The living room occupancy sensor is functioning correctly; all rooms consistently reported zero occupancy during the monitored night hours (00:00 to 03:00), which aligns with expected low-activity periods.

Explanation: Comparative analysis shows that at timestamp 00:00, all other room occupancy sensors (kitchen, dining, bedrooms, bathroom, entrance) also reported a value of 0, establishing a consistent system-wide state of emptiness.

Explanation: The '14 events' mentioned in the stage-1 hypothesis likely refer to temperature updates or minor fluctuations from the living room temp sensor, not human motion, explaining the lack of occupancy triggers without implying sensor failure.

Explanation: When activity eventually occurred later in the day (e.g., kids_room and dining_room occupancy turning to 1 at 20:43), those sensors successfully detected it, confirming the sensor logic and network are operational.

[2026-06-12T00:00:00] ... dining_room_occupancy | OccupancySensing.Occupancy = 0

[2026-06-12T00:30:00] ... living_room_occupancy | OccupancySensing.Occupancy = 0

No immediate action required; continue routine monitoring.

If future logs show high event counts for lights/AC while occupancy remains 0 during active hours, investigate actuator vs. sensor correlation then.

[2026-06-12T07:10:37] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)

[2026-06-12T16:28:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)

[2026-06-12T17:57:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)

[2026-06-12T22:40:23] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)

[2026-06-12T06:10:11] kids_room_window | WindowCovering.CurrentPositionLiftPercent100ths = 0

[2026-06-12T07:10:27] front_door_lock | DoorLock.LockState = 2

[2026-06-12T07:10:37] front_door_lock | DoorLock.LockState = 1

No error logs or timeout signals explicitly mentioned for living_room_dimmable_light, living_room_onoff_light, living_room_temperature_sensor, living_room_smoke_co_alarm, living_room_air_conditioner, or window_covering sensors in the provided snippet.

The layout confirms standard device presence.

None directly contradict normalcy of other devices, but the anomaly in occupancy casts doubt on the holistic health of the room's sensing layer.

Timestamps of 'living_room' dimmable_light and air_conditioner state changes to determine if they were triggered by motion events that the occupancy sensor failed to record.

Raw signal strength (RSSI) or battery level of 'living_room_occupancy' to rule out hardware disconnection or low-power mode.

Comparison of 'living_room_occupancy' logs with 'entrance_occupancy' or 'dining_room_occupancy' during the same timeframe to check for regional interference or network partition issues affecting only the living room node.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

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

## 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>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 2298,
  "salient_event_count": 60,
  "focus_event_count": 89,
  "room_activity": {
    "kitchen": 7,
    "living_room": 14,
    "dining_room": 8,
    "master_bedroom": 11,
    "second_bedroom": 7,
    "kids_room": 12,
    "master_bathroom": 8,
    "entrance": 22
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-12T07:10:27] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-12T07:10:37] front_door_lock

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

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

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Living room occupancy sensor (sensor_id: living_room_occupancy) is likely malfunctioning due to persistent false-negative readings or data synchronization failure, indicated by the static '0' value at midnight despite non-zero activity counts.",
      "supported_by": ["Evidence shows 14 events recorded for 'living_room', but the specific sensor log '[2026-06-12T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0' suggests a lack of dynamic detection capability at that timestamp, potentially indicating the sensor failed to register movement occurring elsewhere in the same room (e.g., lights or motion events) or is stuck in an unresponsive state.", "Contrast with other rooms where occupancy sensors report '0' at midnight which aligns with expected low-activity periods, making the living room's lack of event diversity suspicious given its higher event count."],
      "contradicted_by": ["The 'room_activity' metric shows 14 events for living_room, suggesting some subsystems (possibly lights or climate) are active; however, if these occurred without triggering the motion sensor, it implies the sensor is blind rather than the room being empty. Without raw timestamps of light/AC changes relative to motion, we cannot definitively prove a person was present, but the discrepancy warrants investigation."]
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "All other living room devices appear operational based on available logs.",
      "supported_by": ["No error logs or timeout signals explicitly mentioned for living_room_dimmable_light, living_room_onoff_light, living_room_temperature_sensor, living_room_smoke_co_alarm, living_room_air_conditioner, or wind


The missing sensor data for the second bathroom is attributed to a configuration omission rather than hardware failure or malfunction.

Explanation: The raw log shows consistent telemetry (OccupancySensing events) for all other rooms in the house at regular intervals.

Explanation: However, no log entries exist for 'second_bathroom_occupancy' or any variant of that room name across the entire time window.

Explanation: This absence is identical to the behavior of sensors that are either not installed or explicitly excluded from the monitoring schema, rather than a sudden drop in signal from an active device.

Explanation: Given the stage-1 analysis noted the layout definition included a light but potentially omitted an explicit occupancy sensor tag, this indicates a design/configuration gap, not a runtime anomaly.

Absence of any MQTT/HTTP packet containing 'second_bathroom' tags in the provided raw log excerpt.

Presence of regular occupancy reports for all other monitored rooms (kitchen, living_room, master_bedroom, etc.) confirms the logging system itself is functional.

Verify the device registry to confirm if an occupancy sensor was ever provisioned for the second bathroom zone.

Review the smart-home automation rules to ensure the lighting control for the second bathroom does not rely on a missing presence feed.

[2026-06-21T00:00:00] dining_room_occupancy | OccupancySensing.Occupancy = 0

[2026-06-21T00:00:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 0

[2026-06-21T00:00:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0

[2026-06-21T00:00:00] kids_room_occupancy | OccupancySensing.Occupancy = 0

[2026-06-21T00:00:00] master_bathroom_occupancy | OccupancySensing.Occupancy = 0

[2026-06-21T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0

[2026-06-21T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0

Check raw MQTT/HTTP logs for any packet containing 'second_bathroom' or 'bath_2' tags within the time window.

Verify if the 'occupancy_sensor' device ID associated with second_bathroom exists in the device registry and check its last heartbeat status.

Inspect network connectivity logs for the gateway serving the second bathroom zone to rule out network isolation.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

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

## 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>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1488,
  "salient_event_count": 60,
  "focus_event_count": 78,
  "room_activity": {
    "kitchen": 9,
    "living_room": 17,
    "dining_room": 9,
    "master_bedroom": 9,
    "second_bedroom": 9,
    "kids_room": 9,
    "master_bathroom": 8,
    "entrance": 8
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-21T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-21T00:00:00] dining_room_occupancy | OccupancySensing.Oc

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

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

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Second bathroom occupancy sensor is missing or non-functional.",
      "supported_by": ["The 'room_activity' statistics show zero activity recorded for 'second_bathroom', while other rooms (kitchen, living_room, master_bedroom, etc.) have recorded events (8-17). This suggests the system failed to detect or log any state changes in that room.", "The 'suspicious_signals' list includes occupancy data for all expected rooms except second_bathroom. The absence of any occupancy signal (OccupancySensing.Occupancy = 0 or 1) for this specific room indicates a complete lack of telemetry from its motion sensor."],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "The room is completely empty and unmonitored due to configuration error rather than hardware failure.",
      "supported_by": [],
      "contradicted_by": ["Standard smart-home layouts typically include occupancy sensors in bathrooms to trigger lighting or ventilation; the layout definition lists '次卫灯<onoff_light>' but no explicit occupancy sensor in the provided text, which might imply it's controlled by presence elsewhere or simply omitted. However, given H1's strength regarding missing logs compared to active rooms, total emptiness without sensor data is statistically unlikely if the device was installed."]
    }
  ],
  "most_concerning_signals": [
    "Absence of any entry in 'room_activity' for 'second_bathroom'.",
    "Absence of any 'occupancy_sensor' event in 'suspicious_signals' specifically for second_bathroom, whereas every other room has timestamped null readings."
  ],
  "what_to_verify_in_raw_log": [
    "Check raw MQTT/HTTP logs for any packet containing 'second_b


The bedroom window covering sensor is reporting an impossible value (10000) which exceeds the valid range (0-10000), indicating a firmware bug or signal corruption rather than a physical state change.

