LockDoor 命令后 LockState 未变为 Locked
DoorLockAlarm (LockJammed) 触发
门锁故障意味着家庭物理安全降级

通知住户门锁可能卡住/故障，建议手动检查

The entrance contact sensor exhibits a delayed state transition following manual locking, suggesting calibration drift or misalignment.

Explanation: In Chunk C04, a manual lock operation occurred at 07:17:23, immediately followed by the door contact sensor reporting 'False' (open) at 07:17:25 and returning to 'True' (closed) at 07:17:26.

Explanation: This creates a 2-second gap where the system believes the door is open while it is being locked, which contradicts normal mechanical behavior where the door should be closed immediately upon initiation of the closing mechanism.

Explanation: Chunks C03 and C05 contain no entry/exit events for the front door during this timeframe, preventing a direct comparison to rule out user error or specific environmental factors on that single day; however, the tight coupling between the lock actuation and the subsequent false negative strongly points to a hardware alignment issue.

Event sequence: LockOperation(Manual) @ 07:17:23 -> ContactSensor(False) @ 07:17:25 -> ContactSensor(True) @ 07:17:26.

The 2-second duration of the 'False' state is abnormally long for a standard door swing, indicating the sensor likely failed to register the initial closure phase.

Inspect the physical installation of the magnetic reed switch at the entrance to verify gap distance between the lock body and strike plate.

Perform sensor calibration or realignment if physical inspection reveals improper positioning.

```json
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The entrance sensor exhibits normal mechanical behavior during a manual door closure, where the magnetic reed switch is momentarily disengaged (False) as the door swings shut and immediately re-engages (True) once the door stops moving.",
      "evidence": [
        "Event at 07:17:23: Manual LockOperation initiated (Door closing).",
        "Event at 07:17:25: front_door_contact StateValue = False (Gap detected).",
        "Event at 07:17:26: front_door_contact StateValue = True (Gap closed)."
      ],
      "weaknesses": [
        "The 'False' state persisted for exactly 2 seconds (07:17:23 to 07:17:25), which is unusually long for a standard door swing unless there was significant air resistance or a heavy door mechanism."
      ]
    }
  ],
  "anomaly_hypotheses": [
    {
      "id": "A1",
      "description": "Front door contact sensor calibration drift or misalignment causing false negative readings.",
      "threat_type": "Sensor Malfunction / Calibration Drift",
      "evidence": [
        "Temporal correlation between LockState change and ContactSensor flip suggests the system might be interpreting the lock actuation as a door breach event.",
        "The sequence Lock->False->True implies the sensor did not register the 'closed' state immediately upon the start of the locking mechanism, potentially missing the initial closure phase.",
        "Low room_activity count (19) for entrance compared to other rooms suggests potential under-reporting of entry/exit events due to sensor unreliability."
      ],
      "weaknesses": [
        "No other data points in Chunk C04 show erratic flipping outside of this specific lock event."
      ]
    },
    {
      "id": "A2",
      "description": "Intermittent electrical connection or loose wiring in the entrance contact sensor.",
      "threat_type": "Hardware Failure",
      "evidence": [
        "The rapid transition from False back to True within 1 second could indicate a momentary signal dropout before stabilization, typical of loose connections."
      ],
      "weaknesses": [
        "The sensor quickly recovered to a stable 'True' state, which argues against a complete hardware failure like an open circuit."
      ]
    }
  ],
  "most_discriminative_evidence": [
    "The precise timestamp sequence: LockOperation(Manual) -> LockState=2 -> Contact=False -> Contact=True. This tight coupling suggests the contact sensor state is being triggered by the lock motor's movement rather than independent door motion.",
    "The duration of the 'False' state (2 seconds) relative to the speed of a typical door operation indicates a possible delay in signal propagation or mechanical lag."
  ],
  "missing_information": [
    "Historical data for the same time on previous days to compare if this pattern is recurrent or isolated.",
    "Raw voltage/current readings from the contact sensor during the 07:17:23-07:17:26 window to confirm signal integrity.",
    "Physical installation logs to verify the current gap distance between the lock body and the strike plate/reed switch."
  ]
}
```

Cross-reference with historical data from previous days to determine if the 'Lock->False->True' pattern is a recurring anomaly or an isolated incident.

Verify physical installation logs for gap distance between lock body and reed switch at the entrance.

The analysis is currently focused on a single event (Chunk C04) without sufficient context. To distinguish between a mechanical delay (Normal Hypothesis N1) and sensor drift/misalignment (Anomaly Hypothesis A1), it is necessary to check adjacent chunks (C03, C05) for similar door operations where the sensor behaved normally. If the same 2-second False state occurs during manual locking in other chunks, it likely indicates a systematic issue with that specific door mechanism rather than a sensor fault.

The investigator correctly identified missing raw signal data and historical trends, which are critical for validating the hypothesis of calibration drift versus normal behavior.

## Query
请检查以下设备状态历史，判断 entrance 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。

## 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": 400,
    "bedroom": 353,
    "kitchen": 298,
    "bathroom": 57,
    "entrance": 19
  },
  "attribute_frequency": {
    "MeasuredValue": 866,
    "Occupancy": 220,
    "OnOff": 18,
    "LockState": 6,
    "StateValue": 5,
    "CurrentPositionLiftPercent100ths": 2,
    "SystemMode": 1,
    "OperationalState": 1,
    "CurrentLevel": 1
  },
  "lock_state_flips": 6,
  "occupancy_events": 220,
  "temperature_patterns": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-22T00:00:00",
    "end_ts": "2026-06-22T01:50:00",
    "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": [
      "[2026-06-22T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2270",
      "[2026-06-22T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2176",
      "[2026-06-22T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2274",
      "[2026-06-22T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-22T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-22T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-22T00:05:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2280",
      "[2026-06-22T00:05:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2166",
      "[2026-06-22T00:05:00] kitchen_t

## Query
请检查以下设备状态历史，判断 entrance 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。

## Triage
{
  "latent_task_profile": "device-health | behavior-sequence",
  "focus_rooms": ["entrance"],
  "focus_devices": ["front_door_contact", "front_door_lock"],
  "focus_chunk_ids": ["C04"],
  "suspected_patterns": [
    "Contact sensor state transition mismatch (False -> True) immediately following lock operation",
    "Potential false positive entry event or sensor calibration drift"
  ],
  "why_these_chunks": [
    "Chunk C04 is the only segment containing 'entrance' room activity and specific events for 'front_door_contact' and 'front_door_lock'. The preview lines show a rapid sequence: LockState change, followed by ContactSensor StateValue= False, then immediately StateValue= True. This specific temporal correlation between the lock action and the contact state flip suggests a potential fault in the magnetic reed switch alignment or signal interpretation logic that requires inspection.",
    "No other chunks contain entrance-specific data, making C04 the sole source of truth for diagnosing the status of the entrance sensors."
  ]
}

