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）

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.

Explanation: Analysis of Chunk C06 confirms that at 17:22:00, the cook surface state changed to 'False' (off).

Explanation: 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.

Explanation: 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.

Explanation: 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.

Explanation: Therefore, the event is classified as a transient sensor malfunction or communication glitch rather than a security intrusion or persistent safety threat.

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.

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.

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.

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.

Suspicious automated or remote departure sequence occurring during high activity periods.

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.

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).

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.

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.

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.

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.

## Query
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。

## Layout
Layout: 独居老人 (Elderly Living Alone)
- 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>
- 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>
- 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>
- 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>
- 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>

## Deterministic 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": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-16T11:55:00",
    "end_ts": "2026-06-16T12:49:03",
    "event_count": 80,
    "rooms": {
      "living_room": 22,
      "bedroom": 23,
      "kitchen": 22,
      "entrance": 11,
      "bathroom": 2
    },
    "top_devices": [
      "living_room_temp_sensor",
      "bedroom_temp_sensor",
      "kitchen_temp_sensor",
      "kitchen_occupancy",
      "bedroom_occupancy",
      "entrance_occupancy"
    ],
    "alarmish_count": 45,
    "preview_lines": [
      "[2026-06-16T11:55:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2521",
      "[2026-06-16T11:55:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2440",
      "[2026-06-16T11:55:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2530",
      "[2026-06-16T11:55:00] kitchen_occupancy | OccupancySensing.Occupancy = 1",
      "[2026-06-16T11:57:00] bedroom_occupancy | OccupancySensing.Occupancy = 1",
      "[2026-06-16T11:59:03] entrance_occupancy | OccupancySensing.Occupancy = 1",
      "[2026-06-16T11:59:08] living_room_occupancy | OccupancySensing.Occupancy = 1",
      "[2026-06-16T12:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2520",
      "[2026-06-16T1

## Query
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。

## Triage
{
  "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
{
  "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


FG-02-FP: 电暖器/取暖器正常使用

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

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.

Explanation: 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.

Explanation: 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.

Explanation: 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.

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.

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.

Coincides with high-frequency entrance occupancy events and door cycling which could be genuine intruder behavior masked by noise.

Active intrusion with environmental tampering or distraction tactics.

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.

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.

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.

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.

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.

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.

## Query
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。

## Layout
Layout: 两室一厅 (2BR)
- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>
- 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>
- 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>
- 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>
- 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>
- 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>
- 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>

## Deterministic 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": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-01T00:00:00",
    "end_ts": "2026-06-01T01:20:00",
    "event_count": 80,
    "rooms": {
      "living_room": 20,
      "master_bedroom": 19,
      "second_bedroom": 19,
      "kitchen": 16,
      "bathroom": 3,
      "entrance": 3
    },
    "top_devices": [
      "living_room_temp_sensor",
      "master_bedroom_temp_sensor",
      "second_bedroom_temp_sensor",
      "kitchen_temp_sensor",
      "living_room_occupancy",
      "master_bedroom_occupancy"
    ],
    "alarmish_count": 15,
    "preview_lines": [
      "[2026-06-01T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2278",
      "[2026-06-01T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2267",
      "[2026-06-01T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2276",
      "[2026-06-01T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2267",
      "[2026-06-01T00:00:00] living_room_occupancy | OccupancySensing.

## Query
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。

## Triage
{
  "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
{
  "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-f


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

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.

Explanation: 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).

Explanation: 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.

Explanation: 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.

Explanation: 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.

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.