Explanation: Valid sensor data for lift percentage should be between 0 and 10000 (representing 0% to 100%).

Explanation: The log shows two instances where the value is exactly '10000', which is physically impossible for a standard position sensor.

Explanation: This specific error value appears consistently at different times without any accompanying motor command logs or logical transitions, suggesting a data transmission or parsing failure.

Reset the bedroom window covering motor/sensor unit to clear the corrupted state.

Check for firmware updates or calibration errors for the bedroom window cover device.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

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

## 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>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1850,
  "salient_event_count": 60,
  "focus_event_count": 95,
  "room_activity": {
    "kitchen": 22,
    "living_room": 22,
    "bedroom": 20,
    "bathroom": 10,
    "entrance": 21
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-14T07:08:06] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-14T07:08:15] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-14T08:33:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-14T20:36:15] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-14T05:31:07] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-14T07:08:06] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-14T07:08:15] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-14T08:33:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-14T12:35:07] bedroom_window | WindowCovering.CurrentP

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

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

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Bedroom window covering sensor data exhibits impossible values (10000), suggesting a firmware bug, calibration error, or signal interference rather than actual physical state.",
      "supported_by": ["[2026-06-14T12:35:07] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000", "[2026-06-14T20:36:20] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000"],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "The occupancy sensor in the bedroom is functioning correctly by reporting '0' (empty) at consistent midnight intervals, aligning with the household activity pattern where no one is present.",
      "supported_by": ["[2026-06-14T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0", "Room activity count for bedroom is low (20), consistent with empty periods."],
      "contradicted_by": []
    }
  ],
  "most_concerning_signals": [
    "[2026-06-14T12:35:07] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
    "[2026-06-14T20:36:20] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000"
  ],
  "what_to_verify_in_raw_log": [
    "Check raw radio packets for the bedroom window covering motor to distinguish between a valid high-frequency pulse glitch and a corrupted payload.",
    "Verify if the '10000' value persists across multiple subsequent readings or reverts immediately to 0/100.",
    "Cross-reference with the motor power consumption logs to see if commands were actually sent during the anomalous readings."
  ],
  "provisional_risk": "low"
}

## Focused Raw Log
[2026-06-14T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue =


The living room occupancy sensor is malfunctioning by persistently reporting 'Empty' (0) despite significant temperature fluctuations indicating human presence and activity.

Explanation: Temperature sensors in the living room show continuous increases from 2265 to 2397 between 00:00 and 04:00, strongly suggesting a person is present generating heat.

Explanation: During this same period, the living_room_occupancy sensor consistently reports Occupancy=0, contradicting the thermal evidence.

Explanation: The sensor only updates to Occupancy=1 at 13:59, which is over 9 hours after the initial activity began, confirming the device failed to detect occupants during the night/early morning.

Explanation: This pattern matches H1 where the sensor reports a constant 'Empty' state despite high activity levels.

[2026-06-21T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2265

[2026-06-21T04:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2397

[2026-06-21T04:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0

Immediately inspect and replace or recalibrate the living room occupancy sensor.

Verify if the sensor firmware has been updated or if a battery replacement is required.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

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

## 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>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1848,
  "salient_event_count": 60,
  "focus_event_count": 95,
  "room_activity": {
    "kitchen": 22,
    "living_room": 22,
    "bedroom": 19,
    "bathroom": 11,
    "entrance": 21
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-21T06:58:08] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-21T06:58:13] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-21T08:22:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-21T20:35:13] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-21T05:29:14] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-21T06:58:08] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-21T06:58:13] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-21T08:22:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-21T12:38:15] bedroom_window | WindowCovering.Curr

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

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

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Living room occupancy sensor is reporting a constant 'Empty' (0) state despite high activity levels and time-of-day expectations for an elderly resident.",
      "supported_by": ["room_activity.living_room = 22 (indicates events are being logged in this room)", "suspicious_signals contains multiple living_room_occupancy entries all showing Occupancy=0 across different times (00:00, 00:30, etc.)"],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "The system correctly reports the living room as empty because the elderly resident is only active in other rooms (Kitchen, Bedroom, Entrance) during these specific timestamps.",
      "supported_by": [],
      "contradicted_by": ["room_activity.living_room = 22 suggests significant interaction or movement detection events occurred here, which would likely trigger occupancy changes if the sensor were working normally"]
    }
  ],
  "most_concerning_signals": [
    "[2026-06-21T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-21T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0"
  ],
  "what_to_verify_in_raw_log": [
    "Check raw motion detection logs (PIR/ToF readings) for the living_room to see if physical movement was detected but filtered out by the sensor firmware.",
    "Verify the timestamp of the last successful calibration or battery change for the living_room_occupancy device.",
    "Cross-reference with camera feeds or door logins to confirm if the user entered the living room between 00:00 and 00:30."
  ],
  "provisional_risk": "medium"
}

## Focused Raw Log
[2026-06-21T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.Measure


The kitchen occupancy sensor is reporting a persistent 'empty' (0) state for over 4 hours despite evidence of high activity in the area and subsequent detection later in the day.

Explanation: Evidence shows 22 recorded activity events in the kitchen during the period where the sensor reported 0 occupancy, indicating physical presence or appliance usage occurred.

Explanation: Raw logs confirm the sensor remained stuck at 'Occupancy = 0' from 00:00 until 07:09, failing to detect motion or changes even when temperature sensors were actively reading values.

Explanation: The sensor eventually reported '1' at 07:09 and again at 12:21, confirming the device is functional but suffered a failure mode (stuck-low) during the initial window.

Stage-1 Analysis note: 'kitchen': 22 events in room_activity indicating human presence or appliance usage occurred.

[2026-06-21T07:09:06] kitchen_occupancy | OccupancySensing.Occupancy = 1

Inspect the kitchen PIR/occupancy sensor for calibration drift or obstruction in the field of view.

Check wiring or power supply stability for the specific sensor node between 00:00 and 07:00.

Reset the sensor or replace it if hardware failure is confirmed.

Search for raw IR/PIR pulse timestamps in the kitchen zone to correlate with the 22 reported activity events. If pulses exist but no occupancy update was sent, the communication link or processing logic is faulty.

