"Verify state of 'kitchen_door_contact' and 'main_entry_locks' to rule out simultaneous unauthorized entry via doors.\",\n    \"Check for any 'LockState' transitions on the kitchen window or adjacent room doors during the 19:43-19:45 window.\",\n    \"Review audio/video logs (if available) around 19:43:30 to confirm if the window opening was manual or forced.\"\n  ],\n  \"supervisor_notes\": [\n    \"The investigation correctly identified the critical event in C11 (window open + sensor loss) and the occupancy context.\",\n    \"However, the evidence is currently insufficient to distinguish between a resident opening the window for ventilation vs. an intrusion attempt causing the sensor failure.\",\n    \"We need to examine C10 (immediately preceding) and C12 (immediately following) to see if there were prior door/window lock status changes or post-event alarms that might clarify the sequence of events.\",\n    \"Specifically, checking C10/C12 for 'LockState' logs is crucial because the Investigator noted the absence of lock flip logs as suspicious; we must verify if other security zones were compromised simultaneously.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C10", "C12"], "missing_checks": ["Verify state of 'kitchen_door_contact' and 'main_entry_locks' to rule out simultaneous unauthorized entry via doors.", "Check for any 'LockState' transitions on the kitchen window or adjacent room doors during the 19:43-19:45 window.", "Review audio/video logs (if available) around 19:43:30 to confirm if the window opening was manual or forced."], "supervisor_notes": ["The investigation correctly identified the critical event in C11 (window open + sensor loss) and the occupancy context.", "However, the evidence is currently insufficient to distinguish between a resident opening the window for ventilation vs. an intrusion attempt causing the sensor failure.", "We need to examine C10 (immediately preceding) and C12 (immediately following) to see if there were prior door/window lock status changes or post-event alarms that might clarify the sequence of events.", "Specifically, checking C10/C12 for 'LockState' logs is crucial because the Investigator noted the absence of lock flip logs as suspicious; we must verify if other security zones were compromised simultaneously."]}, "preview_triage_prompt": "## Query\n请根据以下设备日志，评估家庭当前是否需要采取任何安全响应措施。\n\n## Layout\nLayout: 一室一厅 (Studio/1BR)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅台灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 401,\n    \"bedroom\": 353,\n    \"kitchen\": 298,\n    \"bathroom\": 53,\n    \"entrance\": 14\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 866,\n    \"Occupancy\": 217,\n    \"OnOff\": 18,\n    \"StateValue\": 5,\n    \"LockState\": 4,\n    \"CurrentPositionLiftPercent100ths\": 2,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 217,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-05T00:00:00\",\n    \"end_ts\": \"2026-06-05T01:50:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 27,\n      \"bedroom\": 27,\n      \"kitchen\": 22,\n      \"bathroom\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"bathroom_occupancy\"\n    ],\n    \"alarmish_count\": 12,\n    \"preview_lines\": [\n      \"[2026-06-05T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2261\",\n      \"[2026-06-05T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2166\",\n      \"[2026-06-05T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2264\",\n      \"[2026-06-05T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-05T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-05T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-05T00:05:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2279\",\n      \"[2026-06-05T00:05:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2171\",\n      \"[2026-06-05T00:05:00] kitchen_temp_sensor | Temperatur", "preview_verifier_prompt": "## Query\n请根据以下设备日志，评估家庭当前是否需要采取任何安全响应措施。\n\n## Triage\n{\n  \"latent_task_profile\": \"single-event-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_window_contact\", \"kitchen_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C11\"],\n  \"suspected_patterns\": [\n    \"Kitchen window opened while occupants are present in the living room\",\n    \"Sensor data loss (None) coinciding with security event\",\n    \"Rapid temperature fluctuation potentially indicating HVAC response to open window or external environment\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C11 is the only chunk containing a critical security state change: 'kitchen_window_contact' transitioning to False (open) at 19:43:30.\",\n    \"This event occurred while occupancy sensors confirmed residents were active in the living room ('Occupancy = 1'), creating a potential security vulnerability.\",\n    \"The concurrent 'TemperatureMeasurement.MeasuredValue = None' suggests a sensor failure or disconnection, which complicates thermal monitoring and requires immediate verification.\",\n    \"Other chunks show stable environmental readings or normal occupancy patterns without triggering safety alarms.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Routine evening activity with a temporary HVAC sensor glitch.\",\n      \"evidence\": [\n        \"Occupancy sensors consistently show residents in the living room (Value=1) throughout the window open period.\",\n        \"Dishwasher activation at 20:01 suggests normal household chores are occurring.\",\n        \"Temperature readings, once recovered, remain within a plausible range for an indoor environment (approx. 22°C / 71°F if dividing by 32, or raw integer values representing standard ambient temps depending on protocol scaling).\",\n        \"The 'None' reading occurred only once before data resumed.\"\n      ],\n      \"weaknesses\": [\n        \"Does not explain the specific correlation between the window opening event and the immediate loss of temperature telemetry.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Unauthorized entry or forced entry into the kitchen while occupants were present elsewhere.\",\n      \"threat_type\": \"Physical Intrusion / Security Breach\",\n      \"evidence\": [\n        \"At 19:43:30, `kitchen_window_contact` state changed to `False` (Open).\",\n        \"This event coincided exactly with a total loss of telemetry (`MeasuredValue = None`) from the `kitchen_temp_sensor`, suggesting"}}
{"episode_id": "SQ5_TP_B_1037", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq5\\SQ5_TP_B_1037.json", "metadata": {"sq_type": "SQ5", "sq_name": "应急响应规划", "variant": "TP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "family_with_children", "base_date": "2026-06-13T00:00:00", "seed": 20261666, "scenario_id": "FG-02", "total_events": 1395, "anomaly_events_count": 3}, "ground_truth": {"scenario_id": "FG-02", "scenario_name": "电器过热起火", "category": "fire_gas", "is_anomaly": true, "threat_type": "fire_risk", "key_evidence": ["温度异常上升但无合理热源（空调关闭/制冷模式，灶具关闭）", "上升速度超过正常烹饪或日照导致的范围"], "expected_response": "火灾风险警报，建议住户检查该区域电器", "difficulty_score": 10, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 2, "D5_fp_similarity": 2}, "target_room": "kitchen", "injection_time": "2026-06-13T12:20:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"The kitchen temperature sensor experienced a hardware failure or data corruption causing an impossible instantaneous spike (2526 to 3237), which likely triggered a false positive smoke alarm event.\",\n  \"reasoning\": [\n      \"Analysis of Chunk C09 reveals a physically impossible temperature reading where the kitchen sensor jumped from 2526 to 3237 and back to 2518 within seconds, while all other room sensors remained stable around 2500-2525.\",\n      \"This instantaneous spike pattern is characteristic of sensor overflow, calibration error, or packet corruption rather than a real thermal event, as real fires would cause sustained heating in adjacent rooms.\",\n      \"The SmokeState trigger at 12:30:00 occurred shortly after the anomaly but was likely a system reaction to the invalid temperature data rather than evidence of an actual fire, especially given zero occupancy and lack of corroborating heat/smoke in other zones.\"\n    ],\n  \"key_evidence\": [\n      \"Kitchen_temp_sensor MeasuredValue spiked to 3237 then dropped to 2518 within 4 seconds (physically impossible for ambient air).\",\n      \"No corresponding temperature rise or smoke detection in living_room, master_bedroom, or second_bedroom during the incident window.\",\n      \"All occupancy sensors reported 0, indicating no human activity or cooking source was present to generate heat or smoke.\"\n    ],\n  \"recommended_actions\": [\n      \"Immediately isolate and power cycle the kitchen_temp_sensor device to clear temporary buffer errors.\",\n      \"Schedule a physical inspection of the kitchen temperature sensor for damage, misalignment, or environmental interference.\",\n      \"Review system alerting logic thresholds to ensure future extreme outlier values are filtered or flagged separately from critical safety alarms.\"\n    ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "The kitchen temperature sensor experienced a hardware failure or data corruption causing an impossible instantaneous spike (2526 to 3237), which likely triggered a false positive smoke alarm event.", "reasoning": ["Analysis of Chunk C09 reveals a physically impossible temperature reading where the kitchen sensor jumped from 2526 to 3237 and back to 2518 within seconds, while all other room sensors remained stable around 2500-2525.", "This instantaneous spike pattern is characteristic of sensor overflow, calibration error, or packet corruption rather than a real thermal event, as real fires would cause sustained heating in adjacent rooms.", "The SmokeState trigger at 12:30:00 occurred shortly after the anomaly but was likely a system reaction to the invalid temperature data rather than evidence of an actual fire, especially given zero occupancy and lack of corroborating heat/smoke in other zones."], "key_evidence": ["Kitchen_temp_sensor MeasuredValue spiked to 3237 then dropped to 2518 within 4 seconds (physically impossible for ambient air).", "No corresponding temperature rise or smoke detection in living_room, master_bedroom, or second_bedroom during the incident window.", "All occupancy sensors reported 0, indicating no human activity or cooking source was present to generate heat or smoke."], "recommended_actions": ["Immediately isolate and power cycle the kitchen_temp_sensor device to clear temporary buffer errors.", "Schedule a physical inspection of the kitchen temperature sensor for damage, misalignment, or environmental interference.", "Review system alerting logic thresholds to ensure future extreme outlier values are filtered or flagged separately from critical safety alarms."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 48.43544292449951, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1395, "chunk_count": 18, "signals": {"room_activity": {"living_room": 336, "master_bedroom": 336, "second_bedroom": 336, "kitchen": 291, "bathroom": 48, "entrance": 48}, "attribute_frequency": {"MeasuredValue": 1154, "Occupancy": 240, "SmokeState": 1}, "lock_state_flips": 0, "occupancy_events": 240, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"single-event-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C09\"],\n  \"suspected_patterns\": [\n    \"Temperature spike anomaly in kitchen sensor (jump from ~2500 to 3237 and 3200)\",\n    \"Potential sensor malfunction or calibration drift causing false high-temperature reading\",\n    \"No correlated occupancy events during the spike, suggesting no active cooking source\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C09 contains the only data points with MeasuredValue exceeding 3000 (3237, 3200), which is physically unrealistic for a standard indoor environment compared to surrounding chunks where values are around 2500.\",\n    \"This outlier indicates a potential device failure or a specific localized event requiring immediate inspection to rule out fire hazards or hardware malfunction.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "single-event-safety", "focus_rooms": ["kitchen"], "focus_devices": ["kitchen_temp_sensor"], "focus_chunk_ids": ["C09"], "suspected_patterns": ["Temperature spike anomaly in kitchen sensor (jump from ~2500 to 3237 and 3200)", "Potential sensor malfunction or calibration drift causing false high-temperature reading", "No correlated occupancy events during the spike, suggesting no active cooking source"], "why_these_chunks": ["Chunk C09 contains the only data points with MeasuredValue exceeding 3000 (3237, 3200), which is physically unrealistic for a standard indoor environment compared to surrounding chunks where values are around 2500.", "This outlier indicates a potential device failure or a specific localized event requiring immediate inspection to rule out fire hazards or hardware malfunction."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Transient sensor glitch or data corruption in the kitchen_temp_sensor device.\",\n      \"evidence\": [\"MeasuredValue spiked to 3237 and 3200 immediately after a normal reading of 2526 at 12:20:00.\", \"The value returned to normal baseline (~2500) within 2 minutes by 12:45:00.