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.

```json
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "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.",
      "evidence": [
        "C00 shows consistent readings around 2269-2298 across all rooms, which correlates with typical indoor temperatures if divided by ~8-9.",
        "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.",
        "Occupancy and light data function normally (e.g., entrance occupancy = 1 at 18:21), indicating the communication protocol and logic gates are working."
    ]
  ],
  "anomaly_hypotheses": [
    {
      "id": "A1",
      "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.",
      "threat_type": "Fire/Safety Hazard",
      "evidence": [
        "C15 18:25: Kitchen reports 2697 vs Living Room 2316. If normalized, this is a massive differential (>40°C difference).",
        "C15 18:30-18:55: Kitchen temperature remains erratic and high (2717 -> 2695 -> 2619 -> 2576) while living room stabilizes around 2300.",
        "C15 18:59: 'kitchen_cook_surface' turns ON; 'kitchen_light' turns ON.",
        "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."
    },
    {
      "id": "A2",
      "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.",
      "threat_type": "Monitoring Blindspot",
      "evidence": [
        "C15 19:00:00: Value explicitly logged as 'None' for kitchen_temp_sensor.",
        "C16 19:49:00: Value explicitly logged as 'None' for kitchen_temp_sensor shortly after cook surface turned off.",
        "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."
    }
  ],
  "most_discriminative_evidence": [
    "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.",
    "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).",
    "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."
  ],
  "missing_information": [
    "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.",
    "Smoke detector status: No logs indicate smoke detection events during the kitchen temperature spike.",
    "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'.",
    "Cook Surface Type: Is it an induction coil, gas stove, or electric radiant heater? This affects the expected heat signature."
  ]
}
```

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.

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.

## Query
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。

## Layout
Layout: 两室一厅 (2BR)
- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>
- 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>
- 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>
- 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>
- 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>
- 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>
- 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>

## Deterministic 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": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-22T00:00:00",
    "end_ts": "2026-06-22T01:20:00",
    "event_count": 80,
    "rooms": {
      "living_room": 20,
      "master_bedroom": 19,
      "second_bedroom": 19,
      "kitchen": 16,
      "bathroom": 3,
      "entrance": 3
    },
    "top_devices": [
      "living_room_temp_sensor",
      "master_bedroom_temp_sensor",
      "second_bedroom_temp_sensor",
      "kitchen_temp_sensor",
      "living_room_occupancy",
      "master_bedroom_occupancy"
    ],
    "alarmish_count": 15,
    "preview_lines": [
      "[2026-06-22T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2269",
      "[2026-06-22T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2262",
      "[2026-06-22T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2262",
      "[2026-06-22T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2276",
      "[2026-06-22T00:00:00] living_room_occupancy | OccupancySensing.