## Investigator
```json
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The entrance sensor exhibits normal mechanical behavior during a manual door closure, where the magnetic reed switch is momentarily disengaged (False) as the door swings shut and immediately re-engages (True) once the door stops moving.",
      "evidence": [
        "Event at 07:17:23: Manual LockOperation initiated (Door closing).",
        "Event at 07:17:25: front_door_contact StateValue = False (Gap detected).",
        "Event at 07:17:26: front_door_contact StateValue = True (Gap closed)."
      ],
      "weaknesses": [
        "The 'False' state persisted for exactly 2 seconds (07:17:23 to 07:17:25), which is unusually long for a standard door swing unless there was significant air resistance or a heavy door mechanism."
      ]
    }
  ],
  "anomaly_hypotheses": [
    {
      "id": "A1",
      "description": "Front door contact sensor calibration drift or misalignment causing false negative readings.",
      "threat_type": "Sensor Malfunction / Calibration Drift",
      "evidence": [
        "Temporal correlation between LockState change and ContactSensor flip suggests the system might be interpreting the lock actuation as a door breach event.",
        "The sequence Lock->False->True implies the sensor did not register the 'closed' state immediately u


温度传感器读数固定（stuck-at）

Day1 温度有正常的日间波动（上午偏低、中午偏高、晚间回落）
Day2 中午开始读数完全固定在 23.50°C
连续24小时+完全无变化，真实温度不可能如此稳定

标记传感器可能故障，建议住户检查/更换

Kitchen sensors are reporting physically impossible temperatures due to a persistent x10 data scaling error or firmware bug.

Explanation: All temperature readings across all rooms (including kitchen) consistently exceed 2000, with values reaching up to 2493, which implies an ambient temperature of nearly 250°C if interpreted as Celsius.

Explanation: The reported values show a logical diurnal pattern consistent with real-world heating (gradual increase from ~227 to ~248), but the magnitude is off by a factor of exactly 10, indicating a systematic unit conversion failure rather than random noise or sensor drift.

Explanation: While other occupancy sensors function correctly (generating events when people enter rooms like the master bathroom), the specific temperature data format for the kitchen sensor is invalid for any standard residential HVAC logic.

kitchen_temp_sensor reports value 2493 at 2026-06-09T06:15:00, implying 249.3°C in a living space.

Consistent x10 ratio observed between expected residential temps (~22-25°C) and actual raw logs (227-248).

Reset or reboot the kitchen temperature sensor to clear potential firmware state corruption.

Check the device configuration or aggregator settings to verify if the 'Deci-Celsius' unit multiplier was incorrectly applied globally or locally.

The kitchen temperature sensor has a firmware or calibration error causing a persistent x10 multiplication overflow, rendering all readings invalid for standard control logic.

Raw values consistently exceed realistic residential thresholds (e.g., 2480 implies 248°C, far above boiling point).

The `attribute_frequency` shows only 7 `StateValue` events but 1166 `MeasuredValue` events, indicating the system relies heavily on these inflated numbers for state determination.

No `temperature_patterns` were detected in the structured signals, likely because the parsing engine failed to normalize the x10 factor automatically.

If this is a global system artifact affecting all rooms, the issue might be in the central aggregator rather than the specific kitchen sensor hardware.

The kitchen occupancy sensor is completely non-functional or disconnected, resulting in zero event generation despite high activity counts in adjacent rooms.

Structured signal `room_activity` shows 313 events for the kitchen vs 398 for the living room, yet no `OccupancySensing.Occupancy` events appear for the kitchen in any chunk.

In contrast, other rooms like the master bathroom show discrete event logs (e.g., C04: Occupancy=1, Light=OnOff=True).

Suspected pattern explicitly notes: 'Missing occupancy sensor events in the kitchen despite high activity counts in other rooms'.

High activity counts in the kitchen could theoretically stem from window/door sensors if they were active, though the triage output suggests their absence as well.

Consistent presence of TemperatureMeasurement.MeasuredValue = ~2300-2480 across all chunks, which maps to >23°C only if divided by 10, creating a physical impossibility for normal residential cooking environments without normalization.

Complete absence of `OccupancySensing` log lines for `kitchen_occupancy` throughout the entire 6+ hour timeline, unlike other rooms which log periodic states.

The raw unit definition or schema for `TemperatureMeasurement.MeasuredValue` to confirm if 'Celsius' or 'Deci-Celsius' is expected.

Hardware status flags (e.g., battery level, last heartbeat timestamp) for the kitchen sensors to rule out total power failure.

Activity logs specifically for windows/doors in the kitchen to verify if the lack of occupancy data is due to a missing sensor type entirely or a malfunctioning one.

Verify hardware status flags (battery level, last heartbeat) for kitchen sensors to rule out power failure.

Check raw schema/unit definition for TemperatureMeasurement.MeasuredValue to confirm expected units (Celsius vs Deci-Celsius).

Review activity logs specifically for window/door sensors in the kitchen to distinguish between missing sensor type and malfunction.

The investigator has correctly identified potential anomalies (temperature scaling x10 and missing occupancy events) based on the provided chunks C00-C28.

However, the evidence is insufficient to definitively diagnose the root cause. The analysis currently relies on correlation with other rooms but lacks direct hardware diagnostics (status flags) and schema definitions required to confirm if the temperature issue is a data format error or a hardware fault.

The current chunk selection covers the entire timeline, so no additional chunks are needed; the gap lies in the specific fields within those chunks that were not analyzed yet.

Proceed to extract metadata and status fields from the existing chunks rather than requesting new time-based chunks.

## Query
请检查以下设备状态历史，判断 kitchen 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。

## 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": 515,
    "kids_room": 515,
    "kitchen": 313,
    "dining_room": 223,
    "second_bedroom": 48,
    "master_bathroom": 56,
    "entrance": 227,
    "second_bathroom": 1
  },
  "attribute_frequency": {
    "MeasuredValue": 1166,
    "Occupancy": 1082,
    "OnOff": 26,
    "StateValue": 7,
    "LockState": 5,
    "CurrentPositionLiftPercent100ths": 3,
    "SystemMode": 1,
    "OperationalState": 1
  },
  "lock_state_flips": 5,
  "occupancy_events": 1082,
  "temperature_patterns": []
}

## 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_occupa

## Query
请检查以下设备状态历史，判断 kitchen 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。

## Triage
{
  "latent_task_profile": "device-health",
  "focus_rooms": [
    "kitchen"
  ],
  "focus_devices": [
    "kitchen_temp_sensor",
    "kitchen_window_sensor",
    "kitchen_occupancy_sensor"
  ],
  "focus_chunk_ids": [
    "C00",
    "C01",
    "C02",
    "C03",
    "C04",
    "C05",
    "C06",
    "C07",
    "C08",
    "C09",
    "C10",
    "C11",
    "C12",
    "C13",
    "C14",
    "C15",
    "C16",
    "C17",
    "C18",
    "C19",
    "C20",
    "C21",
    "C22",
    "C23",
    "C24",
    "C25",
    "C26",
    "C27",
    "C28"
  ],
  "suspected_patterns": [
    "Temperature values are consistently scaled by a factor of ~10 (e.g., 22.7°C reported as 227)",
    "Missing occupancy sensor events in the kitchen despite high activity counts in other rooms",
    "Absence of window/door contact sensor events for the kitchen area throughout the entire log"
  ],
  "why_these_chunks": "All chunks are required to perform a longitudinal health check. The analysis must verify if the temperature scaling is a global system artifact or isolated to the kitchen sensor, and confirm if the lack of specific event types (occupancy/window state) in the kitchen is consistent across all time periods or sporadic."
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The kitchen temperature sensor is functioning correctly, and the high numerical values (e.g., 2400) represent a valid data format where temperature in Celsius is multiplied by 10.",
      "evidence": [
        "All room sensors report consistent scaling factors (~10x), suggesting a global system configuration rather than an isolated hardware fault.",
        "Temperature values show logical diurnal variation patterns (gradual increase over time from ~227 to ~248), consistent with ambient heating or appliance usage."
      ],
      "weaknesses": [
        "Standard HVAC systems rarely operate at temperatures exceeding 45°C (450 on this scale); while possible in extreme industrial settings, residential peaks of 24.8°C are typical, making 2480 physically improbable for a standard living space unless it is a specialized server room or sauna, which contradicts the 'kitchen' label."
      ]
    }
  ],
  "anomaly_hypotheses": [
    {
      "id": "A1",
      "description": "The kitchen temperature sensor has a firmware or calibration error causing a persistent x10 multiplication overflow, rendering all readings inv


运动传感器高频率周期性触发 该房间无其他活动迹象（灯关、无门窗事件） 周期性极其规律（不像人类活动的随机性）

The second_bedroom_temp_sensor exhibits severe calibration drift or data integrity failure, reporting physically impossible values that diverge significantly from peer sensors without correlating to environmental changes.

Explanation: All sensors report values in the range of 2300-2550, which is physically unrealistic for Celsius (indoor temps are typically 18-30°C), suggesting a raw integer scale where ~23.5°C corresponds to 2350. Despite this scaling, the divergence pattern is anomalous.

Explanation: While all sensors show an upward trend initially (likely due to external heat gain or AC failure), the second_bedroom sensor shows a distinct, steady linear ascent (e.g., 2352 -> 2400 -> 2450) that continues even when other rooms fluctuate or plateau.

Explanation: At 07:48, occupancy is detected in the second bedroom, yet the high temperature reading was already established hours prior and does not spike further upon human entry, ruling out body heat as the cause.

Explanation: The gap between the second_bedroom sensor and others widens over time (from ~1 unit difference to ~30+ units), indicating a local fault such as a stuck incrementer, firmware overflow, or specific sensor aging rather than a global ambient shift.

Second bedroom sensor reads 2523 at 07:35 while living_room reads 2530; however, the trajectory of the second bedroom sensor (steady linear climb) contrasts sharply with the noisy fluctuations of others.

Occupancy event at 07:48 in the second bedroom occurs after the anomaly has persisted for hours, confirming the reading is not caused by local thermal sources.

No status flags (battery/signal) are provided to rule out power-induced drift, but the magnitude of divergence (~3% error relative to absolute value, growing larger) points to a hardware/software fault.

Reset the second_bedroom_temp_sensor node immediately to clear potential temporary state corruption.

Inspect the physical sensor location for obstructions or direct sunlight exposure causing localized heating not seen elsewhere.

Replace the sensor if the reset fails, as the device appears to have suffered irreversible calibration drift or component failure.

At 01:30, while living_room drops to 2301 and master_bedroom rises to 2316, second_bedroom jumps anomalously to 2317, breaking the initial cluster stability.

From 02:40 onwards, second_bedroom readings consistently diverge upwards, reaching 2523 by 07:35, while kitchen and living_room stabilize around 2520-2529.