\", \"No corresponding rise in other room temperatures or smoke detection initially.\"],\n      \"weaknesses\": [\"Fails to explain why the SmokeState triggered '1' exactly at 12:30:00, shortly after the spike.\", \"Does not account for the high 'attribute_frequency' of MeasuredValue (1154) which suggests potential re-sampling or error correction attempts.\"]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"System calibration drift causing false positive readings.\",\n      \"evidence\": [\"All temperature sensors show values in the 2480-2520 range, consistent with each other but slightly elevated compared to standard indoor norms (likely Kelvin scale given magnitude).\", \"The anomaly is isolated to a single timestamp pair without sustained thermal accumulation.\"],\n      \"weaknesses\": [\"Calibration drift rarely causes instantaneous jumps followed by immediate recovery unless reset.\", \"Cannot explain the specific correlation between the temperature spike and the subsequent smoke alarm activation.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Hardware failure of kitchen_temp_sensor triggering false smoke alarm due to overflow or logic error.\",\n      \"threat_type\": \"False Positive / Hardware Fault\",\n      \"evidence\": [\"Temperature jumped from ~2500 to >3200 then dropped back down, indicating a non-physical event likely caused by sensor overflow or communication packet corruption.\", \"SmokeState = 1 appeared at 12:30:00, potentially triggered by the system interpreting the extreme temperature spike as a fire hazard.\", \"Zero occupancy events confirm no human activity or cooking source was present during the anomaly window.\", \"Other room sensors remained stable, ruling out ambient building-wide heating events.\"],\n      \"weaknesses\": [\"Relies on the assumption that the smoke alarm is directly coupled to the temperature threshold logic in the system configuration.\", \"Could be coincidental if an external factor (e.g., actual small fire) occurred but didn't heat the room enough to register on other sensors yet.\"]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Localized fire incident in the kitchen with rapid containment or sensor lag.\",\n      \"threat_type\": \"Fire Hazard (Low Confidence)\",\n      \"evidence\": [\"SmokeState = 1 is a definitive indicator of combustion particles.\", \"Kitchen temperature showed anomalous behavior (spike), which could represent localized hot spots missed by the main sensor's average calculation.\"],\n      \"weaknesses\": [\"If a fire were large enough to trigger smoke alarms, adjacent rooms (living_room, master_bedroom) should show rising temperatures or smoke states within minutes; none did.\", \"The temperature spike pattern (instant jump, instant drop) is characteristic of sensor error rather than thermal physics of a fire.\", \"Occupancy sensors show 0, meaning no one was there to report a smell or see flames, increasing reliance on automated sensors which are conflicting.\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The instantaneous nature of the temperature spike (2526 -> 3237 -> 2518 within 4 seconds) is physically impossible for real-world heating and strongly points to sensor failure or data packet corruption.\",\n    \"The temporal proximity of the temperature anomaly (12:20:00) and the SmokeState trigger (12:30:00) suggests a causal link in the system's alerting logic, even if the physical cause was a sensor fault.\",\n    \"Complete lack of corroborating data from neighboring rooms (stable temps, zero occupancy) rules out a widespread environmental event like a gas leak or major fire.\"\n  ],\n  \"missing_information\": [\n    \"Raw firmware logs or debug traces of the kitchen_temp_sensor to determine if the 3200+ values were valid measurements or internal error codes.\",\n    \"Specific logic thresholds used by the system to correlate TemperatureMeasurement spikes with SmokeState triggers.\",\n    \"Visual inspection results from the kitchen (smell of burning, visible damage, or soot) to confirm or deny the presence of actual combustion.\",\n    \"Network traffic logs to check for DDoS or injection attempts that might have corrupted the sensor data stream.\"]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Transient sensor glitch or data corruption in the kitchen_temp_sensor device.", "evidence": ["MeasuredValue spiked to 3237 and 3200 immediately after a normal reading of 2526 at 12:20:00.", "The value returned to normal baseline (~2500) within 2 minutes by 12:45:00.", "No corresponding rise in other room temperatures or smoke detection initially."], "weaknesses": ["Fails to explain why the SmokeState triggered '1' exactly at 12:30:00, shortly after the spike.", "Does not account for the high 'attribute_frequency' of MeasuredValue (1154) which suggests potential re-sampling or error correction attempts."]}, {"id": "N2", "description": "System calibration drift causing false positive readings.", "evidence": ["All temperature sensors show values in the 2480-2520 range, consistent with each other but slightly elevated compared to standard indoor norms (likely Kelvin scale given magnitude).", "The anomaly is isolated to a single timestamp pair without sustained thermal accumulation."], "weaknesses": ["Calibration drift rarely causes instantaneous jumps followed by immediate recovery unless reset.", "Cannot explain the specific correlation between the temperature spike and the subsequent smoke alarm activation."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Hardware failure of kitchen_temp_sensor triggering false smoke alarm due to overflow or logic error.", "threat_type": "False Positive / Hardware Fault", "evidence": ["Temperature jumped from ~2500 to >3200 then dropped back down, indicating a non-physical event likely caused by sensor overflow or communication packet corruption.", "SmokeState = 1 appeared at 12:30:00, potentially triggered by the system interpreting the extreme temperature spike as a fire hazard.", "Zero occupancy events confirm no human activity or cooking source was present during the anomaly window.", "Other room sensors remained stable, ruling out ambient building-wide heating events."], "weaknesses": ["Relies on the assumption that the smoke alarm is directly coupled to the temperature threshold logic in the system configuration.", "Could be coincidental if an external factor (e.g., actual small fire) occurred but didn't heat the room enough to register on other sensors yet."]}, {"id": "A2", "description": "Localized fire incident in the kitchen with rapid containment or sensor lag.", "threat_type": "Fire Hazard (Low Confidence)", "evidence": ["SmokeState = 1 is a definitive indicator of combustion particles.", "Kitchen temperature showed anomalous behavior (spike), which could represent localized hot spots missed by the main sensor's average calculation."], "weaknesses": ["If a fire were large enough to trigger smoke alarms, adjacent rooms (living_room, master_bedroom) should show rising temperatures or smoke states within minutes; none did.", "The temperature spike pattern (instant jump, instant drop) is characteristic of sensor error rather than thermal physics of a fire.", "Occupancy sensors show 0, meaning no one was there to report a smell or see flames, increasing reliance on automated sensors which are conflicting."]}], "most_discriminative_evidence": ["The instantaneous nature of the temperature spike (2526 -> 3237 -> 2518 within 4 seconds) is physically impossible for real-world heating and strongly points to sensor failure or data packet corruption.", "The temporal proximity of the temperature anomaly (12:20:00) and the SmokeState trigger (12:30:00) suggests a causal link in the system's alerting logic, even if the physical cause was a sensor fault.", "Complete lack of corroborating data from neighboring rooms (stable temps, zero occupancy) rules out a widespread environmental event like a gas leak or major fire."], "missing_information": ["Raw firmware logs or debug traces of the kitchen_temp_sensor to determine if the 3200+ values were valid measurements or internal error codes.", "Specific logic thresholds used by the system to correlate TemperatureMeasurement spikes with SmokeState triggers.", "Visual inspection results from the kitchen (smell of burning, visible damage, or soot) to confirm or deny the presence of actual combustion.", "Network traffic logs to check for DDoS or injection attempts that might have corrupted the sensor data stream."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C01\", \"C11\", \"C14\"],\n  \"missing_checks\": [\n    \"Verify SmokeState logs specifically for the 12:30:00 timestamp to confirm if it was a distinct event or a derived flag from temperature.\",\n    \"Check network traffic logs (if available in other chunks) for packet anomalies around 12:20:00.\",\n    \"Cross-reference with 'master_bedroom' and 'living_room' sensor data chunks to definitively rule out localized fire spreading undetected by the kitchen sensor.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis is currently on-topic but relies heavily on the assumption that the system logic directly correlates temperature spikes to smoke alarms without explicit evidence of that threshold mapping.\",\n    \"The Investigator correctly identified the physical impossibility of the temperature spike (instant jump/drop), pointing strongly to hardware failure or data corruption. However, they have not yet ruled out a very small, contained fire source that might explain the smoke trigger while leaving room temps unchanged, or vice versa.\",\n    \"Missing chunks C01, C11, and C14 are likely required to retrieve the specific 'SmokeState' raw log entries, adjacent room sensor readings (to confirm no spread), and potentially firmware/version info relevant to the sensor's error handling logic.\",\n    \"The conclusion should be tentative until these corroborating data points are reviewed, as the current evidence leaves open the possibility of a real but extremely localized combustion event vs. pure sensor malfunction.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C01", "C11", "C14"], "missing_checks": ["Verify SmokeState logs specifically for the 12:30:00 timestamp to confirm if it was a distinct event or a derived flag from temperature.", "Check network traffic logs (if available in other chunks) for packet anomalies around 12:20:00.", "Cross-reference with 'master_bedroom' and 'living_room' sensor data chunks to definitively rule out localized fire spreading undetected by the kitchen sensor."], "supervisor_notes": ["The analysis is currently on-topic but relies heavily on the assumption that the system logic directly correlates temperature spikes to smoke alarms without explicit evidence of that threshold mapping.", "The Investigator correctly identified the physical impossibility of the temperature spike (instant jump/drop), pointing strongly to hardware failure or data corruption. However, they have not yet ruled out a very small, contained fire source that might explain the smoke trigger while leaving room temps unchanged, or vice versa.", "Missing chunks C01, C11, and C14 are likely required to retrieve the specific 'SmokeState' raw log entries, adjacent room sensor readings (to confirm no spread), and potentially firmware/version info relevant to the sensor's error handling logic.", "The conclusion should be tentative until these corroborating data points are reviewed, as the current evidence leaves open the possibility of a real but extremely localized combustion event vs. pure sensor malfunction."]}, "preview_triage_prompt": "## Query\n系统安全监测模块发出了警告信号。请根据以下设备日志分析可能存在的安全问题，判断威胁类型和严重程度，并制定应急响应方案。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 336,\n    \"master_bedroom\": 336,\n    \"second_bedroom\": 336,\n    \"kitchen\": 291,\n    \"bathroom\": 48,\n    \"entrance\": 48\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1154,\n    \"Occupancy\": 240,\n    \"SmokeState\": 1\n  },\n  \"lock_state_flips\": 0,\n  \"occupancy_events\": 240,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-13T00:00:00\",\n    \"end_ts\": \"2026-06-13T01:20:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 20,\n      \"master_bedroom\": 19,\n      \"second_bedroom\": 19,\n      \"kitchen\": 16,\n      \"bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"master_bedroom_occupancy\"\n    ],\n    \"alarmish_count\": 15,\n    \"preview_lines\": [\n      \"[2026-06-13T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2273\",\n      \"[2026-06-13T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2261\",\n      \"[2026-06-13T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2280\",\n      \"[2026-06-13T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2271\",\n      \"[2026-06-13T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-13T00:00:00] master_bedroom_occupancy | O", "preview_verifier_prompt": "## Query\n系统安全监测模块发出了警告信号。请根据以下设备日志分析可能存在的安全问题，判断威胁类型和严重程度，并制定应急响应方案。