Check if the kitchen occupancy sensor has a history of 'Out of Range' or 'Calibration Failed' error logs prior to the current session.

Verify if the 22 'kitchen' activities correspond to motion detection in adjacent rooms (e.g., living room) that might have been misattributed in the summary statistics.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## 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: 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>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1850,
  "salient_event_count": 60,
  "focus_event_count": 96,
  "room_activity": {
    "kitchen": 22,
    "living_room": 20,
    "bedroom": 20,
    "bathroom": 11,
    "entrance": 23
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-21T07:07:09] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-21T07:07:19] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-21T08:24:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-21T20:49:06] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-21T05:27:17] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-21T07:07:09] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-21T07:07:19] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-21T08:24:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-21T12:20:05] bedroom_window | WindowCovering.CurrentP

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## 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。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Kitchen occupancy sensor is reporting persistent 'empty' (0) status despite high activity counts in the kitchen area, suggesting a potential sensor malfunction or calibration drift.",
      "supported_by": [
        "Evidence shows 'kitchen': 22 events in room_activity, indicating human presence or appliance usage occurred.",
        "Suspicious signals show '[2026-06-21T00:00:00] kitchen_occupancy | OccupancySensing.Occupancy = 0', and repeated checks at 00:30 also show 0."
      ],
      "contradicted_by": [
        "No specific log entry explicitly states the sensor failed; it could theoretically be that all activity happened while the user was technically outside the immediate PIR field, though unlikely given the count of 22 events."
      ]
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "All kitchen-specific sensors (temperature, water leak, smoke, etc.) are not present in the 'suspicious_signals' list, implying they did not trigger error codes or unexpected state changes within this evidence window.",
      "supported_by": [
        "The absence of any 'kitchen_temperature', 'kitchen_water_leak', or 'kitchen_smoke_co_alarm' entries in the 'suspicious_signals' array."
      ],
      "contradicted_by": [
        "Absence of data does not confirm functionality; a silent failure mode where the sensor stops sending updates would not appear as a signal but would result in missing data (though here we see explicit 0 values for occupancy)."
      ]
    }
  ],
  "most_concerning_signals": [
    "[2026-06-21T00:00:00] kitchen_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-21T00:30:00] kitchen_occupancy | OccupancySensing.Occupancy = 0"
  ],
  "what_to_


The living room occupancy sensor is functioning correctly; the lack of 'Occupancy=1' events between 06:53 and 08:31 is consistent with the resident entering the house, bypassing the living room (likely going directly to the kitchen), and exiting without triggering motion in that specific zone.

Explanation: Raw logs confirm the front door was unlocked at 06:53:10 and locked again at 08:31:00, indicating a single entry/exit event within the window where no living room occupancy was detected.

Explanation: During this same window (06:53-08:31), the kitchen occupancy sensor triggered at 06:53:03, suggesting the resident moved directly into the kitchen upon entry, avoiding the living room path entirely.

Explanation: At 14:08:10, the system correctly registered Occupancy=1 for the living room, proving the sensor itself is not stuck or malfunctioning.

Explanation: Temperature readings in the living room show normal gradual increases during the night and day, further indicating no sudden environmental changes that would suggest a sensor failure masking an event.

[2026-06-21T06:53:03] kitchen_occupancy | OccupancySensing.Occupancy = 1

[2026-06-21T14:08:10] living_room_occupancy | OccupancySensing.Occupancy = 1

No action required; system is operating as expected.

Check raw millisecond-level data for living_room_occupancy between 06:53 and 08:31 to see if there were transient occupancy signals that were filtered out or missed.

Verify if the living_room_air_conditioner status changed during this window, which would imply human presence even if the motion sensor didn't report it.

Cross-reference with front_door_lock events to determine if the resident entered via the entrance and moved directly to kitchen/bedroom without passing through the living room.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

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

## 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>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1853,
  "salient_event_count": 60,
  "focus_event_count": 95,
  "room_activity": {
    "kitchen": 21,
    "living_room": 23,
    "bedroom": 19,
    "bathroom": 11,
    "entrance": 21
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-21T06:53:10] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-21T06:53:19] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-21T08:31:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-21T20:54:16] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-21T05:32:13] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-21T06:53:10] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-21T06:53:19] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-21T08:31:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-21T12:28:15] bedroom_window | WindowCovering.Curr

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

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

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Living room occupancy sensor is unresponsive or stuck in 'empty' state despite potential activity, indicated by the lack of any salient events in living_room compared to other rooms.",
      "supported_by": ["room_activity.living_room = 23 (low relative to event count but mostly lock/window), no specific occupancy change logs for living_room in suspicious_signals between midnight and 00:30 unlike other rooms"],
      "contradicted_by": ["suspicious_signals contains explicit occupancy=0 at 00:00:00 and 00:30:00 for all rooms including living_room, which technically shows the sensor *is* reporting a value, but fails to detect presence if anyone entered"]
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "All sensors are functioning correctly; the low activity count in living_room reflects the actual behavior of the elderly resident who spent most time in other rooms or outside the monitored zones during the log period.",
      "supported_by": ["consistent zero occupancy reports across all rooms at scheduled intervals (00:00, 00:30) indicating system-wide synchronization and no total system failure"],
      "contradicted_by": ["discrepancy in timing: bedroom_window and front_door_lock have multiple events between 06:53 and 08:31, while living_room has none, suggesting the resident may have bypassed the living room entirely or the motion sensor failed to trigger on movement"]
    }
  ],
  "most_concerning_signals": [
    "[2026-06-21T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-21T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0"
  ],
  "what_to_verify_in_raw_log": [
    "Check raw millisecond-level data for liv


Entrance occupancy sensor is functioning correctly; all timestamps show 'Occupied=0' consistent with no entry events and door lock status changes indicating manual operation without occupancy detection.

Explanation: Raw log shows entrance_occupancy consistently reporting OccupancySensing.Occupancy = 0 at every recorded interval (00:00 to 04:30).

Explanation: No transient 'Occupied=1' states were missed in the raw data between midnight and early morning.

Explanation: Subsequent activity at 07:04 shows front_door_lock operations and contact state changes without triggering an occupancy event, confirming the sensor does not falsely detect presence during door interactions.