The gap widens specifically when occupancy events occur in other rooms (e.g., entrance at 07:24), but not in the second bedroom until 07:48, yet the temperature anomaly persists regardless of local occupancy changes.

The 'MeasuredValue' attribute appears to be scaling incorrectly or hitting a saturation point unique to this sensor node compared to peers.

There is no direct evidence that the *other* sensors are wrong; they could also be drifting together if the entire system clock or base offset is corrupted globally.

Given the triage output suggests 'Temperature drift', A1 is the strongest candidate. The evidence shows second_bedroom leading the pack in value increase after the initial synchronization phase, indicating a local fault.

Divergence in rate of change: After 02:40, second_bedroom continues to climb steadily (e.g., 2352 -> 2523), whereas kitchen and living_room fluctuate more erratically or plateau slightly earlier.

Occupancy Context Mismatch: At 07:48, occupancy detects presence in second_bedroom, yet the temperature spike was already established before this event, ruling out body heat as the primary cause for the anomalous high reading.

Cross-Sensor Discrepancy: At 07:35, second_bedroom reads 2523 while living_room reads 2530. While close, the trajectory of second_bedroom (steady linear ascent) contrasts with the noisy fluctuations of others, pointing to a stuck incrementer or offset error specific to the second bedroom node.

The definition of the 'MeasuredValue' unit (Celsius, Fahrenheit, Kelvin, or an internal integer scale?) to determine if 2300-2530 represents a realistic temperature or a raw register value overflow.

Historical baseline data for these specific sensors prior to 2026-06-08 to confirm if the current trajectory is a new deviation or part of a long-term degradation pattern.

Status flags for the second_bedroom sensor (e.g., BatteryLevel, SignalStrength, SelfTestResult) which might indicate power issues causing intermittent calibration loss.

Verify data unit definition for values >2000 (Overflow vs Real Temp)

Check sensor status flags (Battery/Signal) in C06-C08

Cross-reference with 'empty room' logs in later chunks to rule out delayed HVAC response

The analysis correctly identifies the divergence pattern but relies heavily on early chunks (C01-C05) and Triage suggestions.

Triage output incorrectly included C15-C06 as a chunk range; evidence suggests C06 is critical for observing the stabilization of other sensors mentioned by the investigator.

Missing chunks C06-C08 are necessary to confirm if the anomaly persists after the initial spike or if it resolves, and to check for late-stage occupancy events that might explain the discrepancy.

Crucially, the raw values (~2300-2530) are physically unrealistic for Celsius without knowing the unit scale. This fundamental ambiguity must be resolved before concluding 'calibration drift'; this requires metadata often found in the full log sequence.

## Query
请检查以下设备状态历史，判断 second_bedroom 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。

## 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": 399,
    "master_bedroom": 336,
    "second_bedroom": 341,
    "kitchen": 298,
    "bathroom": 52,
    "entrance": 230
  },
  "attribute_frequency": {
    "MeasuredValue": 1154,
    "Occupancy": 473,
    "OnOff": 14,
    "StateValue": 5,
    "LockState": 4,
    "SystemMode": 1,
    "OperationalState": 1
  },
  "lock_state_flips": 4,
  "occupancy_events": 473,
  "temperature_patterns": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-08T00:00:00",
    "end_ts": "2026-06-08T01:20:00",
    "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": [
      "[2026-06-08T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2271",
      "[2026-06-08T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2267",
      "[2026-06-08T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2269",
      "[2026-06-08T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2271",
      "[2026-06-08T00:00:00] living_room_occupancy | Occ

## Query
请检查以下设备状态历史，判断 second_bedroom 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。

## Triage
{
  "latent_task_profile": "device-health",
  "focus_rooms": ["second_bedroom", "kitchen", "living_room"],
  "focus_devices": [
    "second_bedroom_temp_sensor",
    "kitchen_temp_sensor",
    "living_room_temp_sensor"
  ],
  "focus_chunk_ids": ["C01", "C02", "C03", "C04", "C05", "C15", "C16"],
  "suspected_patterns": [
    "Temperature drift indicating calibration failure or sensor aging",
    "Discrepancy between reported temperature and occupancy context (e.g., high temp when room is empty)"
  ],
  "why_these_chunks": [
    "C01-C05: Show a progressive, unrealistic rise in second_bedroom_temp_sensor readings (from ~2270 to ~2530) while other sensors remain relatively stable or follow a different curve, suggesting a specific sensor fault rather than ambient heating.",
    "C15-C06: Kitchen sensor spikes significantly higher than living_room during AC operation, indicating potential sensor saturation or offset issues compared to the main living area.",
    "Cross-validation needed: Comparing these chunks against 'empty' state logs to confirm if the high temperatures persist without heat sources present."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "All sensors are functioning correctly, recording a uniform rise in ambient temperature due to external factors (e.g., HVAC failure or solar gain) affecting the entire house simultaneously.",
      "evidence": ["All room sensors show a consistent upward trend from ~23°C (represented as 230x) to ~25.3°C (represented as 253x).", "The relative ordering of temperatures between rooms remains stable throughout the log period."],
      "weaknesses": ["The absolute values (e.g., 2530) exceed standard Celsius ranges for indoor environments unless using a specific scaled unit not indicated, suggesting a potential logging artifact rather than physical reality.", "Even if scaled, the magnitude of change (~2.3 units over 7 hours) is rapid and synchronized across all zones without any localized heat source activation."]
    }
  ],
  "anomaly_hypotheses": [
    {
      "id": "A1",
      "description": "The second_bedroom_temp_sensor is suffering from severe calibration drift or firmware overflow, reporting values significantly higher than other valid sensors.",
      "threat_type": "Sensor Calibration Failure / Data Integrity Error",
      "evidence": ["At 01:30, while living_room drops to 2301 an


只有1-2次错误（非连续多次），最终成功解锁且 UserIndex 是合法用户

The kitchen temperature sensor is reporting physically impossible values (2400K-2700K) for an extended period, indicating a severe hardware malfunction or calibration failure rather than a real environmental hazard.

Explanation: Analysis of Chunks C10 and C11 reveals sustained readings from the kitchen_temp_sensor ranging between 2578K and 2710K, which equates to temperatures exceeding 2300°C. This is physically impossible for any indoor residential environment or standard cooking appliance.

Explanation: While living room and bedroom sensors show consistent, plausible readings (~2300K-2500K), the kitchen sensor data shows a clear divergence that persists even after cooking activities ceased and temperatures normalized in other rooms, confirming the anomaly is isolated to this specific device.

Explanation: The temporal correlation with 'Occupancy=1' creates a safety paradox where the system would attempt to cool a non-existent molten environment, confirming the data integrity failure rather than a genuine fire event.

Kitchen sensor reading of 2710K (approx. 2436°C) at 18:40:00 in Chunk C10.

Consistent normal temperature readings (~2300K) from adjacent living_room_temp_sensor during the same timeframe, isolating the fault to the kitchen sensor.

Immediately disable the kitchen_temp_sensor in the automation logic to prevent erroneous HVAC commands.

Schedule physical inspection and replacement of the kitchen temperature sensor due to internal component failure.

Verify the integrity of the sensor's wiring and power supply to rule out external electrical noise causing the drift.

Critical Sensor Malfunction or Calibration Drift creating false safety signals; specifically, the kitchen temperature sensor reports values >2500K (approx. 2227°C) which indicates either total sensor failure, exposure to fire, or severe data spoofing.

Environmental Hazard / Data Integrity Failure

C10 records kitchen_temp_sensor values ranging from 2578K to 2710K between 18:15 and 19:35. These values correspond to temperatures exceeding 2300°C, far beyond any domestic environment or even a gas flame.

This anomaly coincides with reported 'Occupancy=1' and 'AC Activation', creating a logical contradiction where the thermostat attempts to cool an area that is effectively molten.

The sensor returns 'None' intermittently (18:50, 19:54) during these extreme readings, suggesting hardware saturation or communication loss.

No concurrent fire alarms or smoke detector events are explicitly logged in the provided chunks to confirm physical combustion.

Perimeter Security Compromise involving lock manipulation and unauthorized entry simulation.

C04 logs a 'LockOperationError' at 07:23:00 immediately preceding a successful lock operation and door contact flip, which may indicate a forced entry attempt or electronic tampering before the door was secured.

Multiple lock_state_flips (4 total) recorded in structured signals suggest frequent state changes inconsistent with a single entry/exit event.

The subsequent successful lock operation and auto-lock suggests the system recovered or the event was authorized by a legitimate user (UserIndex=1).

The absolute magnitude of the kitchen temperature readings in Chunk C10 (2709K = ~2436°C) is the primary discriminator. This value is physically impossible for indoor air and rules out 'normal cooking heat' as an explanation, pointing definitively to sensor failure, hardware malfunction, or malicious data injection.

The temporal correlation between the impossible temperature spike and the presence of occupants ('Occupancy=1') creates an immediate health/safety paradox not explained by standard HVAC logic.

Raw voltage/current readings or signal integrity metrics for the kitchen_temp_sensor to determine if the reading is electrical noise or a valid (but impossible) measurement.

Logs from other thermal sensors (smoke detectors, wall-mounted thermostats) to see if they detected the alleged 2700°C environment.

Video footage or motion detection specifics around the entrance during the 07:23:00 error event to verify if a person was present during the lock error.

Verify raw signal integrity or voltage readings for kitchen_temp_sensor in C10 to rule out electrical noise/spike.

Cross-reference logs from smoke detectors and other thermal sensors to confirm the impossibility of a 2700°C indoor environment.

Review video footage or specific motion data around entrance during the 07:23:00 LockOperationError event.

The analysis correctly identifies the critical anomaly (physically impossible temperature) and the potential security breach (lock error).

However, the current evidence is insufficient because it relies solely on the suspect chunks (C04, C10, C11) without corroborating data from surrounding timeframes or alternative sensor types.

Chunk C03 should be checked to see if the lock error was an isolated incident or part of a pattern leading up to it.

Chunk C05 is needed to establish the baseline status immediately following the kitchen anomaly to determine if conditions normalized or persisted.

Without checking additional thermal sensors or raw signal data, we cannot definitively distinguish between catastrophic failure, sensor spoofing, or simple calibration drift.

## Query
以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。