\n\n## Triage\n{\n  \"latent_task_profile\": \"single-event-safety\",\n  \"focus_rooms\": [\"kitchen\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C09\"],\n  \"suspected_patterns\": [\n    \"Temperature spike anomaly in kitchen sensor (jump from ~2500 to 3237 and 3200)\",\n    \"Potential sensor malfunction or calibration drift causing false high-temperature reading\",\n    \"No correlated occupancy events during the spike, suggesting no active cooking source\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunk C09 contains the only data points with MeasuredValue exceeding 3000 (3237, 3200), which is physically unrealistic for a standard indoor environment compared to surrounding chunks where values are around 2500.\",\n    \"This outlier indicates a potential device failure or a specific localized event requiring immediate inspection to rule out fire hazards or hardware malfunction.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Transient sensor glitch or data corruption in the kitchen_temp_sensor device.\",\n      \"evidence\": [\"MeasuredValue spiked to 3237 and 3200 immediately after a normal reading of 2526 at 12:20:00.\", \"The value returned to normal baseline (~2500) within 2 minutes by 12:45:00.\", \"No corresponding rise in other room temperatures or smoke detection initially.\"],\n      \"weaknesses\": [\"Fails to explain why the SmokeState triggered '1' exactly at 12:30:00, shortly after the spike.\", \"Does not account for the high 'attribute_frequency' of MeasuredValue (1154) which suggests potential re-sampling or error correction attempts.\"]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"System calibration drift causing false positive readings.\",\n      \"evidence\": [\"All temperature sensors show values in the 2480-2520 range, consistent with each other but slightly elevated compared to standard indoor norms (likely Kelvin scale given magnitude).\", \"The anomaly is isolated to a single timestamp pair without sustained thermal accumulation.\"],\n      \"weaknesses\": [\"Calibration drift rarely causes instantaneous jumps followed by immediate recovery unless reset.\", \"Cannot explain the specific correlation between the temperature spike and the subsequent smoke alarm activation.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Hardware failure of kitchen_temp_sensor triggering false smoke alarm due to overflow or logic err"}}
{"episode_id": "SQ5_FP_B_1142", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq5\\SQ5_FP_B_1142.json", "metadata": {"sq_type": "SQ5", "sq_name": "应急响应规划", "variant": "FP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "family_with_children", "base_date": "2026-06-28T00:00:00", "seed": 20261771, "scenario_id": "FG-02", "total_events": 1396, "anomaly_events_count": 4}, "ground_truth": {"scenario_id": "FG-02-FP", "scenario_name": "FG-02-FP: 电暖器/取暖器正常使用", "category": "fire_gas", "is_anomaly": false, "threat_type": "none", "key_difference": "有人在房间且温度上升后趋于稳定（不是持续飙升），无烟雾报警触发", "difficulty_score": 10, "difficulty_level": 2, "difficulty_label": "L2_reasoning_detection", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 2, "D4_temporal_span": 2, "D5_fp_similarity": 2}, "target_room": "second_bedroom", "injection_time": "2026-06-28T19:30:00", "variant": "FP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"fire_risk\",\n  \"threat_description\": \"Continuous, synchronized temperature rise across all rooms over an 8-hour period with zero occupancy and no HVAC intervention indicates a persistent unmonitored heat source or system failure.\",\n  \"reasoning\": [\n    \"The data shows a monotonic increase in temperature readings from ~22.7°C (2270) at T=00:00 to ~25.6°C (2557) by T=09:30 across all four monitored zones, representing a significant thermal load.\",\n    \"Occupancy sensors consistently report '0' throughout the entire timeline, ruling out human activity (cooking, sleeping) as the cause of the heating.\",\n    \"There are no logs indicating any HVAC state changes, window adjustments, or alarm triggers during the critical 8+ hour duration, suggesting the safety systems failed to detect or mitigate the anomaly.\"\n  ],\n  \"key_evidence\": [\n    \"Temperature values rose steadily from 2270 to 2557 across living_room, master_bedroom, second_bedroom, and kitchen between 00:00 and 09:30.\",\n    \"No 'Occupancy = 1' events were logged during the heating period, eliminating domestic heat sources.\",\n    \"Absence of any actuator flips or alarm activation logs despite sustained high temperatures.\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately dispatch emergency services or fire department to verify conditions on-site due to potential smoldering fire hazard.\",\n    \"Initiate remote lockdown protocols if available to prevent unauthorized entry until professionals arrive.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "fire_risk", "threat_description": "Continuous, synchronized temperature rise across all rooms over an 8-hour period with zero occupancy and no HVAC intervention indicates a persistent unmonitored heat source or system failure.", "reasoning": ["The data shows a monotonic increase in temperature readings from ~22.7°C (2270) at T=00:00 to ~25.6°C (2557) by T=09:30 across all four monitored zones, representing a significant thermal load.", "Occupancy sensors consistently report '0' throughout the entire timeline, ruling out human activity (cooking, sleeping) as the cause of the heating.", "There are no logs indicating any HVAC state changes, window adjustments, or alarm triggers during the critical 8+ hour duration, suggesting the safety systems failed to detect or mitigate the anomaly."], "key_evidence": ["Temperature values rose steadily from 2270 to 2557 across living_room, master_bedroom, second_bedroom, and kitchen between 00:00 and 09:30.", "No 'Occupancy = 1' events were logged during the heating period, eliminating domestic heat sources.", "Absence of any actuator flips or alarm activation logs despite sustained high temperatures."], "recommended_actions": ["Immediately dispatch emergency services or fire department to verify conditions on-site due to potential smoldering fire hazard.", "Initiate remote lockdown protocols if available to prevent unauthorized entry until professionals arrive."]}, "scores": {"parse_success": true, "detection_correct": false, "detection_label": "FALSE_ALARM", "is_miss": false, "is_false_alarm": true, "threat_type_correct": null, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 67.73600244522095, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1396, "chunk_count": 18, "signals": {"room_activity": {"living_room": 336, "master_bedroom": 336, "second_bedroom": 340, "kitchen": 288, "bathroom": 48, "entrance": 48}, "attribute_frequency": {"MeasuredValue": 1155, "Occupancy": 241}, "lock_state_flips": 0, "occupancy_events": 241, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\n    \"living_room\",\n    \"master_bedroom\",\n    \"second_bedroom\",\n    \"kitchen\"\n  ],\n  \"focus_devices\": [\n    \"temperature_sensor\",\n    \"occupancy_sensor\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C00\",\n    \"C01\",\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C06\",\n    \"C07\",\n    \"C08\",\n    \"C09\",\n    \"C10\",\n    \"C11\",\n    \"C12\",\n    \"C13\",\n    \"C14\",\n    \"C15\",\n    \"C16\",\n    \"C17\"\n  ],\n  \"suspected_patterns\": [\n    \"Unexplained Temperature Surge: All temperature sensors across living areas show a continuous, synchronized increase from ~22°C to over 25°C (represented as 2500+ in raw logs) between 02:40 and 08:10, despite zero occupancy events.\",\n    \"Occupancy-Environment Mismatch: High room activity counts (e.g., 336 in living_room/master_bedroom at start) contrast with persistent 'Occupancy = 0' signals in preview lines, suggesting potential sensor calibration drift or a false positive presence detection that correlates with the temperature spike.\",\n    \"Lack of Active Intervention: No HVAC (air_conditioner) state flips or window_covering adjustments are logged during the critical heating period, indicating a system failure to respond to the thermal anomaly.\"\n  ],\n  \"why_these_chunks\": [\n    \"The entire dataset is required because the anomaly is a slow-burn environmental event rather than a single instantaneous incident. The temperature rise is gradual and consistent across all relevant chunks (C00-C17), making it impossible to diagnose without analyzing the full time-series progression of the temperature values against the static occupancy data.\",\n    \"Specific attention to C00-C03 is needed to establish the baseline deviation where temperatures begin climbing significantly above normal thresholds (22xx -> 23xx) while occupancy remains null.\",\n    \"Chunks C04-C07 represent the peak of the anomaly (25xx range) where the safety risk (potential fire hazard due to unmonitored heat or HVAC failure) is highest.\",\n    \"Later chunks (C08-C17) are necessary to verify if the system eventually triggered an alarm, if the temperature stabilized, or if the anomaly was transient, which determines the final severity of the safety response.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["living_room", "master_bedroom", "second_bedroom", "kitchen"], "focus_devices": ["temperature_sensor", "occupancy_sensor"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04", "C05", "C06", "C07", "C08", "C09", "C10", "C11", "C12", "C13", "C14", "C15", "C16", "C17"], "suspected_patterns": ["Unexplained Temperature Surge: All temperature sensors across living areas show a continuous, synchronized increase from ~22°C to over 25°C (represented as 2500+ in raw logs) between 02:40 and 08:10, despite zero occupancy events.", "Occupancy-Environment Mismatch: High room activity counts (e.g., 336 in living_room/master_bedroom at start) contrast with persistent 'Occupancy = 0' signals in preview lines, suggesting potential sensor calibration drift or a false positive presence detection that correlates with the temperature spike.", "Lack of Active Intervention: No HVAC (air_conditioner) state flips or window_covering adjustments are logged during the critical heating period, indicating a system failure to respond to the thermal anomaly."], "why_these_chunks": ["The entire dataset is required because the anomaly is a slow-burn environmental event rather than a single instantaneous incident. The temperature rise is gradual and consistent across all relevant chunks (C00-C17), making it impossible to diagnose without analyzing the full time-series progression of the temperature values against the static occupancy data.", "Specific attention to C00-C03 is needed to establish the baseline deviation where temperatures begin climbing significantly above normal thresholds (22xx -> 23xx) while occupancy remains null.", "Chunks C04-C07 represent the peak of the anomaly (25xx range) where the safety risk (potential fire hazard due to unmonitored heat or HVAC failure) is highest.", "Later chunks (C08-C17) are necessary to verify if the system eventually triggered an alarm, if the temperature stabilized, or if the anomaly was transient, which determines the final severity of the safety response."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Systematic Sensor Calibration Drift: All temperature sensors are experiencing a synchronized, gradual hardware failure or calibration error, causing raw values to incrementally increase over time without reflecting actual environmental changes.\",\n      \"evidence\": [\n        \"All four room sensors (living_room, master_bedroom, second_bedroom, kitchen) show nearly identical incremental increases from ~2266 to ~2503 between 00:00 and 06:50.\",\n        \"The rate of change is consistent across different rooms despite varying floor plans and insulation properties, which is physically improbable for natural heat accumulation.\",\n        \"Occupancy sensors consistently report 0 throughout the entire period, suggesting no human activity (e.g., cooking, sleeping) could be driving the temperature rise.\"\n      ],\n      \"weaknesses\": [\n        \"While possible, a perfect synchronization of drift across multiple independent devices with different IDs and physical locations is statistically unlikely compared to an environmental cause.\",\n        \"Does not fully explain the magnitude of the rise (+2.4°C in 7 hours) unless the drift factor is extremely high and specific to this firmware version.\"\n      ]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"External Ambient Temperature Spike: The entire house is exposed to extreme external heat (e.g., unseasonably hot weather or direct sunlight on all windows), warming the structure uniformly.\",\n      \"evidence\": [\n        \"Temperature rises in all living spaces simultaneously.\",\n        \"No occupancy events suggest the heating is passive and not driven by internal loads like people or appliances being used actively.\"\n      ],\n      \"weaknesses\": [\n        \"A 2.5°C rise in 7 hours during what appears to be early morning/nighttime hours (based on typical circadian rhythms implied by '00:00' start) is rapid for passive solar gain alone without active HVAC contribution.\",\n        \"The data lacks any window opening/closing logs that might correlate with the start of the event at exactly 00:00.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Undetected Heat Source Ignition (Fire Hazard): A slow-burning electrical fire or overheating appliance has ignited within the home, generating sustained heat that is raising ambient temperatures while occupants remain unaware.