触发间隔不规律（不是周期性的），且频率较低（几分钟一次不是几十秒一次）

The bedroom occupancy sensor is functioning correctly, reporting 'Empty' during the night and detecting presence only when activity (lighting up, window opening) occurred in the morning.

Explanation: The raw log shows consistent 'Occupancy = 0' readings for the bedroom between 00:00 and 06:24, which aligns with the expected state of an empty room at night.

Explanation: At 06:24:00, the sensor correctly transitioned to 'Occupancy = 1', immediately followed by the light turning on at 06:24:06 and the window covering moving at 06:24:16, confirming the sensor accurately detected human presence.

Explanation: The sensor subsequently reported 'Occupancy = 0' again at 06:41:33 after the lights were turned off and no further activity was logged, demonstrating normal behavior without any signs of being stuck or malfunctioning.

[2026-06-09T06:24:00] bedroom_occupancy | OccupancySensing.Occupancy = 1

[2026-06-09T06:24:06] bedroom_light | OnOff.OnOff = True

## 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": 1123,
  "salient_event_count": 60,
  "focus_event_count": 113,
  "room_activity": {
    "kitchen": 22,
    "living_room": 37,
    "bedroom": 23,
    "bathroom": 19,
    "entrance": 12
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-09T07:26:23] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-09T07:26:31] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-09T18:17:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-09T21:55:40] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-09T06:24:16] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-09T07:26:23] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-09T07:26:31] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-09T18:17:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-09T21:55:32] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
    "[2026-06-09T21:55:40] front_door_l

## 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 occupancy sensor is stuck in 'Empty' state despite activity indicators or expected human presence patterns.",
      "supported_by": ["[2026-06-09T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0", "[2026-06-09T00:30:00] bedroom_occupancy | OccupancySensing.Occupancy = 0", "[2026-06-09T01:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0"],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "Bedroom window covering and contact sensors are functioning correctly, reflecting manual user control (closing/opening) and corresponding physical state changes.",
      "supported_by": ["[2026-06-09T06:24:16] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0", "[2026-06-09T21:55:40] front_door_lock | DoorLock.LockState = 1 (Correlates with window opening at 21:55)", "[2026-06-09T21:55:32] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000"],
      "contradicted_by": []
    }
  ],
  "most_concerning_signals": [
    "[2026-06-09T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0"
  ],
  "what_to_verify_in_raw_log": [
    "Check for any motion events in the bedroom between 2026-06-09T00:00:00 and 01:00:00 to rule out false negatives.",
    "Verify if the occupancy sensor battery level or calibration status changed during this period.",
    "Cross-reference with the bedroom light (<dimmable_light>) state to see if it triggered based on motion while occupancy reported as 0."
  ],
  "provisional_risk": "low"
}

## Focused Raw Log
[2026-06-09T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2277
[2026-06-09T00:00:00] living_room_occupancy | OccupancySensing


DF-04-FP: 门锁响应延迟但最终成功锁定

Entrance sensors are functioning correctly; the initial state inconsistency was resolved by subsequent contact sensor events confirming physical door movement.

Explanation: Initial log entry at 07:14:23 showed a manual lock operation followed immediately by a 'Locked' state (2), which appeared inconsistent with a user just leaving.

Explanation: However, raw logs reveal a 'front_door_contact' event at 07:14:25 reporting StateValue=False (open) and at 07:14:30 reporting StateValue=True (closed).

Explanation: This sequence confirms the door was physically opened after the manual lock attempt (likely to retrieve an item or adjust the handle) and then closed, causing the system to auto-lock successfully at 07:14:31. The sensors accurately tracked this physical interaction.

[2026-06-22T07:14:25] front_door_contact | BooleanState.StateValue = False

[2026-06-22T07:14:30] front_door_contact | BooleanState.StateValue = True

No immediate action required as sensors are verified operational.