## 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": 401,
    "bedroom": 354,
    "kitchen": 298,
    "bathroom": 57,
    "entrance": 17
  },
  "attribute_frequency": {
    "MeasuredValue": 866,
    "Occupancy": 222,
    "OnOff": 18,
    "StateValue": 6,
    "LockState": 4,
    "CurrentPositionLiftPercent100ths": 2,
    "SystemMode": 1,
    "OperationalState": 1,
    "CurrentLevel": 1
  },
  "lock_state_flips": 4,
  "occupancy_events": 222,
  "temperature_patterns": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-02T00:00:00",
    "end_ts": "2026-06-02T01:50:00",
    "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": [
      "[2026-06-02T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2274",
      "[2026-06-02T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2165",
      "[2026-06-02T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2271",
      "[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 = 2276",
      "[2026-06-02T00:05:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2178",
      "[2026-06-02T00:05:00] kitchen_temp_sensor | Temperature

## Query
以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。

## Triage
{
  "latent_task_profile": "single-event-safety | composite-safety",
  "focus_rooms": ["entrance", "kitchen", "living_room"],
  "focus_devices": ["front_door_lock", "front_door_contact", "kitchen_temp_sensor", "living_room_ac", "living_room_occupancy"],
  "focus_chunk_ids": ["C04", "C10", "C11"],
  "suspected_patterns": [
    "lock_operation_failure_preceding_entry",
    "abnormal_temperature_elevation_during_high_activity"
  ],
  "why_these_chunks": [
    "Chunk C04 captures a critical sequence: a LockOperationError immediately followed by a successful lock operation and door contact flip, indicating potential tampering or malfunction upon entry.",
    "Chunks C10 and C11 show sustained high temperatures in the kitchen (2578K-2630K) coinciding with living room occupancy and AC activation, suggesting a heating anomaly or sensor calibration drift that requires immediate health verification.",
    "The combination of mechanical failure at the perimeter (entrance) and thermal anomalies inside suggests a multi-vector safety event requiring cross-referencing."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The event represents a series of benign household activities: a resident returning home, cooking dinner in the kitchen, and normal temperature fluctuations due to appliance usage.",
      "evidence": [
        "C04 shows a standard entry sequence: LockOperationError followed immediately by successful locking and door contact flip, consistent with user interaction or minor sensor noise.",
        "C10 and C11 show typical daily patterns: AC activation upon occupancy (18:12), cooking surface usage (18:49), and dishwasher operation (20:13).",
        "Room activity counts are high in living room and bedroom, suggesting occupied residential use rather than intrusion."
      ],
      "weaknesses": [
        "Kitchen temperature values in C10 (e.g., 2709) are physically impossible for ambient air sensors, indicating potential data corruption or mislabeling of device type.",
        "The sequence in C04 involves an error state that, while common, is a deviation from ideal system behavior requiring verification."
      ]
    }
  ],
  "anomaly_hypotheses": [
    {
      "id": "A1",
      "description": "Critical Sensor Malfunction or Calibration Drift creating false safety signals; specifically, the kitchen temperature sensor reports values >2500K (approx. 2227°C) which


通知住户该区域烟雾报警器失灵，建议立即更换，期间注意防火

The kitchen temperature sensor has suffered a hardware failure or communication loss, indicated by erratic readings prior to the incident and a definitive transition to 'None' immediately following stove activation.

Explanation: Step 1: Baseline analysis of chunks C00/C01 shows the sensor was operational but exhibited higher noise/instability compared to other room sensors (e.g., jumping between 2312-2327), suggesting early-stage degradation.

Explanation: Step 2: Chunk C16 reveals a critical sequence where the `kitchen_smoke_alarm` logged a `HardwareFaultAlert` at 18:05:00, coinciding with a general drop in temperatures across all sensors, indicating a potential shared power or environmental stress event.

Explanation: Step 3: The most conclusive evidence is at 18:32:00 in chunk C16; immediately after the `kitchen_cook_surface` turned ON at 18:31:30, the `kitchen_temp_sensor` value dropped from 2300 to `None`. This instantaneous data loss signifies a hard sensor failure or disconnection rather than normal drift or calibration error.

Explanation: Step 4: Although the sensor briefly returned a value at 18:35:00 (2297) and again at 18:55:00 (2306), these intermittent recoveries are characteristic of unstable failing hardware attempting to reconnect before permanent failure or reset.

Explanation: Step 5: Chunk C17 confirms the instability persists, with another instance of `None` at 18:53:00, solidifying the diagnosis of an intermittent but severe malfunction.

At 18:32:00, the sensor reading changed abruptly from a valid number (2300) to 'None' exactly one minute after the cooking surface was activated.

A concurrent 'HardwareFaultAlert' was logged on the adjacent kitchen smoke alarm at 18:05:00, suggesting a shared circuit issue or environmental trigger affecting multiple kitchen devices.

The sensor displayed erratic fluctuations (e.g., 2312 -> 2327 -> 2317) in minutes preceding the total failure, which is inconsistent with stable sensor behavior.

Immediately replace the kitchen temperature sensor as it is no longer reliable for monitoring high-temperature events during cooking.

Inspect the kitchen's power distribution and check the status of the smoke alarm to ensure the fault was not due to a broader electrical surge affecting the zone.

Review historical logs for any other kitchen appliances that may have failed simultaneously to determine if this was a systemic power issue.

At 18:05:00, the `kitchen_smoke_alarm` explicitly reports `HardwareFaultAlert = True` and `Event: HardwareFault()`. While this is on the smoke alarm, the proximity suggests a shared power bus or environmental stressor (overheat) affecting kitchen devices.

At 18:31:30, the `kitchen_cook_surface` turns ON, initiating a heating event.

Immediately following this, at 18:32:00, the `kitchen_temp_sensor` returns `TemperatureMeasurement.MeasuredValue = None`, a definitive sign of sensor disconnection, battery death, or internal error preventing measurement.

Prior to the fault, the sensor showed erratic fluctuations (e.g., jumping from 2312 to 2327 to 2317 in minutes) compared to the smoother trends of other sensors, suggesting early instability before total failure.

The specific error code 'HardwareFault' was logged on the *smoke* alarm, not directly on the temperature sensor, though they likely share a cause. It is possible the temp sensor failed silently without triggering its own explicit fault log in the provided snippet, relying instead on the missing value.

The kitchen sensor exhibits calibration drift or offset errors relative to the rest of the house, leading to inaccurate occupancy-based logic if used for climate control.

In chunks C00/C01, while the master bedroom reaches ~23.4°C, the kitchen fluctuates between 22.8°C and 23.3°C even when the house is warming up, showing inconsistent tracking compared to the living room which rises more steadily to 23.6°C.

During the evening event (C16), the kitchen sensor reads 2300 (23.0°C) while the living room is at 2316 (23.16°C) at the same timestamp, despite the kitchen being heated by the stove (activated at 18:31). A functional sensor should have read higher than the unheated living room during active cooking.

The magnitude of deviation is relatively small (0.1-0.5°C), which might fall within normal tolerance for different room volumes unless strict precision is required.

The most severe issue (the `None` value) is better explained by a hard failure (Hypothesis A1) than simple drift.

The transition of `kitchen_temp_sensor` from a numeric value to `None` at 18:32:00 immediately after `kitchen_cook_surface` activation is the strongest evidence of a hard failure.

The concurrent `HardwareFaultAlert` on the kitchen smoke alarm at 18:05:00 provides context that the kitchen environment experienced a critical event likely causing the subsequent sensor failure.

The lack of temperature rise in the kitchen sensor during the active cooking period (18:31-18:38), while the living room continues to warm, contradicts the expected physical behavior of a working sensor.

The specific error code or reason string associated with the `HardwareFault()` event on the smoke alarm to determine if it affected the power bus for the temperature sensor.

Historical logs from the minute prior to 18:32:00 to see if the temperature sensor was already reporting anomalous values or missed packets before dropping to `None`.

Power supply status or voltage readings for the kitchen circuit during the 18:32:00 event.

Verify if the 'HardwareFaultAlert' at 18:05:00 in C16 is isolated to the smoke alarm or if other kitchen devices (like the temp sensor) were logging errors simultaneously.

Check data continuity immediately before 18:32:00 in C16 to confirm if the drop to 'None' was instantaneous or preceded by signal degradation.

Cross-reference power events or circuit status logs around 18:32:00 in adjacent chunks (C15/C17) to rule out a total kitchen circuit outage.

The analysis correctly identified the transition from valid data to 'None' as a critical failure indicator (A1). However, the current evidence relies heavily on a single chunk (C16) for the failure event and lacks context from the immediate preceding (C15) and succeeding (C17) minutes.

We need C15 to establish the baseline stability of the sensor right before the stove activation and fault alert to rule out pre-existing issues. We need C17 to see if the sensor recovers after a potential reboot or if the failure persists.

The correlation between the smoke alarm fault and the temperature sensor failure needs verification via C15/C17 to determine if they share a common cause (e.g., shared power bus) or if they are independent incidents.

## Query
请检查以下设备状态历史，判断 kitchen 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。

## 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": 516,
    "second_bedroom": 336,
    "kitchen": 306,
    "bathroom": 48,
    "entrance": 230
  },
  "attribute_frequency": {
    "MeasuredValue": 1156,
    "Occupancy": 644,
    "OnOff": 15,
    "StateValue": 7,
    "LockState": 5,
    "SystemMode": 1,
    "HardwareFaultAlert": 1,
    "ExpressedState": 1,
    "OperationalState": 1,
    "CurrentPositionLiftPercent100ths": 1
  },
  "lock_state_flips": 5,
  "occupancy_events": 644,
  "temperature_patterns": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-08T00:00:00",
    "end_ts": "2026-06-08T01:20:00",
    "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": [
      "[2026-06-08T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2268",
      "[2026-06-08T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2269",
      "[2026-06-08T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2270",
      "[2026-06-08T00:00:00] kitchen_temp_sensor | TemperatureM

## Query
请检查以下设备状态历史，判断 kitchen 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。

## Triage
{
  "latent_task_profile": "device-health",
  "focus_rooms": ["kitchen"],
  "focus_devices": ["kitchen_temp_sensor", "kitchen_smoke_co_alarm", "kitchen_contact_sensor"],
  "focus_chunk_ids": ["C00", "C01", "C16"],
  "suspected_patterns": [
    "Temperature measurement drift (values starting at ~22.7°C rising to >25°C without corresponding HVAC activation)",
    "Potential sensor calibration error or battery depletion causing false high readings",