\",\n      \"threat_type\": \"Life Safety / Fire\",\n      \"evidence\": [\n        \"Continuous, monotonic temperature rise across all zones indicates a persistent energy source rather than transient fluctuation.\",\n        \"Peak temperatures reach ~2503-2505 (raw), representing a significant thermal load if these values correspond to real degrees Celsius (approx 22°C base -> 22.5°C final? No, assuming raw value maps to higher temps or represents cumulative risk index, the trend is critical). Even if raw, the *rate* implies active heating.\",\n        \"Complete lack of HVAC intervention (no AC state flips logged) suggests the system failed to detect the anomaly or is overwhelmed.\",\n        \"Duration spans 6.5 hours, indicating the source has been burning/stuck-on for a long duration without triggering standard smoke or heat alarms (if present).\"\n      ],\n      \"weaknesses\": [\n        \"Smoke detectors did not trigger logs in the provided dataset, though their status isn't explicitly queried in every chunk.\",\n        \"If the 'MeasuredValue' is purely a scaled integer (e.g., 22.7°C represented as 2270), the absolute rise is only ~0.5°C, which might be benign; however, the context of 'safety response' implies the trend itself is the danger.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"HVAC System Failure: The central heating system is stuck in 'ON' mode or a malfunctioning heater element is cycling continuously, causing uncontrolled warming.\",\n      \"threat_type\": \"Property Damage / Comfort Hazard\",\n      \"evidence\": [\n        \"Synchronized rise across all rooms is characteristic of forced-air or radiant heating systems distributing warmth centrally.\",\n        \"Zero lock_state_flips and zero occupancy_events rule out human interaction turning on heaters.\",\n        \"The persistence of the rise over 6+ hours suggests a mechanical failure (stuck valve, broken thermostat) rather than user error.\"\n      ],\n      \"weaknesses\": [\n        \"Typically, HVAC failures result in localized hot spots first before equalizing, whereas this shows near-uniform distribution.\",\n        \"Would expect some HVAC control logic logs (setpoint adjustments, relay clicks) even if they were erroneous.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The perfect temporal correlation of temperature spikes starting exactly at T=00:00 across geographically dispersed sensors strongly points to a centralized power source (fire or HVAC failure) rather than isolated sensor faults.\",\n    \"The absence of any 'Occupancy = 1' or appliance usage logs during a 2.4-degree equivalent rise eliminates common domestic causes (cooking, presence-based heating), leaving infrastructure failure or ignition as primary candidates.\"\n  ],\n  \"missing_information\": [\n    \"Raw temperature unit mapping: Is '2270' actually 22.7°C or a proprietary index requiring conversion? If it is 22.7°C rising to 25.0°C, it's mild; if it represents cumulative heat units, the risk is higher.\",\n    \"HVAC Control Logs: Are there hidden logs for thermostat setpoints or relay states that indicate a command was sent but never executed, or a loop detected?\",\n    \"Smoke/CO Detector Status: The logs focus on temperature and occupancy; confirmation of whether smoke detectors have tripped (or why they haven't) is critical for ruling out A1.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Systematic Sensor Calibration Drift: All temperature sensors are experiencing a synchronized, gradual hardware failure or calibration error, causing raw values to incrementally increase over time without reflecting actual environmental changes.", "evidence": ["All four room sensors (living_room, master_bedroom, second_bedroom, kitchen) show nearly identical incremental increases from ~2266 to ~2503 between 00:00 and 06:50.", "The rate of change is consistent across different rooms despite varying floor plans and insulation properties, which is physically improbable for natural heat accumulation.", "Occupancy sensors consistently report 0 throughout the entire period, suggesting no human activity (e.g., cooking, sleeping) could be driving the temperature rise."], "weaknesses": ["While possible, a perfect synchronization of drift across multiple independent devices with different IDs and physical locations is statistically unlikely compared to an environmental cause.", "Does not fully explain the magnitude of the rise (+2.4°C in 7 hours) unless the drift factor is extremely high and specific to this firmware version."]}, {"id": "N2", "description": "External Ambient Temperature Spike: The entire house is exposed to extreme external heat (e.g., unseasonably hot weather or direct sunlight on all windows), warming the structure uniformly.", "evidence": ["Temperature rises in all living spaces simultaneously.", "No occupancy events suggest the heating is passive and not driven by internal loads like people or appliances being used actively."], "weaknesses": ["A 2.5°C rise in 7 hours during what appears to be early morning/nighttime hours (based on typical circadian rhythms implied by '00:00' start) is rapid for passive solar gain alone without active HVAC contribution.", "The data lacks any window opening/closing logs that might correlate with the start of the event at exactly 00:00."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Undetected Heat Source Ignition (Fire Hazard): A slow-burning electrical fire or overheating appliance has ignited within the home, generating sustained heat that is raising ambient temperatures while occupants remain unaware.", "threat_type": "Life Safety / Fire", "evidence": ["Continuous, monotonic temperature rise across all zones indicates a persistent energy source rather than transient fluctuation.", "Peak temperatures reach ~2503-2505 (raw), representing a significant thermal load if these values correspond to real degrees Celsius (approx 22°C base -> 22.5°C final? No, assuming raw value maps to higher temps or represents cumulative risk index, the trend is critical). Even if raw, the *rate* implies active heating.", "Complete lack of HVAC intervention (no AC state flips logged) suggests the system failed to detect the anomaly or is overwhelmed.", "Duration spans 6.5 hours, indicating the source has been burning/stuck-on for a long duration without triggering standard smoke or heat alarms (if present)."], "weaknesses": ["Smoke detectors did not trigger logs in the provided dataset, though their status isn't explicitly queried in every chunk.", "If the 'MeasuredValue' is purely a scaled integer (e.g., 22.7°C represented as 2270), the absolute rise is only ~0.5°C, which might be benign; however, the context of 'safety response' implies the trend itself is the danger."]}, {"id": "A2", "description": "HVAC System Failure: The central heating system is stuck in 'ON' mode or a malfunctioning heater element is cycling continuously, causing uncontrolled warming.", "threat_type": "Property Damage / Comfort Hazard", "evidence": ["Synchronized rise across all rooms is characteristic of forced-air or radiant heating systems distributing warmth centrally.", "Zero lock_state_flips and zero occupancy_events rule out human interaction turning on heaters.", "The persistence of the rise over 6+ hours suggests a mechanical failure (stuck valve, broken thermostat) rather than user error."], "weaknesses": ["Typically, HVAC failures result in localized hot spots first before equalizing, whereas this shows near-uniform distribution.", "Would expect some HVAC control logic logs (setpoint adjustments, relay clicks) even if they were erroneous."]}], "most_discriminative_evidence": ["The perfect temporal correlation of temperature spikes starting exactly at T=00:00 across geographically dispersed sensors strongly points to a centralized power source (fire or HVAC failure) rather than isolated sensor faults.", "The absence of any 'Occupancy = 1' or appliance usage logs during a 2.4-degree equivalent rise eliminates common domestic causes (cooking, presence-based heating), leaving infrastructure failure or ignition as primary candidates."], "missing_information": ["Raw temperature unit mapping: Is '2270' actually 22.7°C or a proprietary index requiring conversion? If it is 22.7°C rising to 25.0°C, it's mild; if it represents cumulative heat units, the risk is higher.", "HVAC Control Logs: Are there hidden logs for thermostat setpoints or relay states that indicate a command was sent but never executed, or a loop detected?", "Smoke/CO Detector Status: The logs focus on temperature and occupancy; confirmation of whether smoke detectors have tripped (or why they haven't) is critical for ruling out A1."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C08\", \"C09\", \"C10\", \"C11\", \"C12\", \"C13\", \"C14\", \"C15\", \"C16\", \"C17\"],\n  \"missing_checks\": [\n    \"Verify if the temperature trend stabilizes or continues to rise in later chunks to determine if the anomaly is transient or ongoing.\",\n    \"Confirm the absence of HVAC state flips or alarm triggers specifically in the post-peak period (chunks C08-C17).\",\n    \"Check for any late-stage smoke detector status updates or fire alarm activations.\"\n  ],\n  \"supervisor_notes\": [\n    \"The analysis correctly identifies a critical thermal anomaly but relies heavily on early-to-mid dataset chunks (C00-C07) which cover the onset and peak of the event.\",\n    \"To fully evaluate the 'safety response' requirement, it is insufficient to only know that the heating occurred; we must verify if the system self-corrected, failed completely, or triggered an alarm later in the timeline.\",\n    \"Chunks C08 through C17 are missing from the specific investigation plan despite being explicitly requested in the Triage Output rationale as necessary to determine 'final severity'. Without these, we cannot confirm if the threat has been mitigated or is escalating.\",\n    \"The current evidence allows us to hypothesize a hazard exists, but not whether it has resulted in a confirmed safety incident requiring immediate human intervention vs. automated recovery.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C08", "C09", "C10", "C11", "C12", "C13", "C14", "C15", "C16", "C17"], "missing_checks": ["Verify if the temperature trend stabilizes or continues to rise in later chunks to determine if the anomaly is transient or ongoing.", "Confirm the absence of HVAC state flips or alarm triggers specifically in the post-peak period (chunks C08-C17).", "Check for any late-stage smoke detector status updates or fire alarm activations."], "supervisor_notes": ["The analysis correctly identifies a critical thermal anomaly but relies heavily on early-to-mid dataset chunks (C00-C07) which cover the onset and peak of the event.", "To fully evaluate the 'safety response' requirement, it is insufficient to only know that the heating occurred; we must verify if the system self-corrected, failed completely, or triggered an alarm later in the timeline.", "Chunks C08 through C17 are missing from the specific investigation plan despite being explicitly requested in the Triage Output rationale as necessary to determine 'final severity'. Without these, we cannot confirm if the threat has been mitigated or is escalating.", "The current evidence allows us to hypothesize a hazard exists, but not whether it has resulted in a confirmed safety incident requiring immediate human intervention vs. automated recovery."]}, "preview_triage_prompt": "## Query\n请根据以下设备日志，评估家庭当前是否需要采取任何安全响应措施。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 336,\n    \"master_bedroom\": 336,\n    \"second_bedroom\": 340,\n    \"kitchen\": 288,\n    \"bathroom\": 48,\n    \"entrance\": 48\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1155,\n    \"Occupancy\": 241\n  },\n  \"lock_state_flips\": 0,\n  \"occupancy_events\": 241,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-28T00:00:00\",\n    \"end_ts\": \"2026-06-28T01:20:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 20,\n      \"master_bedroom\": 19,\n      \"second_bedroom\": 19,\n      \"kitchen\": 16,\n      \"bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"master_bedroom_occupancy\"\n    ],\n    \"alarmish_count\": 15,\n    \"preview_lines\": [\n      \"[2026-06-28T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2270\",\n      \"[2026-06-28T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2266\",\n      \"[2026-06-28T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2267\",\n      \"[2026-06-28T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2266\",\n      \"[2026-06-28T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-28T00:00:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-2", "preview_verifier_prompt": "## Query\n请根据以下设备日志，评估家庭当前是否需要采取任何安全响应措施。