[2026-06-04T07:04:04] front_door_contact | BooleanState.StateValue = False

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## 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: 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>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1850,
  "salient_event_count": 60,
  "focus_event_count": 95,
  "room_activity": {
    "kitchen": 23,
    "living_room": 23,
    "bedroom": 18,
    "bathroom": 10,
    "entrance": 21
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-04T07:04:04] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-04T07:04:08] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-04T08:31:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-04T20:43:11] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-04T05:40:12] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-04T07:04:04] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-04T07:04:08] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-04T08:31:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-04T12:38:06] bedroom_window | WindowCovering.Current

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## 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。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "normal",
      "description": "Entrance occupancy sensor is functioning normally, correctly detecting the absence of presence during early morning hours.",
      "supported_by": ["[2026-06-04T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0"],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "anomaly",
      "description": "Potential false positive or sensor glitch where the entrance occupancy sensor reports 'Occupied' (1) despite no activity logs for that room and a clean state at midnight.",
      "supported_by": [],
      "contradicted_by": ["No 'Occupied=1' events recorded in suspicious_signals for entrance_occupancy", "Low activity count (21) compared to living/kitchen suggests limited interaction"]
    }
  ],
  "most_concerning_signals": [
    "[2026-06-04T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0"
  ],
  "what_to_verify_in_raw_log": [
    "Check raw timestamped events between T-1 hour and T+1 hour of the '00:00:00' report to ensure no transient 'Occupied=1' states were missed by the summary aggregation.",
    "Verify if the '21' activity count in room_activity corresponds to valid sensor triggers or just background noise from the door lock/switch operations."
  ],
  "provisional_risk": "low"
}

## Focused Raw Log
[2026-06-04T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2266
[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.Occupa


Bathroom occupancy sensor is functioning normally; the lack of 'Occupied' events indicates the room remained empty during the observation window, consistent with user activity occurring in other rooms.

Explanation: Raw logs show continuous '0' status for bathroom_occupancy from midnight until late evening, indicating no detected presence.

Explanation: User activity (lighting, door locks, window operations) is confirmed in bedroom, kitchen, and living_room at various times, proving the system is active and recording events elsewhere.

Explanation: The absence of bathroom occupancy events correlates with a lack of user movement in that specific zone, rather than a sensor failure, as the sensor correctly reports an empty state.

[2026-06-23T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0

[2026-06-23T20:43:17] bedroom_light | OnOff.OnOff = True

Verify timestamps of 'bathroom_onoff_light' state changes to determine if lights were turned on manually or automatically; if manual, it confirms human presence despite occupancy sensor silence.

Cross-reference 'bathroom_occupancy' heartbeat intervals with known timestamps of user movement in other rooms (e.g., kitchen/living room) to spot gaps in transmission.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

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

## 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>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1851,
  "salient_event_count": 60,
  "focus_event_count": 95,
  "room_activity": {
    "kitchen": 22,
    "living_room": 23,
    "bedroom": 20,
    "bathroom": 10,
    "entrance": 20
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-23T06:55:02] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-23T06:55:08] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-23T08:30:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-23T20:43:09] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-23T05:29:05] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-23T06:55:02] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-23T06:55:08] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-23T08:30:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-23T12:22:06] bedroom_window | WindowCovering.Current

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

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

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Bathroom occupancy sensor (bathroom_occupancy) is likely malfunctioning or disconnected, reporting continuous 'empty' status despite expected activity.",
      "supported_by": [
        "Evidence Packet shows only 10 total events in the bathroom compared to ~20-23 in other active rooms (kitchen, living_room, bedroom, entrance).",
        "The provided 'suspicious_signals' list contains NO entries for 'bathroom_occupancy', suggesting a lack of state changes or triggers during the observation window.",
        "In a single-elderly-person layout, if the user entered/used the bathroom (implied by room activity count > 0), the sensor should have triggered an 'Occupied' event, similar to the detailed logs seen for windows and doors elsewhere."
      ],
      "contradicted_by": [
        "Room activity count is non-zero (10), which theoretically implies some interaction occurred, but this could be inferred from other sensors (e.g., water leak or light) rather than occupancy."
      ]
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "Bathroom lighting system is functioning normally based on available data.",
      "supported_by": [],
      "contradicted_by": []
    }
  ],
  "most_concerning_signals": [
    "Absence of any 'bathroom_occupancy' event in the suspicious_signals list despite the room having activity.",
    "Disparity between low bathroom event count (10) and higher counts in adjacent or similar-use rooms (kitchen: 22, living_room: 23)."
  ],
  "what_to_verify_in_raw_log": [
    "Check raw logs for 'bathroom_water_leak_detector' events to see if water activation occurred without corresponding occupancy detection.",
    "Verify timestamps of 'bathroom_onoff_l


Kitchen temperature sensor is reporting physically impossible values (2264°C - 2484°C) indicating a severe calibration failure or data corruption, creating a critical fire risk despite the absence of occupancy.

Explanation: The raw log shows kitchen_temp_sensor readings escalating from 2264 to over 2400 between 00:00 and 04:30. These values represent thousands of degrees Celsius, which is physically impossible for a kitchen environment.

Explanation: This pattern indicates a 'sensor drift' or internal fault where the measurement unit has been corrupted or the sensor is malfunctioning, rather than reflecting actual ambient heat.

Explanation: While occupancy was zero during this period, a safety system must flag this because if an occupant had entered or if a fire started, the sensor would not provide accurate detection capabilities due to the baseline error.

[2026-06-08T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2264

[2026-06-08T04:30:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2428

Immediately isolate the kitchen temperature sensor from the automation logic to prevent false alarms or missed detections.

Dispatch technical support to replace or recalibrate the kitchen temperature sensor hardware.

Temporarily enable manual override monitoring for the kitchen zone until the device is verified functional.

The layout specifies an 'Elderly Living Alone' scenario; anomaly detection systems typically flag total silence in safety-critical zones (like kitchen with gas/stove) even if no one is present, unless explicitly configured otherwise. The disparity between 'suspicious_signals' having 60 items and none being kitchen-related is statistically significant given the 24-hour span implied by timestamps ranging from 00:00 to 20:42.

Absence of any 'kitchen_' prefixed events in 'suspicious_signals' despite timestamp coverage of waking hours (07:00 - 20:42).

Total event count for kitchen (23) is disproportionately low compared to expected sensor refresh rates for temperature, smoke, and occupancy in a safety-critical zone.

Lack of correlation between Front Door Lock operations (indicating arrival/departure) and subsequent Kitchen activity, which is typical for an elderly resident preparing meals upon returning home.

Search raw logs for any heartbeat or status reports from 'kitchen_temperature_sensor', 'kitchen_water_leak_detector', or 'kitchen_smoke_co_alarm' specifically.

Check if there were any 'DeviceOffline' or 'ConnectionLost' error codes associated with the kitchen device IDs around 08:00 and 13:00.

Verify if the 'cook_surface' sensor has been reporting power state or usage timers intermittently, as this often generates background noise even without active cooking.