    "Lack of correlation between temperature spikes and appliance usage (dishwasher/cook_surface) events"
  ],
  "why_these_chunks": [
    "C00/C01: Initial baseline establishment showing a consistent upward trend in kitchen temperature relative to other rooms, suggesting early-stage sensor drift.",
    "C16: Contains non-temperature events for the kitchen area (Dishwasher state changes), allowing cross-validation to see if temperature spikes correlate with actual heat generation from appliances."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The kitchen temperature sensor is experiencing a delayed thermal response due to high ambient room temperature (approx. 23°C baseline) rather than a hardware fault, as it tracks the general house warming trend.",
      "evidence": ["In chunks C00 and C01, all sensors show values in the 2268-2359 range (scaled x10), indicating a consistent baseline of ~22.7°C - 23.6°C across the entire house.", "The kitchen sensor readings generally follow the trend of other rooms, albeit with slight lag or noise, suggesting environmental factors like external heat or HVAC inefficiency are affecting all zones uniformly."],
      "weaknesses": ["This hypothesis fails to explain the specific 'HardwareFaultAlert' generated by the smoke alarm at 18:05:00 in chunk C16.", "It cannot account for the sudden drop to `None` at 18:32:00 immediately after the stove was activated, which indicates a complete data loss event typical of sensor failure or power cycle, not just slow thermal response."]
    }
  ],
  "anomaly_hypotheses": [
    {
      "id": "A1",
      "description": "The kitchen temperature sensor suffered a hardware failure or communication drop during active cooking usage, indicated by a fault alert and subsequent null reading.",
      "threat_type": "Sensor Hardware Failure / Data Integrity Loss",
      "evidence": ["At 18:05:00, the `kitchen_smoke_alarm` explicitly rep


FG-03-FP: 烟雾报警器自检触发CO检测

Sustained multi-room temperature rise and sensor failure indicate a significant uncontrolled thermal event or appliance malfunction, posing an immediate fire hazard.

Explanation: Multiple room sensors (kitchen, living room, bedroom) recorded abnormally high values (~2400-2500, likely scaled Celsius indicating 24-25°C+) for over 4 hours without active heating systems, suggesting a genuine environmental anomaly rather than a localized sensor error.

Explanation: The kitchen temperature sensor failed ('None') multiple times during the peak heat period, which correlates with the activation of the cook surface, implying physical damage or disconnection due to excessive heat or smoke exposure.

Explanation: A door lock operation occurred at T07:04 while temperatures were critically high, followed by a smoke alarm self-test at T07:13, strongly suggesting occupant concern regarding a fire or toxic buildup.

Continuous temperature readings across three rooms rising from ~23°C equivalent to >25°C equivalent between T03:25 and T08:20.

Kitchen sensor returning 'None' at T06:02:05 and T06:37:00 coinciding with highest temperatures and cook surface usage.

Manual front door lock operation at T07:04:02 immediately preceding the smoke alarm test event.

Dispatch emergency services/fire department to verify on-site conditions immediately.

Contact the resident to confirm safety status and evacuate if necessary.

Inspect kitchen appliances and HVAC systems for faults once scene is secure.

Even if the values are invalid, the pattern of *other* sensors (living room, bedroom) also rising from ~22°C to ~25°C over 4 hours suggests a real environmental change, not just a kitchen-specific sensor bug.

The correlation between the start of the 'high' values and human activity (cooking surface turned ON at T06:01) makes it plausible that the sensor malfunctioned specifically due to heat proximity, masking a real hazard.

Uncontrolled thermal event (Fire/Overheating) in the Kitchen with potential sensor degradation due to extreme heat.

Sustained temperature rise across multiple rooms (Kitchen, Living Room, Bedroom) from ~22°C to >25°C between T03:25 and T07:15, despite no active heating system being reported ON until T06:01.

Cooking surface was activated at T06:01 ('OnOff = True') while occupants were present.

Smoke alarm entered self-test mode at T07:13 immediately following the peak temperature period, suggesting a pre-existing sensitivity issue or a reaction to low-level combustion products.

Sensor failure ('None' returned) correlates temporally with the highest temperatures and appliance usage, indicating possible sensor melting or disconnection due to excessive heat.

Door lock operations at T07:04 coincide with occupancy changes, possibly indicating an attempt to leave or enter due to discomfort/emergency.

Occupancy data shows people moving around freely (lights on, windows opened), which might argue against a life-threatening fire at that exact moment, though they could be unaware of the severity.

The final reading in C16 shows temperatures returning to normal ranges (~23°C), which could imply the initial spike was transient or the sensor finally recovered after cooling down.

Systematic Data Interpretation Error: The raw data units are non-standard (likely millikelvin or internal integer encoding), causing the visualization/model to misinterpret ~23.00 as 2300.

All temperature sensors report values consistently shifted by a factor of 100 or more compared to standard residential norms (e.g., 2300 vs 23°C).

The values stabilize and behave logically once interpreted as a scaled unit (2300 -> 23.00), showing a gradual decline in C16 consistent with natural cooling or AC usage.

No other safety signals (smoke detection, door alarms) were triggered by this specific numerical anomaly alone; the smoke alarm only ran a test later.

If the data is indeed scaled, the living room and bedroom also rose to ~25°C (2500), which is still abnormally hot for a summer night (June 23rd) in a residential setting without air conditioning, suggesting a genuine thermal event regardless of unit scaling.

The sudden appearance of 'None' values alongside these high numbers strongly suggests a hardware fault triggered by actual heat, not just a software unit conversion error.

The temporal sequence: Cooking surface turns ON at T06:01, followed by a rapid climb in all room temperatures, then sensor failure ('None'), followed by a smoke alarm self-test at T07:13.

The multi-room correlation: The temperature rise is not isolated to the kitchen; the living room and bedroom also increased significantly, ruling out a localized sensor glitch in the kitchen only.

The explicit sensor failure ('None') occurring at the peak of the temperature event indicates physical stress on the sensor, corroborating the presence of extreme heat beyond normal operating parameters.

Actual unit of measurement for 'MeasuredValue' (Is it Kelvin? Millidegrees? Or just a typo in the log?).

Status of the HVAC/Air Conditioning system (Was it off, broken, or set incorrectly?).

Historical baseline for 'TestInProgress' events on the smoke alarm (Is T07:13 a routine daily check or an emergency trigger?).

Video feed or audio logs from the time period T06:00-T07:00 to confirm occupant behavior and auditory cues.

Verify HVAC system status and logs during the temperature spike.

Determine if the smoke alarm 'TestInProgress' at T07:13 was a routine daily check or an emergency trigger.

Review video/audio feeds from C05-C06 range to confirm occupant behavior and auditory cues (smoke/heat sounds).

Check historical baseline for sensor data formatting to rule out systematic unit encoding errors.

The analysis correctly identified the multi-room temperature correlation and sensor failure patterns as critical indicators of a potential thermal event.

However, the evidence is currently insufficient to definitively classify the threat level because it relies heavily on inferred states (e.g., assuming the smoke alarm test implies a hazard) without verifying the actual source of that signal.

Chunks C05 and C17 are needed to cover the immediate aftermath of the peak temperature to see if conditions stabilized or worsened, and C20 may contain the specific HVAC configuration logs required to rule out mechanical failure as the sole cause.

The hypothesis regarding data unit scaling (A2) remains a strong contender; checking raw log formats in missing chunks is essential before escalating to emergency protocols.

## Query
以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。

## 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": 495,
    "bedroom": 529,
    "kitchen": 538,
    "bathroom": 63,
    "entrance": 230
  },
  "attribute_frequency": {
    "Occupancy": 942,
    "MeasuredValue": 870,
    "OnOff": 21,
    "CurrentPositionLiftPercent100ths": 4,
    "LockState": 4,
    "StateValue": 4,
    "TestInProgress": 2,
    "COState": 2,
    "CurrentLevel": 1
  },
  "lock_state_flips": 4,
  "occupancy_events": 942,
  "temperature_patterns": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-23T00:00:00",
    "end_ts": "2026-06-23T01:35:00",
    "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": [
      "[2026-06-23T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2272",
      "[2026-06-23T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2172",
      "[2026-06-23T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2261",
      "[2026-06-23T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-23T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-23T00:00:00] kitchen_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-23T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-23T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0",

## Query
以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。

## Triage
{
  "latent_task_profile": "composite-safety",
  "focus_rooms": ["kitchen", "living_room"],
  "focus_devices": [
    "kitchen_temp_sensor",
    "living_room_temp_sensor",
    "bedroom_temp_sensor",
    "kitchen_occupancy",
    "entrance_occupancy"
  ],
  "focus_chunk_ids": ["C02", "C03", "C04", "C16"],
  "suspected_patterns": [
    "sustained_abnormal_temperature_rise",
    "persistent_high_temperatures_despite_no_recent_activity_change",
    "temperature_sensor_data_format_anomaly"
  ],
  "why_these_chunks": [
    "C02-C04 show a continuous and steep rise in temperature readings across multiple rooms (from ~22°C to >25°C), which is abnormal for a residential environment without an active heating system.",
    "C16 contains critical data anomalies: 'kitchen_temp_sensor' returns 'None', suggesting sensor failure or disconnection, while other sensors still report high temperatures. Additionally, the cook surface turned off ('OnOff.OnOff = False') while occupancy remains high, raising questions about whether the heat source was recently extinguished or if the temperature spike occurred before shutdown.",
    "The combination of persistently high temperatures, fluctuating sensor states, and the specific context of an elderly person living alone suggests a potential fire hazard, malfunctioning appliance, or environmental control failure requiring immediate verification."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The system experienced a prolonged period of sensor failure in the kitchen, leading to erroneous high temperature readings (e.g., 2300-2500) which were actually invalid data points rather than physical heat.",
      "evidence": ["C02-C04 show 'TemperatureMeasurement.MeasuredValue' in the range of 2300-2500, which is physically impossible for Celsius and likely represents an overflow or calibration error code.", "At C03/T06:02:05 and C04/T06:37:00, the sensor explicitly returns 'None', confirming intermittent hardware or communication failure during the high-value period.", "When the sensor resumes reporting at C16 (T17:27), values drop to realistic ranges (~2300-2350, assuming a decimal shift or different unit scale initially, but stabilizing to ~23°C by T18:20)."],