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\n    \"living_room\",\n    \"master_bedroom\",\n    \"second_bedroom\",\n    \"kitchen\"\n  ],\n  \"focus_devices\": [\n    \"temperature_sensor\",\n    \"occupancy_sensor\"\n  ],\n  \"focus_chunk_ids\": [\n    \"C00\",\n    \"C01\",\n    \"C02\",\n    \"C03\",\n    \"C04\",\n    \"C05\",\n    \"C06\",\n    \"C07\",\n    \"C08\",\n    \"C09\",\n    \"C10\",\n    \"C11\",\n    \"C12\",\n    \"C13\",\n    \"C14\",\n    \"C15\",\n    \"C16\",\n    \"C17\"\n  ],\n  \"suspected_patterns\": [\n    \"Unexplained Temperature Surge: All temperature sensors across living areas show a continuous, synchronized increase from ~22°C to over 25°C (represented as 2500+ in raw logs) between 02:40 and 08:10, despite zero occupancy events.\",\n    \"Occupancy-Environment Mismatch: High room activity counts (e.g., 336 in living_room/master_bedroom at start) contrast with persistent 'Occupancy = 0' signals in preview lines, suggesting potential sensor calibration drift or a false positive presence detection that correlates with the temperature spike.\",\n    \"Lack of Active Intervention: No HVAC (air_conditioner) state flips or window_covering adjustments are logged during the critical heating period, indicating a system failure to respond to the thermal anomaly.\"\n  ],\n  \"why_these_chunks\": [\n    \"The entire dataset is required because the anomaly is a slow-burn environmental event rather than a single instantaneous incident. The temperature rise is gradual and consistent across all relevant chunks (C00-C17), making it impossible to diagnose without analyzing the full time-series progression of the temperature values against the static occupancy data.\",\n    \"Specific attention to C00-C03 is needed to establish the baseline deviation where temperatures begin climbing significantly above normal thresholds (22xx -> 23xx) while occupancy remains null.\",\n    \"Chunks C04-C07 represent the peak of the anomaly (25xx range) where the safety risk (potential fire hazard due to unmonitored heat or HVAC failure) is highest.\",\n    \"Later chunks (C08-C17) are necessary to verify if the system eventually triggered an alarm, if the temperature stabilized, or if the anomaly was transient, which determines the final severity of the safety response.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Systematic Sensor Calibration Drift: All temperature sensors are experiencing a synchronized, gradual hardware failure or calibr"}}
{"episode_id": "SQ5_TP_B_1054", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq5\\SQ5_TP_B_1054.json", "metadata": {"sq_type": "SQ5", "sq_name": "应急响应规划", "variant": "TP", "layout_id": "B", "layout_name": "两室一厅 (2BR)", "profile_id": "young_professional", "base_date": "2026-06-24T00:00:00", "seed": 20261683, "scenario_id": "INS-04", "total_events": 1664, "anomaly_events_count": 6}, "ground_truth": {"scenario_id": "INS-04", "scenario_name": "白天撬窗入室", "category": "intrusion", "is_anomaly": true, "threat_type": "intrusion", "key_evidence": ["住户外出期间（门锁显示已锁+无人在家）窗户被打开", "随后出现多房间运动信号", "入侵者未使用门锁（无 LockOperation 事件）"], "expected_response": "触发入侵警报，通知住户，建议报警", "difficulty_score": 11, "difficulty_level": 3, "difficulty_label": "L3_composite_reasoning", "difficulty_dimensions": {"D1_evidence_count": 2, "D2_signal_directness": 2, "D3_cross_device": 3, "D4_temporal_span": 2, "D5_fp_similarity": 2}, "target_room": "master_bedroom", "injection_time": "2026-06-24T14:32:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"fire_risk\",\n  \"threat_description\": \"Simultaneous sensor saturation across all zones with a distinct peak in the kitchen indicates a severe environmental hazard, likely an uncontrolled fire or extreme heat event causing ADC overflow.\",\n  \"reasoning\": [\n    \"All temperature sensors simultaneously reported impossible values (>2000) starting at 00:00 and rising linearly, which rules out natural weather changes or localized cooling system failures.\",\n    \"The kitchen sensor consistently recorded the highest relative values (peaking at 2712), strongly correlating the anomaly source to the kitchen area where cooking equipment is located.\",\n    \"Occupancy logs show human presence and emergency behaviors (lights on, cook surface activation, door lock cycles) occurring during the high-temperature period, confirming residents responded to a perceived danger rather than casual activity.\",\n    \"The linear rise in raw numerical values across multiple sensor types suggests the Analog-to-Digital Converter (ADC) saturated due to extreme ambient heat or smoke interference, masking the actual temperature but indicating a critical safety breach.\"\n  ],\n  \"key_evidence\": [\n    \"Simultaneous spike in all room temperatures from ~2263 to >2500 starting at midnight with no preceding firmware updates.\",\n    \"Kitchen temperature readings were significantly higher than other rooms throughout the incident duration (e.g., 2712 vs ~2400).\",\n    \"Log entries show bathroom occupancy, light activation, and manual front door locking/unlocking coinciding with the temperature peaks.\",\n    \"Kitchen cook_surface was activated while temperature readings were already in the 'thousands', suggesting the device was running under hazardous conditions before the sensors fully saturated.\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately dispatch emergency services (Fire Department) to the residence location due to high probability of active fire.\",\n    \"Evacuate the premises if occupants are still inside; do not re-enter until declared safe by authorities.\",\n    \"Check physical status of the IoT gateway power supply for signs of surge damage caused by the event.\",\n    \"Retrieve video footage from kitchen cameras (if available and functional) to verify the nature of the hazard and guide fire suppression efforts.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "fire_risk", "threat_description": "Simultaneous sensor saturation across all zones with a distinct peak in the kitchen indicates a severe environmental hazard, likely an uncontrolled fire or extreme heat event causing ADC overflow.", "reasoning": ["All temperature sensors simultaneously reported impossible values (>2000) starting at 00:00 and rising linearly, which rules out natural weather changes or localized cooling system failures.", "The kitchen sensor consistently recorded the highest relative values (peaking at 2712), strongly correlating the anomaly source to the kitchen area where cooking equipment is located.", "Occupancy logs show human presence and emergency behaviors (lights on, cook surface activation, door lock cycles) occurring during the high-temperature period, confirming residents responded to a perceived danger rather than casual activity.", "The linear rise in raw numerical values across multiple sensor types suggests the Analog-to-Digital Converter (ADC) saturated due to extreme ambient heat or smoke interference, masking the actual temperature but indicating a critical safety breach."], "key_evidence": ["Simultaneous spike in all room temperatures from ~2263 to >2500 starting at midnight with no preceding firmware updates.", "Kitchen temperature readings were significantly higher than other rooms throughout the incident duration (e.g., 2712 vs ~2400).", "Log entries show bathroom occupancy, light activation, and manual front door locking/unlocking coinciding with the temperature peaks.", "Kitchen cook_surface was activated while temperature readings were already in the 'thousands', suggesting the device was running under hazardous conditions before the sensors fully saturated."], "recommended_actions": ["Immediately dispatch emergency services (Fire Department) to the residence location due to high probability of active fire.", "Evacuate the premises if occupants are still inside; do not re-enter until declared safe by authorities.", "Check physical status of the IoT gateway power supply for signs of surge damage caused by the event.", "Retrieve video footage from kitchen cameras (if available and functional) to verify the nature of the hazard and guide fire suppression efforts."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 4, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 54.76158428192139, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1664, "chunk_count": 21, "signals": {"room_activity": {"living_room": 402, "master_bedroom": 341, "second_bedroom": 336, "kitchen": 298, "bathroom": 56, "entrance": 231}, "attribute_frequency": {"MeasuredValue": 1154, "Occupancy": 479, "OnOff": 14, "StateValue": 7, "LockState": 4, "SystemMode": 1, "OperationalState": 1}, "lock_state_flips": 4, "occupancy_events": 479, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\", \"entrance\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"living_room_temp_sensor\", \"entrance_occupancy\", \"master_bedroom_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C02\", \"C03\", \"C04\", \"C05\", \"C15\", \"C16\", \"C17\", \"C18\", \"C19\", \"C20\"],\n  \"suspected_patterns\": [\n    \"Critical Temperature Anomaly: Sensor readings start in the thousands (e.g., 2263) and rise continuously to over 2500, indicating a sensor calibration failure, data overflow, or a severe undetected fire/smoke event causing extreme heat.\",\n    \"Unusual Occupancy Spikes: Entrance occupancy shows frequent short-duration presence events (flipping between 0 and 1) late at night/early morning (chunks C06-C20), suggesting potential unauthorized entry attempts or a person moving through the house while asleep.\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunks C02-C05 show the initial onset and rapid escalation of the temperature reading anomaly, which is the most critical safety signal.\",\n    \"Chunks C15-C20 contain the highest density of 'alarmish' counts and display the peak of the temperature spike alongside irregular entrance occupancy patterns, requiring immediate investigation for both environmental hazards and intrusion.\",\n    \"These chunks cover the transition from normal operating hours to overnight periods where the severity of both the temperature drift and potential intrusions would be most dangerous.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "living_room", "entrance"], "focus_devices": ["kitchen_temp_sensor", "living_room_temp_sensor", "entrance_occupancy", "master_bedroom_temp_sensor"], "focus_chunk_ids": ["C02", "C03", "C04", "C05", "C15", "C16", "C17", "C18", "C19", "C20"], "suspected_patterns": ["Critical Temperature Anomaly: Sensor readings start in the thousands (e.g., 2263) and rise continuously to over 2500, indicating a sensor calibration failure, data overflow, or a severe undetected fire/smoke event causing extreme heat.", "Unusual Occupancy Spikes: Entrance occupancy shows frequent short-duration presence events (flipping between 0 and 1) late at night/early morning (chunks C06-C20), suggesting potential unauthorized entry attempts or a person moving through the house while asleep."], "why_these_chunks": ["Chunks C02-C05 show the initial onset and rapid escalation of the temperature reading anomaly, which is the most critical safety signal.", "Chunks C15-C20 contain the highest density of 'alarmish' counts and display the peak of the temperature spike alongside irregular entrance occupancy patterns, requiring immediate investigation for both environmental hazards and intrusion.", "These chunks cover the transition from normal operating hours to overnight periods where the severity of both the temperature drift and potential intrusions would be most dangerous."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Sensor Calibration Drift or Offset Error\",\n      \"evidence\": [\n        \"All room temperature sensors simultaneously report values in the thousands (2300-2500+), which is physically impossible for ambient air.\",\n        \"The anomaly began at a specific timestamp (02:40) and escalated linearly across all devices.\"\n      ],\n      \"weaknesses\": [\n        \"A global calibration failure affecting every sensor type (bedroom, kitchen, living room) with identical initial offset is statistically improbable without a central firmware update event not recorded in logs.\",\n        \"Does not explain the subsequent occupancy events in the bathroom and entrance after the temperature readings stabilized/fluctuated.\"\n      ]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"Data Overflow/Integer Wraparound\",\n      \"evidence\": [\n        \"Values start around 2343 and rise continuously to over 2500, suggesting an integer counter incrementing past its maximum limit before wrapping.\",\n        \"Uniformity across all sensors suggests a shared data parsing error in the monitoring module.\"\n      ],\n      \"weaknesses\": [\n        \"If it were a pure software overflow, readings would likely jump abruptly or reset to zero/negative rather than climb steadily while other metrics (occupancy) function normally.\",\n        \"Fails to account for the specific pattern of human activity (lights on/off, door locks) occurring later in the log during the 'high' temperature period.\"\n      ]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Simultaneous Sensor Malfunction due to Environmental Hazard (Fire/Smoke)\",\n      \"threat_type\": \"Environmental Safety / Fire Hazard\",\n      \"evidence\": [\n        \"Rapid escalation of temperature readings from ~2343 to >2500 across ALL zones within 2 hours (02:40 - 04:40). While the absolute numbers are suspect due to potential overflow, the relative increase indicates extreme heat exposure.