Cross-reference the exact timestamp of the last known valid reading for the kitchen occupancy sensor against the first entry in the provided packet.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## 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: 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>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1849,
  "salient_event_count": 60,
  "focus_event_count": 95,
  "room_activity": {
    "kitchen": 23,
    "living_room": 22,
    "bedroom": 18,
    "bathroom": 10,
    "entrance": 22
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-08T07:03:06] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-08T07:03:17] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-08T08:29:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-08T20:42:15] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-08T05:26:20] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-08T07:03:06] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-08T07:03:17] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-08T08:29:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-08T12:32:17] bedroom_window | WindowCovering.CurrentP

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## 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。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Kitchen area sensors appear non-functional or offline due to a complete lack of activity logs compared to other rooms and the global occupancy baseline.",
      "supported_by": ["room_activity.kitchen shows only 23 events (likely static/config), while living_room/entrance have 22 each during active hours; absence of any dynamic state changes (temp, leak, smoke, cook_surface) in the evidence packet for kitchen; suspicious_signals contains zero entries related to 'kitchen_', 'water_leak', 'smoke_co_alarm', 'cook_surface', or 'temperature' despite multiple timestamps where activity occurred elsewhere (e.g., door locks at 07:03, window ops at 13:50)."],
      "contradicted_by": ["The system is receiving data from other zones (bedroom window, front door lock) proving network connectivity exists; The 'focus_event_count' of 95 suggests the system expected more granular data than just room-level aggregates."]
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "Kitchen sensors are functioning normally but the user did not enter the kitchen during the monitoring period, resulting in no event generation.",
      "supported_by": ["Global occupancy signals show all rooms at 0% at midnight and 00:30; If the household was empty for most of the day, kitchen sensors would remain idle. The low count (23) might represent initial boot-up checks or daily calibration rather than human interaction.", "No contradictory high-activity events in living_room or entrance suggest a single-person scenario where the individual may have stayed in bedroom/living room."],
      "contradicted_by": ["The layout specifies an 'Elderly Living Alone' scenario; anomaly detection systems typically flag tot


The bathroom occupancy sensor is malfunctioning or disabled, failing to report presence during active household events.

Explanation: Household activity (lighting, window operation, door locks) confirms the resident was present and moving between rooms (kitchen, living room, bedroom).

Explanation: Occupancy sensors in kitchen, living room, and bedroom successfully triggered 'Occupancy = 1' events corresponding to these activities.

Explanation: Despite confirmed human presence in adjacent areas and at different times, the bathroom occupancy sensor only reported '0' throughout the entire log period with no positive detection events.

Explanation: This consistent lack of signal contradicts expected usage patterns for an elderly resident alone, indicating a device failure rather than user behavior.

[2026-06-11T08:20:03] kitchen_occupancy | OccupancySensing.Occupancy = 1

[2026-06-11T12:36:03] living_room_occupancy | OccupancySensing.Occupancy = 1

[2026-06-11T05:27:04] bedroom_light | OnOff.OnOff = True (indicating resident presence)

No timestamped entries exist in the provided log where bathroom_occupancy.Occupancy equals 1.

Physically inspect the bathroom occupancy sensor to verify power supply and battery status.

Check smart home app settings to ensure the bathroom sensor is not accidentally set to 'disabled', 'maintenance mode', or filtered out.

Replace the sensor if hardware inspection reveals no issues, given the persistent failure to detect motion.

In an 'Elderly Living Alone' scenario, a total lack of motion-triggered events compared to neighboring rooms (entrance/kitchen) over a 15+ hour span is statistically improbable for normal behavior unless the house was entirely vacant, which contradicts the door lock operations showing manual locking/unlocking while inside (implied by the sequence).

Discrepancy between high activity in Entrance/Kitchen/LivingRoom and critically low activity in Bathroom relative to an elderly solo resident profile.

Absence of any positive OccupancyState transitions (0 -> 1) for bathroom_occupancy in the provided salient/focus events.

Search for any timestamped entries where bathroom_occupancy.Occupancy equals 1 within the time range of other room activities (e.g., 07:00 - 20:00).

Check system configuration logs to see if bathroom_occupancy has been manually set to 'disabled', 'maintenance mode', or 'offline'.

Verify battery voltage or signal strength metrics for the bathroom_occupancy device if available in the metadata layer.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

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

## 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>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1850,
  "salient_event_count": 60,
  "focus_event_count": 95,
  "room_activity": {
    "kitchen": 23,
    "living_room": 23,
    "bedroom": 18,
    "bathroom": 10,
    "entrance": 21
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-11T07:08:08] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-11T07:08:14] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-11T08:21:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-11T20:44:09] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-11T05:27:11] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-11T07:08:08] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-11T07:08:14] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-11T08:21:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-11T12:35:13] bedroom_window | WindowCovering.Current

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

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

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Bathroom occupancy sensor is likely malfunctioning or disabled, failing to detect the resident's presence during active household events.",
      "supported_by": [
        "bathroom room_activity count (10) is significantly lower than kitchen/living_room/entrance (~23), suggesting a lack of triggered motion events despite expected usage patterns for an elderly person.",
        "Multiple timestamped events indicate activity in other rooms (kitchen, living_room, entrance) and door/window operations between 07:08 and 20:44. If the resident moved from the entrance to the bathroom (common routine), the absence of corresponding 'OccupancySensing.Occupancy = 1' events for the bathroom implies the sensor did not trigger."
      ],
      "contradicted_by": [
        "The raw log provided only shows `OccupancySensing.Occupancy = 0` at midnight intervals; it does not contain any explicit positive detection events (`=1`) for the bathroom, so we cannot definitively prove *when* it failed versus when it was simply off. However, the statistical gap in event counts strongly suggests a failure to report state changes."
      ]
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "All bathroom sensors are functioning correctly, but the low event count is due to the specific time window analyzed containing no bathroom visits by the resident.",
      "supported_by": [
        "No explicit error codes or 'sensor offline' flags are present in the suspicious_signals list for bathroom_occupancy.",
        "The temperature_patterns array is empty, which might imply stable conditions, though it could also mean no data was logged due to the missing occupancy triggers."
      ],
      "contr


The living room occupancy sensor is stuck in an 'Empty' state during periods of confirmed human activity and movement in the same household.

Explanation: Raw logs confirm multiple instances of human presence (bedroom lights on, front door lock/unlock cycles) occurring while the living_room_occupancy sensor continuously reported 0.

Explanation: At T=14:01:08, the entrance sensor correctly detected occupancy=1, and immediately after at T=14:01:08, the living_room sensor also switched to 1, proving the device is capable of detecting motion but failed to do so earlier when the resident was active.

Explanation: The lack of any 'Occupancy = 1' readings for the living room between 00:00:00 and 14:01:08, despite temperature fluctuations suggesting a lived-in environment, indicates a hardware failure or communication glitch rather than environmental interference.

[2026-06-24T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0 vs. [2026-06-24T05:25:06] bedroom_light | OnOff.OnOff = True

[2026-06-24T14:01:08] living_room_occupancy | OccupancySensing.Occupancy = 1 (successful detection after long period of false negatives)

Physically inspect the living room PIR sensor for obstruction, dirt, or damage.

Check the sensor's power supply and communication link stability.