      "weaknesses": ["Even if the values are invalid, the pattern of *other* sensors (living room, bedroom) also rising from ~22°C to ~25°C over 4 hours suggests a real environmental chan


WD-03-FP: 住户外出但开了自动浇花系统

漏水传感器触发后在短时间内（3分钟）恢复为false，而非持续触发超过10分钟

A sustained, linear temperature rise across all monitored rooms over several hours indicates a critical HVAC failure or system malfunction, creating an imminent fire and health hazard.

Explanation: The data shows a continuous, unexplained increase in ambient temperature from approximately 23°C to over 25°C (50°C+ on raw scale) across every room simultaneously, which is inconsistent with normal passive heating or external weather patterns that would show variance.

Explanation: Despite multiple occupancy events where residents entered the house and turned on lights/appliances, there were no 'OnOff' commands for the Air Conditioner or Thermostat, nor any indication of cooling activity, suggesting the system has failed to activate or respond.

Explanation: The kitchen sensor eventually returned 'None' at 07:01:10 immediately after a cooking surface was activated, likely due to sensor saturation from extreme heat, confirming dangerous overheating conditions.

Explanation: The uniformity and linearity of the temperature spike across disconnected zones strongly point to a central mechanical failure (e.g., compressor lockout, fan failure, or power loss) rather than localized issues.

Temperature readings rose steadily from ~23°C to >25°C over a 6-hour period in Living Room, Kitchen, Master Bedroom, and Kids Room simultaneously.

No thermostat commands or cooling cycles were logged during the entire event, despite the temperature exceeding typical comfort thresholds.

Kitchen sensor data dropped to 'None' upon activation of the cooktop, indicating potential sensor burnout due to excessive ambient heat.

Occupancy logs confirm the house was occupied towards the end, yet temperatures continued to climb rapidly without intervention.

Immediately dispatch emergency services or contact a technician to inspect the HVAC/cooling system.

Evacuate the premises if smoke alarms trigger or if temperatures continue to rise uncontrollably.

Do not attempt to manually reset the HVAC unit until a professional has identified the cause of the failure.

Check external weather conditions to rule out extreme ambient heat, though internal uniformity suggests mechanical failure.

The rate of increase is linear and continuous over 6 hours without any plateau, which is atypical for passive heat gain where equilibrium should eventually be reached or slowed by thermal mass. Normal diurnal swings rarely cause such a sustained, steep gradient in an enclosed space without active heating.

The uniformity of the rise across all rooms simultaneously suggests a common failure point (like total HVAC loss) rather than just outside weather, especially given the magnitude of the rise (~2.5°C per hour average).

Total HVAC/Cooling System Failure leading to progressive overheating and potential structural/fire hazard.

Sustained, linear temperature increase across ALL monitored rooms (Living, Kitchen, Bedrooms) from ~23°C to >25°C over a 6-hour period despite zero occupancy.

Kitchen sensor specifically shows erratic spikes near the end (2500+ -> None), possibly indicating sensor saturation or proximity to a failing appliance/heater.

Occupancy events (people entering rooms at 06:03) do not interrupt the heating trend; temperatures continue to climb rapidly even as humans enter, indicating no human intervention (like turning on AC) has occurred.

Correlation between rising ambient temp and lack of cooling response.

Could be a sensor calibration error affecting all nodes simultaneously (less likely if they are distinct physical devices).

External factors like direct sunlight through windows could theoretically drive temps up, but usually with more variance and lag.

Even with sun exposure, raising every room uniformly by nearly 3°C in 6 hours without any fluctuation is highly improbable without a mechanical failure of the cooling system.

Undetected electrical fault or short circuit in the HVAC unit causing it to generate excessive heat instead of cooling.

Rapid acceleration of temperature rise in later chunks (C04-C05) coinciding with occupant activity might indicate they noticed the heat and checked systems, but temps kept rising.

Kitchen temperature data drops to 'None' at 07:01:10, potentially indicating a sensor burnout or extreme heat distortion.

No other electrical anomalies (trips, lights flickering) are explicitly logged in the provided chunks besides normal light switches.

The pattern looks more like passive accumulation than sudden ignition.

Lack of explicit 'Power Fault' or 'Circuit Breaker Trip' signals in the structured data.

Linear, unceasing temperature ascent across the entire house (23°C -> 25°C+) over 6 hours with zero occupancy intervening.

Simultaneous rise in Kitchen and Bedroom sensors indicates a central system failure rather than localized cooking or appliance use.

Absence of any 'OnOff' commands for the Air Conditioner or Thermostat in the logs during this period.

HVAC/Thermostat state logs (Was the system set to 'Cool'? Did it report 'Error'?).

External weather data (Outdoor temperature and humidity).

Smoke detector status/readings (Are they currently armed or silent?).

History of the last successful cooling cycle.

HVAC/Thermostat state logs (Cool mode active? Error codes?)

External weather data (Outdoor temp/humidity)

The investigation is currently on-topic and correctly identifies the core anomaly: a sustained, uniform temperature rise across all rooms despite zero occupancy, pointing towards HVAC failure rather than external weather or localized events.

However, the evidence is insufficient to confirm a 'safety threat' vs. a 'benign environmental event' with high confidence. The current chunk set (C01-C28) only covers sensor readings and basic occupancy/lighting; it lacks critical system state data.

Specifically, we need to verify if the AC was actually commanded to run and why it failed (logs for C01-C28 should include thermostat commands or error states). Without this, we cannot rule out that the system was never turned on or had a silent electrical fault not captured by generic 'light switch' logs.

Additionally, external weather data is missing from the provided chunks, making it impossible to distinguish between a total power loss to the AC unit versus an unusually hot day causing passive heating (though the linear rate suggests failure).

## Query
以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。

## 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": 399,
    "master_bedroom": 520,
    "kids_room": 519,
    "kitchen": 303,
    "dining_room": 217,
    "second_bedroom": 48,
    "master_bathroom": 54,
    "entrance": 229,
    "second_bathroom": 3
  },
  "attribute_frequency": {
    "MeasuredValue": 1156,
    "Occupancy": 1086,
    "OnOff": 26,
    "StateValue": 9,
    "LockState": 5,
    "CurrentPositionLiftPercent100ths": 3,
    "SystemMode": 1,
    "OperationalState": 1
  },
  "lock_state_flips": 5,
  "occupancy_events": 1086,
  "temperature_patterns": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-05T00:00:00",
    "end_ts": "2026-06-05T01:10:00",
    "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",
      "dining_roo

## Query
以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。

## Triage
{
  "latent_task_profile": "single-event-safety | composite-safety",
  "focus_rooms": [
    "kitchen",
    "living_room",
    "master_bedroom",
    "kids_room"
  ],
  "focus_devices": [
    "kitchen_temp_sensor",
    "living_room_temp_sensor",
    "master_bedroom_temp_sensor",
    "kids_room_temp_sensor",
    "smoke_co_alarm",
    "air_conditioner"
  ],
  "focus_chunk_ids": [
    "C01",
    "C02",
    "C03",
    "C04",
    "C05",
    "C06",
    "C07",
    "C08",
    "C09",
    "C10",
    "C11",
    "C12",
    "C13",
    "C14",
    "C15",
    "C16",
    "C17",
    "C18",
    "C19",
    "C20",
    "C21",
    "C22",
    "C23",
    "C24",
    "C25",
    "C26",
    "C27",
    "C28"
  ],
  "suspected_patterns": [
    "Continuous temperature spike across all living spaces (approx. 23°C -> 25.6°C) over ~12 hours despite no occupancy change in some rooms.",
    "Correlation between rising ambient temperature and potential HVAC failure or malfunction.",
    "Risk of fire hazard due to overheating kitchen appliances or electrical systems if AC fails."
  ],
  "why_these_chunks": [
    "All chunks from C01 to C28 show a progressive, linear increase in temperature readings for sensors in the kitchen, living room, master bedroom, and kids room.",
    "The initial chunks (C00-C01) establish the baseline (~22-23°C). Subsequent chunks reveal the anomaly where temperatures climb steadily to exceed 25°C.",
    "This pattern indicates a latent safety threat (potential heating system failure or lack of cooling) that requires immediate verification against smoke alarms and appliance states, rather than just analyzing discrete events like door locks or lights."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The house is unoccupied and experiencing a gradual, benign temperature rise due to external ambient conditions (e.g., hot day) or delayed HVAC wake-up cycles after being off overnight.",
      "evidence": ["All rooms show occupancy = 0 from 01:30 until 06:03.", "Temperature readings are consistent across multiple sensors in different zones, suggesting a systemic environmental factor rather than localized heating.", "No fire alarms or smoke detectors have triggered yet."],
      "weaknesses": ["The rate of increase is linear and continuous over 6 hours without any plateau, which is atypical for passive heat gain where equilibrium should eventually be reached or slowed by thermal


SmokeCoAlarm 的 COState 变为 Warning 或 Critical

CO 报警是严重安全事件，不同于烟雾报警

紧急通知所有住户撤离，开窗通风，联系燃气公司

The system indicates a high probability of an unattended kitchen fire or gas leak due to a sustained temperature rise and CO alarm trigger while the house was empty.

Explanation: Pre-incident analysis (C01) establishes a stable baseline where the kitchen temperature (~2320°C equivalent in data units) was consistently lower than the living room (~2330-2350), making the subsequent rapid and sustained heating anomaly statistically significant.

Explanation: At 03:24:00, the CO alarm triggered ('COState = 1') concurrently with the kitchen temperature exceeding the living room temperature for the first time since monitoring began, indicating localized heat generation rather than ambient warming.

Explanation: Post-trigger data (C02-C03) shows the kitchen temperature continuing to climb steadily (reaching ~2490 by 06:10) while other rooms remain relatively stable, and no human occupancy was detected until over two hours later when cooking appliances were manually turned on, suggesting the threat occurred without intervention.

Explanation: The combination of a specific safety device trigger (CO Alarm) and divergent thermal behavior in an unoccupied space rules out simple sensor drift and points to a physical hazard like combustion or gas ignition.

Event 'COAlarm()' triggered at 2026-06-04T03:24:00 in the kitchen.

Kitchen temperature rose from 2320 to 2490 while living room remained near 2470, despite zero occupancy across all sensors during the incident window.

No manual override, reset, or siren activation logs were found between the alarm trigger and the arrival of occupants.

Immediately dispatch emergency services to investigate the kitchen for fire or hazardous gas presence.

Do not enter the scene until professionals have cleared it; assume the CO alarm and heat source are active.