\",\n        \"Correlation between high temperature reports and human presence: Occupancy spikes occur in the bathroom (06:26, 06:31, 06:41, 06:51) and entrance (multiple times from 07:19 onwards).\",\n        \"Emergency behaviors observed: Kitchen light turned ON at 18:48 followed immediately by cook_surface activation; Front door unlocked manually then relocked automatically shortly after entry detection.\",\n        \"Kitchen sensor behavior: Values spike highest in the kitchen area (reaching 2712), consistent with a fire source originating there.\"\n      ],\n      \"weaknesses\": [\n        \"The absolute temperature values (>2000 degrees) are so high they suggest the sensor might be reporting raw voltage counts or has completely failed/calibrated incorrectly, making it difficult to distinguish between 'extreme fire heat' and 'sensor total failure'.\",\n        \"No direct smoke detection alerts or flame sensor triggers are explicitly logged in the provided chunks.\"\n      ]\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Cybersecurity Intrusion & Sensor Spoofing\",\n      \"threat_type\": \"Cyber Security / Unauthorized Access\",\n      \"evidence\": [\n        \"Coordinated anomaly: All sensors jumped to 'thousands' simultaneously, suspicious of a remote command injection altering sensor baselines.\",\n        \"Intrusion patterns: Frequent short-duration occupancy events at the entrance starting 07:19, culminating in manual lock/unlock cycles.\",\n        \"Suspicious timing: Activity occurs during low-light hours (early morning/morning transition) when residents are typically asleep or away.\"\n      ],\n      \"weaknesses\": [\n        \"It is highly unlikely an attacker could spoof *every* physical sensor in the house simultaneously without physical access to the gateway or network intrusion that would likely trigger other alarms.\",\n        \"The 'thousands' reading appears more like a hardware failure mode than a calculated spoofed value.\"\n      ]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"The combination of 'Kitchen' showing the highest relative temperature increase (peaking at 2712 vs ~2500 elsewhere) strongly correlates with the location of a potential fire source.\",\n    \"The sequence of events in Chunk C05: Bathroom occupancy -> Light On -> Door Lock Interaction suggests a person responding to a distress signal or investigating a hazard, rather than casual entry.\",\n    \"The linear rise in temperature values across all rooms despite no obvious external heating source implies a systemic sensor failure triggered by a physical event (heat/fire) causing the ADC (Analog-to-Digital Converter) to saturate or overflow.\"\n  ],\n  \"missing_information\": [\n    \"Status of the primary Smoke Detector and Heat Alarm units (are they triggering?).\",\n    \"Power supply status of the IoT gateway/sensors (was there a brownout or surge?).\",\n    \"Historical baseline temperature readings for this season to confirm if '2300' represents a known saturation point for these specific sensor models.\",\n    \"Video feed status or camera logs from the entrance and kitchen to visually verify the nature of the intruder or fire.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Sensor Calibration Drift or Offset Error", "evidence": ["All room temperature sensors simultaneously report values in the thousands (2300-2500+), which is physically impossible for ambient air.", "The anomaly began at a specific timestamp (02:40) and escalated linearly across all devices."], "weaknesses": ["A global calibration failure affecting every sensor type (bedroom, kitchen, living room) with identical initial offset is statistically improbable without a central firmware update event not recorded in logs.", "Does not explain the subsequent occupancy events in the bathroom and entrance after the temperature readings stabilized/fluctuated."]}, {"id": "N2", "description": "Data Overflow/Integer Wraparound", "evidence": ["Values start around 2343 and rise continuously to over 2500, suggesting an integer counter incrementing past its maximum limit before wrapping.", "Uniformity across all sensors suggests a shared data parsing error in the monitoring module."], "weaknesses": ["If it were a pure software overflow, readings would likely jump abruptly or reset to zero/negative rather than climb steadily while other metrics (occupancy) function normally.", "Fails to account for the specific pattern of human activity (lights on/off, door locks) occurring later in the log during the 'high' temperature period."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Simultaneous Sensor Malfunction due to Environmental Hazard (Fire/Smoke)", "threat_type": "Environmental Safety / Fire Hazard", "evidence": ["Rapid escalation of temperature readings from ~2343 to >2500 across ALL zones within 2 hours (02:40 - 04:40). While the absolute numbers are suspect due to potential overflow, the relative increase indicates extreme heat exposure.", "Correlation between high temperature reports and human presence: Occupancy spikes occur in the bathroom (06:26, 06:31, 06:41, 06:51) and entrance (multiple times from 07:19 onwards).", "Emergency behaviors observed: Kitchen light turned ON at 18:48 followed immediately by cook_surface activation; Front door unlocked manually then relocked automatically shortly after entry detection.", "Kitchen sensor behavior: Values spike highest in the kitchen area (reaching 2712), consistent with a fire source originating there."], "weaknesses": ["The absolute temperature values (>2000 degrees) are so high they suggest the sensor might be reporting raw voltage counts or has completely failed/calibrated incorrectly, making it difficult to distinguish between 'extreme fire heat' and 'sensor total failure'.", "No direct smoke detection alerts or flame sensor triggers are explicitly logged in the provided chunks."]}, {"id": "A2", "description": "Cybersecurity Intrusion & Sensor Spoofing", "threat_type": "Cyber Security / Unauthorized Access", "evidence": ["Coordinated anomaly: All sensors jumped to 'thousands' simultaneously, suspicious of a remote command injection altering sensor baselines.", "Intrusion patterns: Frequent short-duration occupancy events at the entrance starting 07:19, culminating in manual lock/unlock cycles.", "Suspicious timing: Activity occurs during low-light hours (early morning/morning transition) when residents are typically asleep or away."], "weaknesses": ["It is highly unlikely an attacker could spoof *every* physical sensor in the house simultaneously without physical access to the gateway or network intrusion that would likely trigger other alarms.", "The 'thousands' reading appears more like a hardware failure mode than a calculated spoofed value."]}], "most_discriminative_evidence": ["The combination of 'Kitchen' showing the highest relative temperature increase (peaking at 2712 vs ~2500 elsewhere) strongly correlates with the location of a potential fire source.", "The sequence of events in Chunk C05: Bathroom occupancy -> Light On -> Door Lock Interaction suggests a person responding to a distress signal or investigating a hazard, rather than casual entry.", "The linear rise in temperature values across all rooms despite no obvious external heating source implies a systemic sensor failure triggered by a physical event (heat/fire) causing the ADC (Analog-to-Digital Converter) to saturate or overflow."], "missing_information": ["Status of the primary Smoke Detector and Heat Alarm units (are they triggering?).", "Power supply status of the IoT gateway/sensors (was there a brownout or surge?).", "Historical baseline temperature readings for this season to confirm if '2300' represents a known saturation point for these specific sensor models.", "Video feed status or camera logs from the entrance and kitchen to visually verify the nature of the intruder or fire."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C00\", \"C01\"],\n  \"missing_checks\": [\n    \"Verify Smoke Detector and Heat Alarm status logs.\",\n    \"Check IoT Gateway power supply history for brownouts/surges.\",\n    \"Review historical baseline temperatures for specific sensor saturation points.\",\n    \"Retrieve video feed or camera logs from kitchen and entrance.\"\n  ],\n  \"supervisor_notes\": [\n    \"The investigator's analysis is on-topic and logically sound, correctly identifying the discrepancy between physically impossible temperature readings and potential fire vs. spoofing scenarios.\",\n    \"Evidence is currently insufficient because the investigation focuses heavily on Chunks C02-C20 (the anomaly period). To determine root cause, it is critical to review Chunks C00 and C01 to establish the pre-incident baseline and check for any preceding system alerts, firmware updates, or network anomalies that might explain the simultaneous sensor failure.\",\n    \"The 'most_discriminative_evidence' section mentions Chunk C05 specifically; ensuring C00 and C01 are reviewed will help confirm if the event was sudden or preceded by other indicators.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C00", "C01"], "missing_checks": ["Verify Smoke Detector and Heat Alarm status logs.", "Check IoT Gateway power supply history for brownouts/surges.", "Review historical baseline temperatures for specific sensor saturation points.", "Retrieve video feed or camera logs from kitchen and entrance."], "supervisor_notes": ["The investigator's analysis is on-topic and logically sound, correctly identifying the discrepancy between physically impossible temperature readings and potential fire vs. spoofing scenarios.", "Evidence is currently insufficient because the investigation focuses heavily on Chunks C02-C20 (the anomaly period). To determine root cause, it is critical to review Chunks C00 and C01 to establish the pre-incident baseline and check for any preceding system alerts, firmware updates, or network anomalies that might explain the simultaneous sensor failure.", "The 'most_discriminative_evidence' section mentions Chunk C05 specifically; ensuring C00 and C01 are reviewed will help confirm if the event was sudden or preceded by other indicators."]}, "preview_triage_prompt": "## Query\n系统安全监测模块发出了警告信号。请根据以下设备日志分析可能存在的安全问题，判断威胁类型和严重程度，并制定应急响应方案。\n\n## Layout\nLayout: 两室一厅 (2BR)\n- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>\n- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>\n- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>\n- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 402,\n    \"master_bedroom\": 341,\n    \"second_bedroom\": 336,\n    \"kitchen\": 298,\n    \"bathroom\": 56,\n    \"entrance\": 231\n  },\n  \"attribute_frequency\": {\n    \"MeasuredValue\": 1154,\n    \"Occupancy\": 479,\n    \"OnOff\": 14,\n    \"StateValue\": 7,\n    \"LockState\": 4,\n    \"SystemMode\": 1,\n    \"OperationalState\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 479,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-24T00:00:00\",\n    \"end_ts\": \"2026-06-24T01:20:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 20,\n      \"master_bedroom\": 19,\n      \"second_bedroom\": 19,\n      \"kitchen\": 16,\n      \"bathroom\": 3,\n      \"entrance\": 3\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"master_bedroom_temp_sensor\",\n      \"second_bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"master_bedroom_occupancy\"\n    ],\n    \"alarmish_count\": 15,\n    \"preview_lines\": [\n      \"[2026-06-24T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2263\",\n      \"[2026-06-24T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2266\",\n      \"[2026-06-24T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2266\",\n      \"[2026-06-24T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2263\",\n      \"[2026-06-24T00:00:00] living_room_occupancy | Occu", "preview_verifier_prompt": "## Query\n系统安全监测模块发出了警告信号。请根据以下设备日志分析可能存在的安全问题，判断威胁类型和严重程度，并制定应急响应方案。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\", \"entrance\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"living_room_temp_sensor\", \"entrance_occupancy\", \"master_bedroom_temp_sensor\"],\n  \"focus_chunk_ids\": [\"C02\", \"C03\", \"C04\", \"C05\", \"C15\", \"C16\", \"C17\", \"C18\", \"C19\", \"C20\"],\n  \"suspected_patterns\": [\n    \"Critical Temperature Anomaly: Sensor readings start in the thousands (e.g., 2263) and rise continuously to over 2500, indicating a sensor calibration failure, data overflow, or a severe undetected fire/smoke event causing extreme heat.\",\n    \"Unusual Occupancy Spikes: Entrance occupancy shows frequent short-duration presence events (flipping between 0 and 1) late at night/early morning (chunks C06-C20), suggesting potential unauthorized entry attempts or a person moving through the house while asleep.\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunks C02-C05 show the initial onset and rapid escalation of the temperature reading anomaly, which is the most critical safety signal.\",\n    \"Chunks C15-C20 contain the highest density of 'alarmish' counts and display the peak of the temperature spike alongside irregular entrance occupancy patterns, requiring immediate investigation for both environmental hazards and intrusion.\",\n    \"These chunks cover the transition from normal operating hours to overnight periods where the severity of both the temperature drift and potential intrusions would be most dangerous.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Sensor Calibration Drift or Offset Error\",\n      \"evidence\": [\n        \"All room temperature sensors simultaneously report values in the thousands (2300-2500+), which is physically impossible for ambient air.\",\n        \"The anomaly began at a specific timestamp (02:40) and escalated linearly across all devices.\"\n      ],\n      \"weaknesses\": [\n        \"A global calibration failure affecting every sensor type (bedroom, kitchen, living room) with identical initial offset is statistically improbable without a central firmware update event not recorded in logs.\",\n        \"Does not explain the subsequent occupancy events in the bathroom and entrance after the temperature readings stabilized/fluctuated.\"\n      ]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"Data Overflow/Integer Wraparound\",\n      \"evidence\": [\n        \"Values start around 2343 a"}}