## Query
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。

## Triage
{
  "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
```json
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "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.",
      "evidence": [
        "C00 shows consistent readings around 2269-2298 across all rooms, which correlates with typical indoor temperatures if divided by ~8-9.",
        "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.",
        "Occupancy and light data function normally (e.g., entrance occupancy = 1 at 18:21), indicating the communication protocol and


CH-01-FP: 孩子生病请假在家（家长陪护）

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

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.

Explanation: 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.

Explanation: 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.

Explanation: 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.

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.

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.

Sensor Calibration Drift / Unit Error

A real-world household cannot sustain internal temperatures above 100°C without structural damage or fire; this physical impossibility invalidates the 'normal' hypothesis.

Systematic Data Logging Artifact

Occupancy sensors report '0' for all rooms continuously from 00:00 until 06:12, despite the massive thermal energy accumulation implied by the logs.

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.

Critical Sensor Failure Leading to False Alarms

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.

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.

Potential Unauthorized Entry with Sensor Blind Spot

Security Breach (High Probability due to data noise)

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.

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.

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.

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.

Sensor Calibration Drift / Unit Error

Systematic Data Logging Artifact

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.

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.

## Query
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。

## Layout
Layout: 三室两厅 (3BR)
- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>
- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>
- 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>
- 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>
- 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>
- 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>
- 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>
- 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>
- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>
- 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>

## Deterministic 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": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-17T00:00:00",
    "end_ts": "2026-06-17T01:10:00",
    "event_count": 80,
    "rooms": {
      "living_room": 18,
      "master_bedroom": 18,
      "kids_room": 18,
      "kitchen": 14,
      "dining_room": 3,
      "second_bedroom": 3,
      "master_bathroom": 3,
      "entrance": 3
    },
    "top_devices": [
      "living_room_temp_sensor",
      "master_bedroom_temp_sensor",
      "kids_room_temp_sensor",
      "kitchen_temp_sensor",
      "living_room_occupancy",

## Query
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。

## Triage
{
  "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
{
  "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 'n


只在儿童房一个房间内发生，kids_room_occupancy=1，有小孩在场

System-wide sensor calibration failure causing physically impossible temperature readings that falsely indicate a critical overheating event.

Explanation: 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).

Explanation: 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.

Explanation: 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.

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.

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.

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.

Critical Sensor Calibration Failure / Data Encoding Error causing false high-temperature readings.

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).

Does not explain the 'heat' threat itself unless the system logic misinterprets these numbers as a fire risk, triggering unnecessary alarms.

Undetected Fire or Uncontrolled Heat Source leading to actual overheating.

Continuous upward trend in temperature readings throughout the monitoring period.

High absolute values (if interpreted correctly as scaled integers) indicate extreme heat.

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.

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.

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.

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.

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.

## Query
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。

## Layout
Layout: 三室两厅 (3BR)
- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>
- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>
- 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>
- 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>
- 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>
- 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>
- 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>
- 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>
- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>
- 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>

## Deterministic 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": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-09T00:00:00",
    "end_ts": "2026-06-09T01:10:00",
    "event_count": 80,
    "rooms": {
      "living_room": 18,
      "master_bedroom": 18,
      "kids_room": 18,
      "kitchen": 14,
      "dining_room": 3,
      "second_bedroom": 3,
      "master_bathroom": 3,
      "entrance": 3
    },
    "top_devices": [
      "living_room_temp_sensor",
      "master_bedroom_temp_sensor",
      "kids_room_temp_sensor",
      "kitchen_temp_sensor",
      "living_room_occupancy",

## Query
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。

## Triage
{
  "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
{
  "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


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

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）

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.

Explanation: 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.

Explanation: 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.

Explanation: 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.

Explanation: 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.

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.

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.

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.

Relies on external knowledge of normal room temperatures; if the house is indeed kept at extreme heat (unlikely), this hypothesis fails.

Potential Security Breach / Tailgating Event at Entrance.

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.

Could be a pet, delivery driver, or family member moving between rooms (e.g., retrieving medication before bed).

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.

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.

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.

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.

## Query
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。

## Layout
Layout: 一室一厅 (Studio/1BR)
- 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>
- 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>
- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>
- 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>
- 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>

## Deterministic 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": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-02T00:00:00",
    "end_ts": "2026-06-02T01:40:00",
    "event_count": 80,
    "rooms": {
      "living_room": 26,
      "bedroom": 24,
      "kitchen": 26,
      "bathroom": 4
    },
    "top_devices": [
      "kitchen_temp_sensor",
      "living_room_temp_sensor",
      "bedroom_temp_sensor",
      "living_room_occupancy",
      "bedroom_occupancy",
      "bathroom_occupancy"
    ],
    "alarmish_count": 14,
    "preview_lines": [
      "[2026-06-02T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2281",
      "[2026-06-02T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2168",
      "[2026-06-02T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2274",
      "[2026-06-02T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-02T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-02T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-02T00:05:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2268",