```json
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "False Positive CO Alarm due to environmental interference or sensor malfunction, with subsequent high temperatures caused by an external heat source (e.g., open window near a hot HVAC unit, sunlight exposure, or a nearby appliance running at full capacity).",
      "evidence": ["All occupancy sensors report '0' immediately after the alarm, suggesting no one was present to manually trigger it or investigate.", "Temperatures are elevated (~24°C) but not extreme for a room-sized space over 2.5 hours, which might indicate gradual heating rather than rapid fire combustion."],
      "weaknesses": ["The temperature in the kitchen is consistently higher than other rooms and shows a slight upward trend, which contradicts typical passive cooling from an open window.", "A standard false positive usually triggers a reset or silence within minutes; here, the system continues logging without user intervention."]
    }
  ],
  "anomaly_hypotheses": [
    {
      "id": "A1",
      "description": "Early-stage residential fire or gas leak ignition in the kitchen.",
      "threat_type": "Fire / Hazardous Gas Leak",
      "evidence": [
      "Definitive Trigger: 'Event: COAlarm()' at 03:24:00 indicates the presence of carbon monoxide or smoke.",
      "Anomalous Thermal Gradient: The kitchen temperature (2370 -> 2438K/°C scale relative to baseline, effectively rising ~68 degrees over time) remains significantly higher than bedroom/living room temperatures.",
      "Sustained Heat Rise: Unlike normal fluctuations, the kitchen temperature shows a consistent monotonic increase throughout the monitoring window, while other rooms remain stable.",
      "Occupancy Context: The house appears empty ('Occupancy = 0') during the incident, meaning the threat is unmitigated and unaddressed by humans."
    ]
  ],
  "most_discriminative_evidence": [
    "The concurrent occurrence of a specific 'COAlarm()' event followed by a sustained, localized temperature rise exclusively in the kitchen, despite all rooms being reported as unoccupied."
  ],
  "missing_information": [
    "Pre-incident baseline temperatures for the kitchen to calculate the exact rate of rise.",
    "Status of any manual override buttons or siren activation logs.",
    "Outdoor weather conditions (temperature/humidity) to rule out external environmental influence."
  ]
}
```

Verify pre-incident baseline temperatures in C01 to calculate rate of rise accurately.

Check C03 for any subsequent alarm resets, sirens activation, or external sensor data (weather/outside temperature) to rule out environmental interference.

The investigation correctly identifies the core threat indicators (CO Alarm + Temp Rise) in C02 and formulates valid hypotheses.

However, the evidence is currently insufficient because it relies heavily on a single chunk (C02).

To validate the 'Anomaly' hypothesis vs. the 'False Positive' hypothesis, we need context from adjacent time windows: C01 should establish the pre-incident thermal baseline to confirm if the rise is anomalous or part of a trend, and C03 should check for system responses (sirens/reset) or outdoor conditions that might explain the readings.

Without establishing the baseline (C01) and checking immediate follow-up events/environmental context (C03), the rate-of-rise calculation and exclusion of external factors remain speculative.

## Query
以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。

## 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": 529,
    "kitchen": 537,
    "bathroom": 63,
    "entrance": 230
  },
  "attribute_frequency": {
    "Occupancy": 944,
    "MeasuredValue": 870,
    "OnOff": 21,
    "CurrentPositionLiftPercent100ths": 4,
    "LockState": 4,
    "StateValue": 4,
    "COState": 1,
    "ExpressedState": 1,
    "CurrentLevel": 1
  },
  "lock_state_flips": 4,
  "occupancy_events": 944,
  "temperature_patterns": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-04T00:00:00",
    "end_ts": "2026-06-04T01:35:00",
    "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": [
      "[2026-06-04T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2277",
      "[2026-06-04T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2174",
      "[2026-06-04T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2261",
      "[2026-06-04T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-04T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-04T00:00:00] kitchen_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-04T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-04T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0",

## Query
以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。

## Triage
{
  "latent_task_profile": "single-event-safety",
  "focus_rooms": ["kitchen"],
  "focus_devices": ["kitchen_smoke_co_alarm", "kitchen_temp_sensor", "kitchen_occupancy"],
  "focus_chunk_ids": ["C02"],
  "suspected_patterns": [
    "COAlarm event triggered at 03:24:00 indicating potential smoke or carbon monoxide presence",
    "Rapid temperature rise in kitchen (2320 -> 2370 -> 2390) concurrent with alarm"
  ],
  "why_these_chunks": [
    "Chunk C02 contains the critical 'Event: COAlarm()' from the kitchen smoke detector, which is a definitive safety threat indicator.",
    "The temperature readings in C02 show an anomalous spike pattern consistent with a fire or gas leak incident starting around this time."
  ]
}

## Investigator
```json
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "False Positive CO Alarm due to environmental interference or sensor malfunction, with subsequent high temperatures caused by an external heat source (e.g., open window near a hot HVAC unit, sunlight exposure, or a nearby appliance running at full capacity).",
      "evidence": ["All occupancy sensors report '0' immediately after the alarm, suggesting no one was present to manually trigger it or investigate.", "Temperatures are elevated (~24°C) but not extreme for a room-sized space over 2.5 hours, which might indicate gradual heating rather than rapid fire combustion."],
      "weaknesses": ["The temperature in the kitchen is consistently higher than other rooms and shows a slight upward trend, which contradicts typical passive cooling from an open window.", "A standard false positive usually triggers a reset or silence within minutes; here, the system continues logging without user intervention."]
    }
  ],
  "anomaly_hypotheses": [
    {
      "id": "A1",
      "description": "Early-stage residential fire or gas leak ignition in the kitchen.",
      "threat_type": "Fire / Hazardous Gas Leak",
      "evidence": [
      "Definitive Trigger: 'Event: COAlarm()' at 03:24:00 indicates the presence of carbon monoxide or smoke.",
      "Anomalous Thermal Gradient: The kitchen temperature (2370 -> 2438K/°C scale relative to baseline, effectively rising ~68 degrees over time) remains significantly higher than bedroom/living room temperatures.",
      "Sustained Heat Rise: Unlike normal fluctuations, the kitchen temperature shows a consistent monotonic increase throughout the monitoring window, while other r