{"episode_id": "SQ5_TP_D_1012", "episode_path": "C:\\Users\\Wal1et\\Downloads\\llmiotsafe\\data\\benchmark\\sq5\\SQ5_TP_D_1012.json", "metadata": {"sq_type": "SQ5", "sq_name": "应急响应规划", "variant": "TP", "layout_id": "D", "layout_name": "独居老人 (Elderly Living Alone)", "profile_id": "elderly_living_alone", "base_date": "2026-06-26T00:00:00", "seed": 20261641, "scenario_id": "WD-01", "total_events": 1848, "anomaly_events_count": 2}, "ground_truth": {"scenario_id": "WD-01", "scenario_name": "卫生间水管漏水", "category": "water_damage", "is_anomaly": true, "threat_type": "water_leak", "key_evidence": ["漏水传感器直接触发"], "expected_response": "通知住户，如果有智能水阀则关闭总水阀", "difficulty_score": 6, "difficulty_level": 1, "difficulty_label": "L1_basic_detection", "difficulty_dimensions": {"D1_evidence_count": 1, "D2_signal_directness": 1, "D3_cross_device": 1, "D4_temporal_span": 1, "D5_fp_similarity": 2}, "target_room": "bathroom", "injection_time": "2026-06-26T09:16:00", "variant": "TP"}, "raw_response": "{\n  \"is_anomaly\": true,\n  \"confidence\": \"high\",\n  \"threat_type\": \"sensor_malfunction\",\n  \"threat_description\": \"Temperature sensors are reporting physically impossible values (2000°C+) due to a calibration error or data corruption, while occupancy and actuator logs indicate normal resident activity, suggesting the threat is a false positive alert caused by faulty sensor data rather than an actual security breach.\",\n  \"reasoning\": [\n    \"Analysis of chunks C00-C05 reveals temperature readings consistently exceeding 2000°C (e.g., 2487, 2528), which is physically impossible for ambient room conditions, indicating a systematic sensor failure, unit conversion bug, or integer overflow.\",\n    \"In contrast to the anomalous temperature data, occupancy sensors and actuator logs show logical, sequential human behavior: residents waking up at 05:33, using the bathroom, cooking food at 06:07, and manually locking the door at 06:59, proving the physical environment and control systems are functional.\",\n    \"The intermittent appearance of 'None' in temperature readings (C03, C04) alongside valid operational events suggests the sensor hardware or transmission layer is malfunctioning or resetting intermittently, causing the safety module to trigger spurious alarms based on corrupted data.\"\n  ],\n  \"key_evidence\": [\n    \"Temperature values in range 2000-2552°C appearing across all sensors during morning hours when the home should be unoccupied or occupied normally.\",\n    \"Coexistence of impossible thermal data with realistic behavioral events such as lights turning on, cooking surfaces activating, and manual door locking operations.\",\n    \"Sudden switch to 'None' for kitchen_temp_sensor at specific timestamps (06:08, 06:41) without corresponding system-wide failure, isolating the issue to the temperature sensor subsystem.\"\n  ],\n  \"recommended_actions\": [\n    \"Immediately isolate and disable the affected temperature sensors (kitchen_temp_sensor, living_room_temp_sensor, bedroom_temp_sensor) from the safety monitoring logic to prevent further false alarms.\",\n    \"Schedule a maintenance technician to inspect the sensor hardware for physical damage, recalibrate the sensors, or replace them if the fault persists after cleaning/power cycling.\",\n    \"Review firmware versions for the temperature sensor modules and check for known bugs related to data formatting or integer handling that may have been introduced in recent updates.\"\n  ]\n}", "model_response": {"is_anomaly": true, "confidence": "high", "threat_type": "sensor_malfunction", "threat_description": "Temperature sensors are reporting physically impossible values (2000°C+) due to a calibration error or data corruption, while occupancy and actuator logs indicate normal resident activity, suggesting the threat is a false positive alert caused by faulty sensor data rather than an actual security breach.", "reasoning": ["Analysis of chunks C00-C05 reveals temperature readings consistently exceeding 2000°C (e.g., 2487, 2528), which is physically impossible for ambient room conditions, indicating a systematic sensor failure, unit conversion bug, or integer overflow.", "In contrast to the anomalous temperature data, occupancy sensors and actuator logs show logical, sequential human behavior: residents waking up at 05:33, using the bathroom, cooking food at 06:07, and manually locking the door at 06:59, proving the physical environment and control systems are functional.", "The intermittent appearance of 'None' in temperature readings (C03, C04) alongside valid operational events suggests the sensor hardware or transmission layer is malfunctioning or resetting intermittently, causing the safety module to trigger spurious alarms based on corrupted data."], "key_evidence": ["Temperature values in range 2000-2552°C appearing across all sensors during morning hours when the home should be unoccupied or occupied normally.", "Coexistence of impossible thermal data with realistic behavioral events such as lights turning on, cooking surfaces activating, and manual door locking operations.", "Sudden switch to 'None' for kitchen_temp_sensor at specific timestamps (06:08, 06:41) without corresponding system-wide failure, isolating the issue to the temperature sensor subsystem."], "recommended_actions": ["Immediately isolate and disable the affected temperature sensors (kitchen_temp_sensor, living_room_temp_sensor, bedroom_temp_sensor) from the safety monitoring logic to prevent further false alarms.", "Schedule a maintenance technician to inspect the sensor hardware for physical damage, recalibrate the sensors, or replace them if the fault persists after cleaning/power cycling.", "Review firmware versions for the temperature sensor modules and check for known bugs related to data formatting or integer handling that may have been introduced in recent updates."]}, "scores": {"parse_success": true, "detection_correct": true, "detection_label": "HIT", "is_miss": false, "is_false_alarm": false, "threat_type_correct": false, "reasoning_steps": 3, "has_evidence": true, "has_actions": true, "confidence": "high"}, "latency": 51.24861526489258, "api_error": null, "egpv2_trace": {"case_summary": {"event_count": 1848, "chunk_count": 24, "signals": {"room_activity": {"living_room": 496, "bedroom": 529, "kitchen": 532, "bathroom": 61, "entrance": 230}, "attribute_frequency": {"Occupancy": 938, "MeasuredValue": 870, "OnOff": 21, "StateValue": 5, "CurrentPositionLiftPercent100ths": 4, "LockState": 4, "CurrentLevel": 1}, "lock_state_flips": 4, "occupancy_events": 938, "temperature_patterns": []}}, "triage_raw": "{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"living_room_temp_sensor\", \"kitchen_occupancy\", \"entrance_occupancy\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\"],\n  \"suspected_patterns\": [\n    \"Anomalous temperature readings (e.g., 2281, 2528) likely indicating sensor drift or unit conversion errors rather than actual heat.\",\n    \"Prolonged high occupancy counts in Kitchen and Entrance during early morning hours (06:00-09:00) suggesting potential unauthorized entry or a caregiver presence before the resident's usual wake-up time.\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunks C00-C03 show the most critical data anomalies: extreme temperature values appearing at night/early morning when the home should be unoccupied or low-activity, triggering immediate safety alerts.\",\n    \"Chunk C04 marks the transition point where normal occupancy patterns resume (Kitchen and Bedroom active), establishing a baseline to compare against the earlier suspicious activity.\"\n  ]\n}", "triage_parsed": {"latent_task_profile": "composite-safety", "focus_rooms": ["kitchen", "living_room"], "focus_devices": ["kitchen_temp_sensor", "living_room_temp_sensor", "kitchen_occupancy", "entrance_occupancy"], "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04"], "suspected_patterns": ["Anomalous temperature readings (e.g., 2281, 2528) likely indicating sensor drift or unit conversion errors rather than actual heat.", "Prolonged high occupancy counts in Kitchen and Entrance during early morning hours (06:00-09:00) suggesting potential unauthorized entry or a caregiver presence before the resident's usual wake-up time."], "why_these_chunks": ["Chunks C00-C03 show the most critical data anomalies: extreme temperature values appearing at night/early morning when the home should be unoccupied or low-activity, triggering immediate safety alerts.", "Chunk C04 marks the transition point where normal occupancy patterns resume (Kitchen and Bedroom active), establishing a baseline to compare against the earlier suspicious activity."]}, "investigator_raw": "{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Systematic sensor calibration error or unit conversion bug affecting all temperature sensors simultaneously.\",\n      \"evidence\": [\"All rooms report values >2000°C consistently from 00:00 to 07:20, which is physically impossible for ambient room conditions.\", \"The relative difference between rooms (e.g., Kitchen ~230-250 higher than Bedroom) remains constant over time, suggesting a fixed offset or scaling factor error rather than dynamic heat sources.\"],\n      \"weaknesses\": [\"Does not explain the specific behavioral anomalies in occupancy and lock states observed later in the log.\", \"Cannot account for the sudden appearance of valid-looking low-temperature readings mixed with nulls at 06:08 and 06:41 if it were purely a software bug; hardware failure patterns usually differ.\"]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"Resident's morning routine began unusually early due to health reasons or external events.\",\n      \"evidence\": [\"Occupancy sensors show activity starting at 05:33 in the bedroom.\", \"Lights turned on in bedroom (05:33) and bathroom (05:39).\", \"Cooking surface activated at 06:07.\"],\n      \"weaknesses\": [\"Completely ignores the extreme temperature data which triggers the initial security alert.\", \"Fails to explain why an occupant would be present while temperature sensors read '2500 degrees' unless the sensor data is ignored as noise, which contradicts standard monitoring protocols.\"]\n    }\n  ],\n  \"anomaly_hypotheses\": [\n    {\n      \"id\": \"A1\",\n      \"description\": \"Sensor spoofing attack or data injection targeting environmental sensors to mask other activities or trigger false alarms, combined with legitimate resident movement.\",\n      \"threat_type\": \"Data Integrity Compromise / Sensor Spoofing\",\n      \"evidence\": [\"Temperature values are nonsensical (2000-2500 range), indicating injected data or corrupted transmission.\", \"Despite the fake heat data, real-world behaviors occur: lights turn on, doors unlock/lock manually, cooking surfaces activate, and occupants move between rooms logically.\", \"At 06:41 and 06:08, temperature readings return to 'None', suggesting the attacker stopped injecting data or the device rebooted/recovered, revealing the underlying reality.\", \"The lock state flip count (4) correlates with manual unlocking at 06:59, confirming physical interaction despite the digital chaos.\"],\n      \"weaknesses\": [\"Requires assuming simultaneous compromise of multiple independent IoT devices (temp sensors vs occupancy/lock sensors) by the same actor, though this is common in botnet attacks.\"],\n      \"weaknesses_extra\": []\n    },\n    {\n      \"id\": \"A2\",\n      \"description\": \"Hardware malfunction causing sensor drift/failure, coinciding with normal resident waking up.\",\n      \"threat_type\": \"Hardware Failure / False Positive Alert\",\n      \"evidence\": [\"Continuous rising trend in temperature values could mimic heating element failure or sensor drift.\", \"Null values appearing randomly (06:08, 06:41) suggest intermittent connection loss typical of failing hardware.\"],\n      \"weaknesses\": [\"Extreme values (>2000) are too high for simple drift; they look like integer overflow or deliberate manipulation.\", \"Normal occupant behavior (cooking, locking door) occurs seamlessly alongside the anomaly. A failing sensor wouldn't typically stop reporting entirely mid-stream without triggering a different type of error code, whereas 'None' often indicates a reset or switch to a safe state after corruption.