Replace the sensor if calibration attempts fail or physical inspection reveals no issues.

```json
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Living room occupancy sensor is malfunctioning or has a communication fault, as it reports 'Empty' (0) continuously throughout the day despite high activity counts and user interactions in other rooms.",
      "supported_by": [
        "Evidence: living_room_occupancy consistently reports Occupancy = 0 at 00:00:00, 00:30:00, and implied intervals.",
        "Evidence: Room activity metrics show 23 events in living_room, indicating significant human presence or movement that should trigger the sensor.",
        "Evidence: Contrast with entrance, kitchen, and bedroom which also report 0 but have specific lock/window events suggesting active monitoring; however, the sheer volume of 'living_room' activity vs. static '0' status is suspicious."
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "anomaly",
      "description": "Potential false negative due to environmental interference (e.g., strong AC airflow from the adjacent air_conditioner causing blind spots for PIR sensors).",
      "supported_by": [
        "Evidence: Layout indicates living_room contains an <air_conditioner>.",
        "Evidence: H1 hypothesis regarding continuous 0 readings."
      ],
      "contradicted_by": []
    },
    {
      "id": "H3",
      "type": "normal",
      "description": "The system is correctly reporting no occupancy because the resident is sleeping or away during these specific timestamps, and the 'activity count' refers to non-occupancy related events (like temperature fluctuations or device toggles).",
      "supported_by": [],
      "contradicted_by": [
        "Evidence: The query context implies checking for 'working normally' against a baseline of expected interaction; usually, if there are 23 activity events in a room, at least some involve motion detection unless all were caused by pets or appliances triggering the counter without person detection.",
        "Evidence: Other rooms (kitchen, entrance) show higher event counts (21, 22) and likely correlate with movement."
    }
  ],
  "most_concerning_signals": [
    "[2026-06-24T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-24T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0"
  ],
  "what_to_verify_in_raw_log": [
    "Check raw PIR/Infrared signal strength or beam break logs for living_room_occupancy around times when other room sensors detected activity.",
    "Verify if the air_conditioner power state changed recently, potentially disrupting sensor calibration.",
    "Cross-reference video feeds (if available) or doorbell logs for the entrance to confirm if the elderly resident entered/left the house while the living room reported empty."
  ],
  "provisional_risk": "medium"
}
```

## Task
Analyze the following evidence packet for a smart-home anomaly query.

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

## 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>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1851,
  "salient_event_count": 60,
  "focus_event_count": 95,
  "room_activity": {
    "kitchen": 21,
    "living_room": 23,
    "bedroom": 19,
    "bathroom": 10,
    "entrance": 22
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-24T06:53:10] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-24T06:53:16] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-24T08:31:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-24T20:35:14] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-24T05:25:16] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-24T06:53:10] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-24T06:53:16] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-24T08:31:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-24T12:24:14] bedroom_window | WindowCovering.Curr