漏水传感器持续触发超过10分钟
全屋无人（所有 occupancy = 0，门锁为 Locked）
无人处理导致损失持续扩大

紧急通知住户，如有智能水阀立即关闭

The kitchen temperature sensor exhibits physically impossible readings (>2800) and subsequent failure ('None') immediately following cook surface activation, strongly indicating a thermal event (fire or equipment malfunction) that may have been masked by sensor burnout.

Explanation: Temporal correlation: The cook surface turned ON at 11:52:30, and exactly 30 seconds later the temperature sensor returned 'None' while reporting impossible values (>2800) just prior. This precise timing suggests the sensor failed due to extreme heat generated by the appliance.

Explanation: Magnitude anomaly: Indoor ambient temperatures never exceed 100°C (~347°F). Readings of 2887 units are physically implausible for normal operation and indicate sensor saturation or destruction from a fire or electrical arc.

Explanation: Asymmetric recovery: The temperature gradually normalized over an hour after the initial spike, consistent with the cooling down of a hot object or room after a thermal event ceased, rather than a simple software glitch.

[2026-06-14T11:52:30] kitchen_cook_surface | OnOff.OnOff = True

[2026-06-14T11:53:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = None

[2026-06-14T11:45:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2887

Immediately inspect the kitchen area for signs of smoke, soot, or damaged appliances.

Replace the kitchen temperature sensor as it appears to be permanently compromised.

Check smoke detector and CO alarm logs for this time window to confirm if they were triggered but missed, or if they also failed.

{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "Sensor calibration drift or temporary communication glitch causing transient high readings and null values.",
      "evidence": ["kitchen_temp_sensor returned 'None' at 09:32:00 after normal operation in C07; similar 'None' at 12:50:00 after cooking ended in C09; other room sensors remained stable (~2500 units) during these events, suggesting a localized kitchen sensor issue rather than a systemic failure.", "High values in C09 (2887 -> 2502 over ~1 hour) show a gradual normalization consistent with sensor recovery or environmental cooling after an event."],
      "weaknesses": ["Does not explain the specific temporal correlation between the cook surface activation and the first 'None' reading in C09 (11:53:00). Normal glitches do not consistently coincide with appliance state changes. The magnitude of the spike (>2800) is physically impossible for ambient temperature, indicating a fault mechanism beyond simple drift."}
    ]
  ],
  "anomaly_hypotheses": [
    {
      "id": "A1",
      "description": "Hidden fire hazard or uncontrolled heating event in the kitchen masked by sensor failure.",
      "threat_type": "Fire Hazard / Equipment Failure",
      "evidence": ["In C09, at 11:52:30 the cook surface turned ON. Exactly 30 seconds later (11:53:00), the sensor reported 'None', coinciding with the onset of impossible high values (2887 at 11:45, dropping to 2808 at 11:55). This suggests the sensor was overwhelmed or disconnected due to extreme heat/fire.", "The pattern of impossible values (2800+) followed by a gradual decline back to normal (2500s) indicates a thermal event that ceased or was mitigated, leaving a cooling residue.", "In C07, a window opened while the cook surface was active (or vice versa contextually), potentially exacerbating smoke spread if a fire occurred, though no direct fire signal is present yet."],
      "weaknesses": ["No direct confirmation of flame, smoke detection, or CO alarms triggered in the logs provided.", "Occupancy data shows residents were away (Living Room occupancy 0-1, Bedrooms 0) during the peak anomaly period in C09 (11:45-12:00), which may have delayed discovery but does not confirm the cause."]
    }
  ],
  "most_discriminative_evidence": [
    "Temporal coincidence: In Chunk C09, the kitchen cook surface activates at 11:52:30, and exactly 30 seconds later, the temperature sensor fails ('None') while reporting impossible values (>2800) immediately prior and during the failure. Normal sensor noise does not correlate perfectly with appliance state changes.",
    "Magnitude anomaly: Readings exceeding 2800 units are physically implausible for indoor ambient temperature, strongly indicating a sensor burnout from extreme heat (fire) or electrical arcing rather than software error.",
    "Asymmetric recovery: The return to normal values (~2500) occurs gradually after the initial spike, consistent with cooling down from a thermal event, whereas a simple power cycle would likely reset the sensor differently or immediately."
  ],
  "missing_information": [
    "Logs from Smoke Detectors and Carbon Monoxide (CO) sensors for the kitchen.",
    "Video feed or motion sensor data specifically inside the kitchen during the 11:45–12:00 window to verify if a person was interacting with the stove or if an explosion/fire occurred.",
    "Power grid logs to check for simultaneous voltage spikes or circuit breaker trips associated with the cook surface activation."
  ]
}

Verify Smoke Detector and CO sensor logs for the kitchen during C09.

Check power grid logs for voltage spikes or circuit trips at 11:52:30.

Review video/motion data for the kitchen between 11:45-12:00.

Cross-reference Living Room/Bedroom occupancy logs to confirm if residents were truly away during the peak anomaly.

The analysis is on-topic and correctly identifies the core anomaly (sensor failure coinciding with cook surface activation and impossible temperature readings).

Evidence is currently insufficient to definitively classify this as a confirmed safety threat versus a hardware fault without corroborating data from other systems (smoke, CO, power).

The Investigator Output correctly lists specific missing checks; these should be prioritized immediately to rule in/out fire hazards.

No additional time-window chunks (C08, C10) appear strictly necessary beyond the ones already selected (C07, C09) for the initial hypothesis testing, but external system logs are required.

## Query
以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。

## 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": 481,
    "master_bedroom": 336,
    "second_bedroom": 336,
    "kitchen": 308,
    "bathroom": 57,
    "entrance": 51
  },
  "attribute_frequency": {
    "MeasuredValue": 1158,
    "Occupancy": 383,
    "OnOff": 16,
    "StateValue": 7,
    "SystemMode": 1,
    "CurrentPositionLiftPercent100ths": 1,
    "OperationalState": 1,
    "LockState": 1
  },
  "lock_state_flips": 1,
  "occupancy_events": 383,
  "temperature_patterns": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-14T00:00:00",
    "end_ts": "2026-06-14T01:20:00",
    "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": [
      "[2026-06-14T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2262",
      "[2026-06-14T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2268",
      "[2026-06-14T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2274",
      "[2026-06-14T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2272",
      "[2026-06-14T00:00:00] living_room_occ

## Query
以下是刚刚发生的事件。请判断这是否构成安全威胁，并说明理由。

## Triage
{
  "latent_task_profile": "single-event-safety | behavior-sequence",
  "focus_rooms": ["kitchen"],
  "focus_devices": ["kitchen_temp_sensor", "kitchen_cook_surface", "kitchen_window_contact", "kitchen_light"],
  "focus_chunk_ids": ["C07", "C09"],
  "suspected_patterns": [
    "Sensor data corruption (MeasuredValue = None) coinciding with appliance activation",
    "Unusually high temperature readings (>2800 units) suggesting sensor drift or fault before normalization",
    "Window state change (False/Open) detected while cooking surface is active"
  ],
  "why_these_chunks": "Chunk C09 contains a critical anomaly where the kitchen temperature sensor returns 'None' exactly when the cook surface turns on, preceded by impossible temperature values (~2887). This indicates a sensor failure that could mask a fire hazard. Chunk C07 shows the onset of these erratic high values and includes an open window event during cooking, which are key indicators for potential safety incidents requiring immediate investigation."
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "Sensor calibration drift or temporary communication glitch causing transient high readings and null values.",
      "evidence": ["kitchen_temp_sensor returned 'None' at 09:32:00 after normal operation in C07; similar 'None' at 12:50:00 after cooking ended in C09; other room sensors remained stable (~2500 units) during these events, suggesting a localized kitchen sensor issue rather than a systemic failure.", "High values in C09 (2887 -> 2502 over ~1 hour) show a gradual normalization consistent with sensor recovery or environmental cooling after an event."],
      "weaknesses": ["Does not explain the specific temporal correlation between the cook surface activation and the first 'None' reading in C09 (11:53:00). Normal glitches do not consistently coincide with appliance state changes. The magnitude of the spike (>2800) is physically impossible for ambient temperature, indicating a fault mechanism beyond simple drift."}
    ]
  ],
  "anomaly_hypotheses": [
    {
      "id": "A1",
      "description": "Hidden fire hazard or uncontrolled heating event in the kitchen masked by sensor failure.",
      "threat_type": "Fire Hazard / Equipment Failure",
      "evidence": ["In C09, at 11:52:30 the cook surface turned ON. Exactly 30 seconds later (11:53:00), the sensor reported 'None', coinciding with the onset of imposs