\"]\n    }\n  ],\n  \"most_discriminative_evidence\": [\n    \"Coexistence of 'impossible' temperature readings (2000-2500+) with perfectly logical human behavior sequences (waking up -> turning on lights -> using bathroom -> cooking -> locking door).\",\n    \"Intermittent data loss ('None') at 06:08 and 06:41 immediately following periods of anomalous data, suggesting the system recovered or was reset, likely ending the spoofing session.\",\n    \"Manual lock operation event at 06:59:10 (Source=Manual) occurring while temperature sensors are still spewing garbage data, proving the physical layer is functional and independent of the compromised data stream.\"\n  ],\n  \"missing_information\": [\n    \"Device firmware version and last update history for temperature sensors.\",\n    \"Network traffic logs showing packet payloads during the 00:00-07:20 window to confirm data injection.\",\n    \"Resident's known wake-up schedule and medical history to validate the timing of the morning activities.\",\n    \"Status of the central hub/gateway to determine if the issue is localized to sensors or propagated from a controller.\"\n  ]\n}", "investigator_parsed": {"normal_hypotheses": [{"id": "N1", "description": "Systematic sensor calibration error or unit conversion bug affecting all temperature sensors simultaneously.", "evidence": ["All rooms report values >2000°C consistently from 00:00 to 07:20, which is physically impossible for ambient room conditions.", "The relative difference between rooms (e.g., Kitchen ~230-250 higher than Bedroom) remains constant over time, suggesting a fixed offset or scaling factor error rather than dynamic heat sources."], "weaknesses": ["Does not explain the specific behavioral anomalies in occupancy and lock states observed later in the log.", "Cannot account for the sudden appearance of valid-looking low-temperature readings mixed with nulls at 06:08 and 06:41 if it were purely a software bug; hardware failure patterns usually differ."]}, {"id": "N2", "description": "Resident's morning routine began unusually early due to health reasons or external events.", "evidence": ["Occupancy sensors show activity starting at 05:33 in the bedroom.", "Lights turned on in bedroom (05:33) and bathroom (05:39).", "Cooking surface activated at 06:07."], "weaknesses": ["Completely ignores the extreme temperature data which triggers the initial security alert.", "Fails to explain why an occupant would be present while temperature sensors read '2500 degrees' unless the sensor data is ignored as noise, which contradicts standard monitoring protocols."]}], "anomaly_hypotheses": [{"id": "A1", "description": "Sensor spoofing attack or data injection targeting environmental sensors to mask other activities or trigger false alarms, combined with legitimate resident movement.", "threat_type": "Data Integrity Compromise / Sensor Spoofing", "evidence": ["Temperature values are nonsensical (2000-2500 range), indicating injected data or corrupted transmission.", "Despite the fake heat data, real-world behaviors occur: lights turn on, doors unlock/lock manually, cooking surfaces activate, and occupants move between rooms logically.", "At 06:41 and 06:08, temperature readings return to 'None', suggesting the attacker stopped injecting data or the device rebooted/recovered, revealing the underlying reality.", "The lock state flip count (4) correlates with manual unlocking at 06:59, confirming physical interaction despite the digital chaos."], "weaknesses": ["Requires assuming simultaneous compromise of multiple independent IoT devices (temp sensors vs occupancy/lock sensors) by the same actor, though this is common in botnet attacks."], "weaknesses_extra": []}, {"id": "A2", "description": "Hardware malfunction causing sensor drift/failure, coinciding with normal resident waking up.", "threat_type": "Hardware Failure / False Positive Alert", "evidence": ["Continuous rising trend in temperature values could mimic heating element failure or sensor drift.", "Null values appearing randomly (06:08, 06:41) suggest intermittent connection loss typical of failing hardware."], "weaknesses": ["Extreme values (>2000) are too high for simple drift; they look like integer overflow or deliberate manipulation.", "Normal occupant behavior (cooking, locking door) occurs seamlessly alongside the anomaly. A failing sensor wouldn't typically stop reporting entirely mid-stream without triggering a different type of error code, whereas 'None' often indicates a reset or switch to a safe state after corruption."]}], "most_discriminative_evidence": ["Coexistence of 'impossible' temperature readings (2000-2500+) with perfectly logical human behavior sequences (waking up -> turning on lights -> using bathroom -> cooking -> locking door).", "Intermittent data loss ('None') at 06:08 and 06:41 immediately following periods of anomalous data, suggesting the system recovered or was reset, likely ending the spoofing session.", "Manual lock operation event at 06:59:10 (Source=Manual) occurring while temperature sensors are still spewing garbage data, proving the physical layer is functional and independent of the compromised data stream."], "missing_information": ["Device firmware version and last update history for temperature sensors.", "Network traffic logs showing packet payloads during the 00:00-07:20 window to confirm data injection.", "Resident's known wake-up schedule and medical history to validate the timing of the morning activities.", "Status of the central hub/gateway to determine if the issue is localized to sensors or propagated from a controller."]}, "supervisor_raw": "{\n  \"on_topic\": true,\n  \"evidence_sufficient\": false,\n  \"needs_more_chunks\": [\"C05\", \"C06\", \"C10\", \"C14\"],\n  \"missing_checks\": [\"Verify network traffic logs for data injection signatures\", \"Check central hub status to rule out propagation from controller\", \"Cross-reference resident medical history with activity timestamps\"],\n  \"supervisor_notes\": [\n    \"The analysis correctly identified the conflict between impossible temperature data and logical human behavior, narrowing the scope to sensor spoofing or hardware failure.\",\n    \"However, the evidence selection is incomplete. The current chunks focus heavily on the anomaly window (early morning) but lack context for the system's state immediately preceding the event (to establish a clean baseline) and subsequent recovery phases.\",\n    \"Specifically, C05 and C06 are needed to see the transition into the anomalous period more clearly, while C10 and C14 are critical to observe the post-incident state and confirm if the system returned to normal operation or if residual issues exist.\",\n    \"Additionally, the 'missing_information' section highlights a need for network logs and firmware checks which cannot be derived from device state logs alone; these external data sources must be collected to validate the 'Data Integrity Compromise' hypothesis.\"\n  ]\n}", "supervisor_parsed": {"on_topic": true, "evidence_sufficient": false, "needs_more_chunks": ["C05", "C06", "C10", "C14"], "missing_checks": ["Verify network traffic logs for data injection signatures", "Check central hub status to rule out propagation from controller", "Cross-reference resident medical history with activity timestamps"], "supervisor_notes": ["The analysis correctly identified the conflict between impossible temperature data and logical human behavior, narrowing the scope to sensor spoofing or hardware failure.", "However, the evidence selection is incomplete. The current chunks focus heavily on the anomaly window (early morning) but lack context for the system's state immediately preceding the event (to establish a clean baseline) and subsequent recovery phases.", "Specifically, C05 and C06 are needed to see the transition into the anomalous period more clearly, while C10 and C14 are critical to observe the post-incident state and confirm if the system returned to normal operation or if residual issues exist.", "Additionally, the 'missing_information' section highlights a need for network logs and firmware checks which cannot be derived from device state logs alone; these external data sources must be collected to validate the 'Data Integrity Compromise' hypothesis."]}, "preview_triage_prompt": "## Query\n系统安全监测模块发出了警告信号。请根据以下设备日志分析可能存在的安全问题，判断威胁类型和严重程度，并制定应急响应方案。\n\n## Layout\nLayout: 独居老人 (Elderly Living Alone)\n- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>\n- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>, 床头灯<onoff_light>\n- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>\n- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房运动传感器<occupancy_sensor>\n- living_room: 客厅温度传感器<temperature_sensor>, 客厅灯<dimmable_light>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>\n\n## Deterministic Signals\n{\n  \"room_activity\": {\n    \"living_room\": 496,\n    \"bedroom\": 529,\n    \"kitchen\": 532,\n    \"bathroom\": 61,\n    \"entrance\": 230\n  },\n  \"attribute_frequency\": {\n    \"Occupancy\": 938,\n    \"MeasuredValue\": 870,\n    \"OnOff\": 21,\n    \"StateValue\": 5,\n    \"CurrentPositionLiftPercent100ths\": 4,\n    \"LockState\": 4,\n    \"CurrentLevel\": 1\n  },\n  \"lock_state_flips\": 4,\n  \"occupancy_events\": 938,\n  \"temperature_patterns\": []\n}\n\n## Chunk Index\n[\n  {\n    \"chunk_id\": \"C00\",\n    \"start_ts\": \"2026-06-26T00:00:00\",\n    \"end_ts\": \"2026-06-26T01:35:00\",\n    \"event_count\": 80,\n    \"rooms\": {\n      \"living_room\": 24,\n      \"bedroom\": 24,\n      \"kitchen\": 24,\n      \"bathroom\": 4,\n      \"entrance\": 4\n    },\n    \"top_devices\": [\n      \"living_room_temp_sensor\",\n      \"bedroom_temp_sensor\",\n      \"kitchen_temp_sensor\",\n      \"living_room_occupancy\",\n      \"bedroom_occupancy\",\n      \"kitchen_occupancy\"\n    ],\n    \"alarmish_count\": 20,\n    \"preview_lines\": [\n      \"[2026-06-26T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2281\",\n      \"[2026-06-26T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2171\",\n      \"[2026-06-26T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2276\",\n      \"[2026-06-26T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-26T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-26T00:00:00] kitchen_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-26T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-26T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0\",\n      \"[2026-06-26", "preview_verifier_prompt": "## Query\n系统安全监测模块发出了警告信号。请根据以下设备日志分析可能存在的安全问题，判断威胁类型和严重程度，并制定应急响应方案。\n\n## Triage\n{\n  \"latent_task_profile\": \"composite-safety\",\n  \"focus_rooms\": [\"kitchen\", \"living_room\"],\n  \"focus_devices\": [\"kitchen_temp_sensor\", \"living_room_temp_sensor\", \"kitchen_occupancy\", \"entrance_occupancy\"],\n  \"focus_chunk_ids\": [\"C00\", \"C01\", \"C02\", \"C03\", \"C04\"],\n  \"suspected_patterns\": [\n    \"Anomalous temperature readings (e.g., 2281, 2528) likely indicating sensor drift or unit conversion errors rather than actual heat.\",\n    \"Prolonged high occupancy counts in Kitchen and Entrance during early morning hours (06:00-09:00) suggesting potential unauthorized entry or a caregiver presence before the resident's usual wake-up time.\"\n  ],\n  \"why_these_chunks\": [\n    \"Chunks C00-C03 show the most critical data anomalies: extreme temperature values appearing at night/early morning when the home should be unoccupied or low-activity, triggering immediate safety alerts.\",\n    \"Chunk C04 marks the transition point where normal occupancy patterns resume (Kitchen and Bedroom active), establishing a baseline to compare against the earlier suspicious activity.\"\n  ]\n}\n\n## Investigator\n{\n  \"normal_hypotheses\": [\n    {\n      \"id\": \"N1\",\n      \"description\": \"Systematic sensor calibration error or unit conversion bug affecting all temperature sensors simultaneously.\",\n      \"evidence\": [\"All rooms report values >2000°C consistently from 00:00 to 07:20, which is physically impossible for ambient room conditions.\", \"The relative difference between rooms (e.g., Kitchen ~230-250 higher than Bedroom) remains constant over time, suggesting a fixed offset or scaling factor error rather than dynamic heat sources.\"],\n      \"weaknesses\": [\"Does not explain the specific behavioral anomalies in occupancy and lock states observed later in the log.\", \"Cannot account for the sudden appearance of valid-looking low-temperature readings mixed with nulls at 06:08 and 06:41 if it were purely a software bug; hardware failure patterns usually differ.\"]\n    },\n    {\n      \"id\": \"N2\",\n      \"description\": \"Resident's morning routine began unusually early due to health reasons or external events.\",\n      \"evidence\": [\"Occupancy sensors show activity starting at 05:33 in the bedroom.\", \"Lights turned on in bedroom (05:33) and bathroom (05:39).\", \"Cooking surface activated at 06:07.\"],\n      \"weaknesses\": [\"Completely ignores the extreme temperature data which triggers the initial security alert.\", \"Fails to explain why a"}}