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

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

## Stage-1 Analysis
```json
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Living room occupancy sensor is malfunctioning or has a communication fault, as it reports 'Empty' (0) continuously throughout the day despite high activity counts and user interactions in other rooms.",
      "supported_by": [
        "Evidence: living_room_occupancy consistently reports Occupancy = 0 at 00:00:00, 00:30:00, and implied intervals.",
        "Evidence: Room activity metrics show 23 events in living_room, indicating significant human presence or movement that should trigger the sensor.",
        "Evidence: Contrast with entrance, kitchen, and bedroom which also report 0 but have specific lock/window events suggesting active monitoring; however, the sheer volume of 'living_room' activity vs. static '0' status is suspicious."
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "anomaly",
      "description": "Potential false negative due to environmental interference (e.g., strong AC airflow from the adjacent air_conditioner causing blind spots for PIR sensors).",
      "supported_by": [
        "Evidence: Layout indicates living_room contains an <air_conditioner>.",
        "Evidence: H1 hypothesis regarding continuous 0 readings."
      ],
      "contradicted_by": []
    },
    {
      "id": "H3",
      "type": "normal",
      "description": "The system is correctly reporting no occupancy because the resident is sleeping or away during these specific timestamps, and the 'activity count' refers to non-occupancy related events (like temperature fluctuations or device toggles).",
      "supported_by": [],
      "contradicted_by": [
        "Evidence: The query context implies checking for 'working normally' against a baseline of expect


The living room occupancy sensor is malfunctioning and stuck in a 'false empty' state despite clear evidence of human presence and activity in the house.

Explanation: All other sensors (bedroom, kitchen, bathroom) correctly report occupancy changes throughout the day, proving the system is generally functional and residents are active.

Explanation: At 13:58:07, the bedroom occupant enters the living room (indicated by the light turning on at 12:47 and window closing), yet the living_room_occupancy sensor remains at 0 until explicitly changing to 1 later, suggesting a failure to detect motion or a logic error rather than actual absence.

Explanation: Temperature logs show significant heating activity in the living room (rising from 2276 to 2530 Kelvin range, approx 22-220C? Note: Likely scaled units where 2276 ~ 22°C rising to higher values), indicating the space was conditioned while occupied, contradicting the 'empty' sensor reading.

[2026-06-25T13:58:07] living_room_occupancy | OccupancySensing.Occupancy = 1

[2026-06-25T08:20:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2530

Immediately verify physical presence in the living room via camera or visual inspection.

Reset the living room occupancy sensor or replace the PIR unit as it is likely faulty or obstructed.

Correlate living_room light (dimmable_light) and air_conditioner (air_conditioner) state changes with occupancy claims.

Verify if the timestamp '2026-06-25' corresponds to a weekend or holiday when the elder might be resting elsewhere.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

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

## 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>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1851,
  "salient_event_count": 60,
  "focus_event_count": 95,
  "room_activity": {
    "kitchen": 23,
    "living_room": 22,
    "bedroom": 19,
    "bathroom": 11,
    "entrance": 20
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-25T06:58:02] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-25T06:58:08] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-25T08:20:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-25T20:47:14] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-25T05:30:12] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-25T06:58:02] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-25T06:58:08] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-25T08:20:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-25T12:39:12] bedroom_window | WindowCovering.Curr

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

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

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Living room occupancy sensor reports continuous 'empty' status (0) for the entire observed period, despite being in a shared residence context where activity is expected.",
      "supported_by": ["[2026-06-25T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0", "[2026-06-25T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0"],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "anomaly",
      "description": "Potential sensor failure or obstruction causing false negative occupancy detection in the living room.",
      "supported_by": ["H1 description"],
      "contradicted_by": []
    },
    {
      "id": "H3",
      "type": "normal",
      "description": "The elderly resident has vacated the home and all sensors are correctly reporting empty states due to no human presence.",
      "supported_by": ["front_door_lock lock/unlock events suggest door operations but don't confirm internal presence timing relative to occupancy data"],
      "contradicted_by": ["H1 description suggests prolonged static state without variation typical of daily life logs, though this is weak evidence given limited log snippet"]
    }
  ],
  "most_concerning_signals": [
    "Continuous Occupancy=0 for living_room across multiple timestamps (00:00:00, 00:30:00)",
    "Lack of any other living_room specific events (lights, AC, curtains) toggling on/off during the day, which usually correlates with occupancy"
  ],
  "what_to_verify_in_raw_log": [
    "Check raw motion detector PIR beam interruption logs for living_room to distinguish between sensor dead zone vs. actual no-motion.",
    "Correlate living_room light (dimmable_light) and air_conditioner (air_conditio


The entrance occupancy sensor functioned correctly by detecting human presence during manual door interactions, contradicting the hypothesis of total failure or false negatives.

Explanation: Manual lock operations occurred at 06:55 and 08:34, implying human physical presence at the entrance.

Explanation: Contrary to the initial concern of a 'stuck' or failed sensor reporting '0', the log explicitly shows 'entrance_occupancy | OccupancySensing.Occupancy = 1' recorded at 08:30:07.

Explanation: This detection occurred just before the 08:34:00 manual lock event, confirming the sensor successfully detected the occupant and is working as intended.

[2026-06-02T08:30:07] entrance_occupancy | OccupancySensing.Occupancy = 1

Continue standard monitoring; no immediate intervention required.

Verify that the previous 'Occupancy=0' reading at 00:00:00 was due to legitimate absence rather than sensor lag (likely normal given the long duration until first activity).

Timestamped logs from entrance_occupancy immediately before and after the 06:55:04 and 08:34:00 lock events to confirm if any transient '1' (occupied) states were missed or filtered out.

Signal strength (RSSI) or battery voltage data for the entrance_occupancy sensor around the times of the manual lock events to rule out power loss or interference.

Calibration history or reset events for the entrance_occupancy sensor.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## 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: 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>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1851,
  "salient_event_count": 60,
  "focus_event_count": 95,
  "room_activity": {
    "kitchen": 20,
    "living_room": 21,
    "bedroom": 20,
    "bathroom": 12,
    "entrance": 22
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-02T06:55:04] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-02T06:55:15] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-02T08:34:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-02T20:47:17] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-02T05:40:09] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-02T06:55:04] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-02T06:55:15] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-02T08:34:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-02T12:22:07] bedroom_window | WindowCovering.Current

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## 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。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Entrance occupancy sensor exhibits a false negative (or total failure) during active residential hours, failing to detect presence despite door interaction events.",
      "supported_by": [
        "[2026-06-02T06:55:04] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
        "[2026-06-02T08:34:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
        "[2026-06-02T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "The residence is unoccupied, and all sensors are reporting correctly based on the lack of human activity.",
      "supported_by": [
        "[2026-06-02T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-02T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0"
      ],
      "contradicted_by": [
        "[2026-06-02T06:55:04] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
        "[2026-06-02T08:34:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)"
      ]
    }
  ],
  "most_concerning_signals": [
    "Manual lock operations at 06:55 and 08:34 imply human entry/exit, yet the entrance occupancy sensor reports '0' (empty) at the start of the day and does not show activity consistent with these manual interactions.",
    "Discrepancy between 'Manual' door lock operations (requiring human physical presence) and static 'Occupancy=0' readings for the entrance zone."
  ],
  "what_to_verify_in_raw_log": [
    "Timestamped logs from entrance_occupancy immediately before


状态 vs 实际位置不一致

The living room occupancy sensor is stuck reporting '0' (empty) despite significant house activity and temperature changes, indicating a hardware or firmware failure rather than a security breach.

Explanation: Raw logs show the living_room_occupancy sensor consistently reporting Occupancy = 0 at regular 30-minute intervals from midnight to morning.

Explanation: This contradicts Stage-1 evidence stating the living room had 42 activities, implying people were present but the sensor failed to detect motion.

Explanation: Crucially, other sensors in different rooms (bedroom, bathroom) also report 0 during these same intervals, suggesting a potential system-wide clock sync issue, network broadcast failure, or mass sensor reset event affecting the Z-Wave/Wi-Fi mesh, rather than an isolated local malfunction.

Stage-1 analysis notes: 'Room activity count for living_room is 42... indicating significant events occurred there.'

Check the smart home hub/network logs for signal strength loss or packet loss between midnight and 08:00.

Perform a manual physical test of the living room motion sensor by waving a hand in front of it while monitoring the app.

Raw telemetry from the living_room_occupancy sensor to check for signal strength, battery levels, or communication errors during the reported zero-occupancy windows.

Logs from other motion detectors (bedroom/bathroom) to confirm if their simultaneous 0 readings indicate a global system reset or just a localized failure.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

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

## 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>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1344,
  "salient_event_count": 60,
  "focus_event_count": 103,
  "room_activity": {
    "kitchen": 18,
    "living_room": 42,
    "bedroom": 22,
    "bathroom": 18,
    "entrance": 3
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-07T22:58:38] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-07T05:26:01] living_room_window | OperationalStatus = 0b000010",
    "[2026-06-07T05:26:30] living_room_window | OperationalStatus = 0b000010",
    "[2026-06-07T05:26:30] living_room_window | CurrentPositionLiftPercent100ths = 5000",
    "[2026-06-07T05:27:00] living_room_window | OperationalStatus = 0b000010",
    "[2026-06-07T08:40:09] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-07T10:07:20] living_room_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-07T22:58:28] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
    "[2026-06-07T22:58:38] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-07T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

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

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Living room occupancy sensor is malfunctioning or falsely reporting an empty state during periods of high activity.",
      "supported_by": ["Room activity count for living_room is 42 (highest in the house), indicating significant events occurred there.", "Multiple suspicious signals show 'living_room_occupancy' consistently reporting Occupancy = 0 at regular intervals (00:00, 00:30, 01:00, 01:30)."],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "The living room window covering and status sensors are functioning correctly, reflecting automated user routines.",
      "supported_by": ["OperationalStatus = 0b000010 appears multiple times, likely a standard 'open/closed' or 'fault' flag consistent with a specific state change.", "CurrentPositionLiftPercent100ths changes from 5000 to 0, indicating the curtain was lowered automatically.", "No contradictory data suggests these readings are impossible."],
      "contradicted_by": []
    }
  ],
  "most_concerning_signals": [
    "[2026-06-07T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-07T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-07T01:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-07T01:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0"
  ],
  "what_to_verify_in_raw_log": [
    "Timestamps and event types associated with the 42 living_room activities to see if they coincide with the 00:00-01:30 period where occupancy is reported as 0.",
    "Raw telemetry from the living_room_occupancy sensor to check for signal strength, battery levels, or communication errors during


温度传感器读数漂移（drift）

温度读数持续单向偏移，不符合正常日间温度曲线 其他传感器或空调自带温度显示不一致（如果可以交叉验证）

Living room occupancy sensor is functioning correctly by reporting the expected 'empty' state during morning hours and updating to 'occupied' upon human arrival.

Explanation: The living_room_occupancy sensor reports '0' (empty) from 00:00 to 06:00, which aligns with the absence of other activity logs in that specific room during this time window.

Explanation: At 06:19:00, a bedroom light turns on, followed by an immediate update to the bedroom_occupancy sensor at 06:24:00 indicating presence.

Explanation: Crucially, at 06:30:00, immediately after the household becomes active in other rooms, the living_room_occupancy sensor updates from 0 to 1, confirming it detects entry or movement and is not stuck.

Explanation: The pattern of static readings followed by a timely state change indicates normal operation rather than a failure.

[2026-06-01T06:30:00] living_room_occupancy | OccupancySensing.Occupancy = 1

[2026-06-01T06:19:00] bedroom_light | OnOff.OnOff = True

[2026-06-01T01:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0

Check raw timestamp intervals between occupancy reports: Are they exactly 30 minutes apart, or did the sensor stop sending data entirely?

Verify if any other living room devices (lights, AC, curtains) changed state during these times to confirm human presence or automated scheduling that should trigger occupancy re-evaluation.

Compare battery level or power status logs for the specific living_room_occupancy device if available.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

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

## 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>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1132,
  "salient_event_count": 60,
  "focus_event_count": 115,
  "room_activity": {
    "kitchen": 22,
    "living_room": 38,
    "bedroom": 22,
    "bathroom": 22,
    "entrance": 11
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-01T07:17:18] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-01T07:17:24] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-01T18:00:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-01T21:47:32] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-01T06:19:06] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-01T07:17:18] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-01T07:17:24] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-01T18:00:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-01T21:47:29] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
    "[2026-06-01T21:47:32] front_do

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

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

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Living room occupancy sensor is unresponsive or dead, showing a static '0' state for multiple hours despite high activity counts in the room.",
      "supported_by": ["Multiple consecutive readings of living_room_occupancy = 0 at 00:00, 00:30, 01:00, 01:30 indicating no state changes or detection capability"],
      "contradicted_by": ["Room activity count shows 38 events in living_room, suggesting other devices are active and the room is not physically empty or ignored by the system"]
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "The living room was genuinely empty during the early morning hours (00:00 - 01:30).",
      "supported_by": ["Occupancy sensor reads 0 consistently"],
      "contradicted_by": ["High 'room_activity' score (38) implies device interactions occurred in the living room; if the only occupant detector were off, it would be unlikely to have 38 distinct activity events attributed to that room unless the activity definition includes non-occupancy events like lights/AC toggling without human presence, which contradicts the typical definition of 'activity' in such logs. However, H1 is stronger because a static sensor often fails to update even when conditions change."],
      "confidence_note": "Less likely given the static nature of the log entries compared to dynamic updates seen elsewhere (e.g., door locks)."
    }
  ],
  "most_concerning_signals": [
    "[2026-06-01T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-01T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-01T01:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-01T01:30:00] living_room


状态 vs 实际位置不一致

The bedroom occupancy sensor is malfunctioning by incorrectly reporting 'Unoccupied' (0) shortly after detecting presence (1), despite corroborating evidence of light activation and subsequent window operation.

Explanation: At 06:29:00, the sensor correctly detected occupancy (1), triggering the bedroom light at 06:29:02.

Explanation: However, only 37 seconds later at 06:31:42, the sensor falsely reverted to 'Occupancy = 0' while the user was clearly still active (indicated by bathroom activity and lights being on).

Explanation: Subsequent events confirm the anomaly: the window coverings were commanded to close at 18:00 and successfully reported position changes (5000 -> 10000), proving the motor control system is functional, isolating the failure to the occupancy sensing logic or hardware.

[2026-06-19T06:29:00] bedroom_occupancy | OccupancySensing.Occupancy = 1

[2026-06-19T06:31:42] bedroom_occupancy | OccupancySensing.Occupancy = 0

[2026-06-19T06:29:02] bedroom_light | OnOff.OnOff = True

[2026-06-19T18:00:00] bedroom_window | Command: DownOrClose

Inspect and clean the PIR lens of the bedroom motion sensor for obstructions.

Review and adjust the sensor's sensitivity settings or reposition the device to reduce false negatives during low-light conditions.

Consider replacing the sensor unit if cleaning and calibration fail to resolve the intermittent zero-reporting.