      "[2026-06-02T00:05:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2168",

## Query
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。

## Triage
{
  "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
{
  "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 specific


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

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.

Explanation: 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.

Explanation: 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.

Explanation: 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.

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.

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.

No 'MeasuredValue' data points from the kitchen sensor during peak activity periods suggests a hardware failure rather than just environmental heat.

Sensor malfunction causing data drift and loss of calibration.

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.

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.

Unattended cooking leading to potential fire hazard and subsequent sensor failure.

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.

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.

Critical HVAC/Furnace failure resulting in lethal indoor environment.

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.

Cannot definitively distinguish between a single point failure (stove + no vent) vs. total system failure without historical baseline data.

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.

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.

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.

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.

## Query
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。

## Layout
Layout: 独居老人 (Elderly Living Alone)
- 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>
- 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>
- 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>
- 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>
- 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>

## Deterministic 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": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-03T00:00:00",
    "end_ts": "2026-06-03T01:35:00",
    "event_count": 80,
    "rooms": {
      "living_room": 24,
      "bedroom": 24,
      "kitchen": 24,
      "bathroom": 4,
      "entrance": 4
    },
    "top_devices": [
      "living_room_temp_sensor",
      "bedroom_temp_sensor",
      "kitchen_temp_sensor",
      "living_room_occupancy",
      "bedroom_occupancy",
      "kitchen_occupancy"
    ],
    "alarmish_count": 20,
    "preview_lines": [
      "[2026-06-03T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2276",
      "[2026-06-03T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2170",
      "[2026-06-03T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2276",
      "[2026-06-03T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-03T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-03T00:00:00] kitchen_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-03T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-03T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-03T00:05:00] li

## Query
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。

## Triage
{
  "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
{
  "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


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.

Explanation: 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.

Explanation: 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.

Explanation: 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.

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.

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.

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.

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.

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).

Ignores the massive temperature anomaly which could be a security risk indicator (e.g., fire suppression failure masked by bad data).

Sensor malfunction causing false alarm cascades; the 'alarmish_count' spikes are artifacts of the temperature scale error triggering threshold violations.

System Reliability / False Positive Security Alert

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.

If the alarm logic relies on rate-of-change rather than absolute value, this might not trigger alarms, contradicting the triage suspicion.

Potential unauthorized entry event during low-occupancy windows (C10 sequence), where lock manipulation occurred before resident arrival.

C10 starts with LockState=2 at 18:28:00, followed immediately by DoorContact=False (open) at 18:28:02.

Resident occupancy detection occurs 2 minutes after door contact opens.

Sequence implies someone unlocked/opened the door, then entered, then turned on lights.

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.

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.

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.

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.

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.

## Query
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。

## Layout
Layout: 一室一厅 (Studio/1BR)
- 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>
- 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>
- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>
- 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>
- 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>

## Deterministic 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": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-09T00:00:00",
    "end_ts": "2026-06-09T01:50:00",
    "event_count": 80,
    "rooms": {
      "living_room": 27,
      "bedroom": 27,
      "kitchen": 22,
      "bathroom": 4
    },
    "top_devices": [
      "living_room_temp_sensor",
      "bedroom_temp_sensor",
      "kitchen_temp_sensor",
      "living_room_occupancy",
      "bedroom_occupancy",
      "bathroom_occupancy"
    ],
    "alarmish_count": 12,
    "preview_lines": [
      "[2026-06-09T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2272",
      "[2026-06-09T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2163",
      "[2026-06-09T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2270",
      "[2026-06-09T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-09T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-09T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-09T00:05:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2268",
      "[2026-06-09T00:05:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2164",
      "[2026-06-09T00:05:00] kitchen_temp_sens

## Query
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。

## Triage
{
  "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
{
  "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


CH-04-FP: 家长在玄关操作门锁

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.

Explanation: 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.

Explanation: 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.

Explanation: 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.

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.

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.

Does not account for the specific door lock/unlock sequence occurring during occupied hours.

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.

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).

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

## Query
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。

## Layout
Layout: 三室两厅 (3BR)
- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>
- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>
- 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>
- 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>
- 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>
- 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>
- 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>
- 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>
- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>
- 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>

## Deterministic 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": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-25T00:00:00",
    "end_ts": "2026-06-25T01:10:00",
    "event_count": 80,
    "rooms": {
      "living_room": 18,
      "master_bedroom": 18,
      "kids_room": 18,
      "kitchen": 14,
      "dining_room": 3,
      "second_bedroom": 3,
      "master_bathroom": 3,
      "entrance": 3
    },
    "top_devices": [
      "living_room_temp_sensor",
      "master_bedroom_temp_sensor",
      "kids_room_temp_sensor",
      "kitchen_temp_sensor",
      "living_room_occupancy",

## Query
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。

## Triage
{
  "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
{
  "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 occup