```json
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Bedroom motion sensor (occupancy_sensor) is malfunctioning or has incorrect sensitivity settings, failing to detect movement during the night hours.",
      "supported_by": [
        "[2026-06-19T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-19T00:30:00] bedroom_occupancy | OccupancySensing.Occupancy = 0"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "anomaly",
      "description": "Bedroom window covering (window_covering) motor/control unit is stuck or reporting inconsistent position states.",
      "supported_by": [
        "[2026-06-19T06:29:12] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
        "[2026-06-19T18:00:30] bedroom_window | CurrentPositionLiftPercent100ths = 5000",
        "[2026-06-19T21:59:29] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000"
      ],
      "contradicted_by": []
    },
    {
      "id": "H3",
      "type": "normal",
      "description": "Bedroom temperature sensor is functioning normally, as there are no reported anomalies in the temperature data stream for this room.",
      "supported_by": [],
      "contradicted_by": []
    }
  ],
  "most_concerning_signals": [
    "Continuous 'Occupancy = 0' reports from bedroom_occupancy at midnight despite potential human activity context inferred from other rooms.",
    "Discontinuous and potentially conflicting 'CurrentPositionLiftPercent100ths' values (0 -> 5000 -> 10000) for bedroom_window without corresponding operational status changes."
  ],
  "what_to_verify_in_raw_log": [
    "Check raw IR/RF timestamps for bedroom_occupancy to see if any movement events were logged but filtered out by local logic vs. transmitted as false negatives.",
    "Verify the timestamp sequence for bedroom_window operations to determine if the position jumps correspond to actual motor commands or sensor readouts.",
    "Cross-reference bedroom_occupancy logs with front_door_lock unlock times to see if a person entered the house before the occupancy sensor reset."
  ],
  "provisional_risk": "medium"
}
```

## Task
Analyze the following evidence packet for a smart-home anomaly query.

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

## 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>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1129,
  "salient_event_count": 60,
  "focus_event_count": 106,
  "room_activity": {
    "kitchen": 17,
    "living_room": 34,
    "bedroom": 26,
    "bathroom": 18,
    "entrance": 11
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-19T07:28:13] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-19T07:28:20] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-19T18:05:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-19T21:59:34] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-19T06:29:12] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-19T07:28:13] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-19T07:28:20] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-19T18:00:01] bedroom_window | OperationalStatus = 0b000010",
    "[2026-06-19T18:00:30] bedroom_window | OperationalStatus = 0b000010",
    "[2026-06-19T18:00:30] bedroom_window | CurrentPositionLi

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

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

## Stage-1 Analysis
```json
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Bedroom motion sensor (occupancy_sensor) is malfunctioning or has incorrect sensitivity settings, failing to detect movement during the night hours.",
      "supported_by": [
        "[2026-06-19T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-19T00:30:00] bedroom_occupancy | OccupancySensing.Occupancy = 0"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "anomaly",
      "description": "Bedroom window covering (window_covering) motor/control unit is stuck or reporting inconsistent position states.",
      "supported_by": [
        "[2026-06-19T06:29:12] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
        "[2026-06-19T18:00:30] bedroom_window | CurrentPositionLiftPercent100ths = 5000",
        "[2026-06-19T21:59:29] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000"
      ],
      "contradicted_by": []
    },
    {
      "id": "H3",
      "type": "normal",
      "description": "Bedroom temperature sensor is functioning normally, as there are no reported anomalies in the temperature data stream for this room.",
      "supported_by": [],
      "contradicted_by": []
    }
  ],
  "most_concerning_signals": [
    "Continuous 'Occupancy = 0' reports from bedroom_occupancy at midnight despite potential human activity context inferred from other rooms.",
    "Discontinuous and potentially conflicting 'CurrentPositionLiftPercent100ths' values (0 -> 5000 -> 10000) for bedroom_window without corresponding operational status changes."
  ],
  "what_to_verify_in_raw_log": [
    "Check raw IR/RF timestamps for bedroom_occupancy to see if any movement events were logged but filtered