Consider reviewing user manual for door lock handling procedures if confusion persists regarding the 'LockOperation' vs 'ContactSensor' timing.

```json
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Entrance area sensors (specifically the door lock) exhibit a state inconsistency where the device reports being locked while manual unlock operations are recorded, suggesting either sensor reporting failure or logic desynchronization.",
      "supported_by": [
        "[2026-06-22T07:14:23] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
        "[2026-06-22T07:14:23] front_door_lock | DoorLock.LockState = 2",
        "[2026-06-22T21:24:03] front_door_lock | DoorLock.LockState = 2"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "The entrance contact sensor and motion sensors are functioning within normal parameters based on available data points, showing no immediate false triggers or dead zones detected in the salient events.",
      "supported_by": [
        "Absence of suspicious 'contact_sensor' or 'occupancy_sensor' events for entrance in the provided log snippet.",
        "Consistent timestamping between lock operations and state changes in other entries."
      ],
      "contradicted_by": [
        "H1 suggests underlying system instability that could affect all entrance sensors."
      ]
    }
  ],
  "most_concerning_signals": [
    "[2026-06-22T07:14:23] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-22T07:14:23] front_door_lock | DoorLock.LockState = 2"
  ],
  "what_to_verify_in_raw_log": [
    "Check if any 'ContactSensor' events for 'entrance_contact' exist around 07:14:23 to verify if the door was physically closed/opened at the time of the reported conflict.",
    "Verify the definition of LockOperationType=1 (Is it Locking or Unlocking?) against LockState=2 (Is 2 Locked or Unlocked?) to confirm if this is a software mapping error or physical failure.",
    "Cross-reference the 'Auto' lock operation at 07:14:31 with the state history to see if the state reverted correctly after the manual intervention."
  ],
  "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 entrance 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。

## Layout
Layout: 一室一厅 (Studio/1BR)
- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>
- bedroom: 卧室温度传感器<temperature_sensor>, 卧室灯<dimmable_light>, 卧室窗帘<window_covering>, 卧室窗户传感器<contact_sensor>, 卧室运动传感器<occupancy_sensor>
- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>
- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>
- living_room: 客厅主灯<dimmable_light>, 客厅台灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅运动传感器<occupancy_sensor>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1115,
  "salient_event_count": 60,
  "focus_event_count": 110,
  "room_activity": {
    "kitchen": 18,
    "living_room": 36,
    "bedroom": 22,
    "bathroom": 19,
    "entrance": 15
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-22T07:14:23] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-22T07:14:31] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-22T18:22:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-22T22:11:50] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-22T06:41:17] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-22T07:14:23] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-22T07:14:31] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-22T18:22:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-22T21:24:03] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-22T21:24:08] front_door_lock | DoorLock.LockState = 1",

## 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
```json
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Entrance area sensors (specifically the door lock) exhibit a state inconsistency where the device reports being locked while manual unlock operations are recorded, suggesting either sensor reporting failure or logic desynchronization.",
      "supported_by": [
        "[2026-06-22T07:14:23] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
        "[2026-06-22T07:14:23] front_door_lock | DoorLock.LockState = 2",
        "[2026-06-22T21:24:03] front_door_lock | DoorLock.LockState = 2"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "The entrance contact sensor and motion sensors are functioning within normal parameters based on available data points, showing no immediate false triggers or dead zones detected in the salient events.",
      "supported_by": [
        "Absence of suspicious 'contact_sensor' or 'occupancy_sensor' events for entrance in the provided log snippet.",
        "Consistent timestamping between lock operations and state changes in other entries."
      ],
      "contradicted_by": [
        "H1 suggests underlying system instability that could affect all entrance sensors."
      ]
    }
  ],
  "most_concerning_signals": [
    "[2026-06-22T07:14:23] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-22T07:14:23] front_door_lock | DoorLock.LockState = 2"
  ],
  "what_to_verify_in_raw_log": [
    "Check if any 'ContactSensor' events for 'entrance_contact' exist around 07:14:23 to verify if the door was physically closed/opened at the time of the reported conflict.",
    "Verify the definition of LockOperationType=1 (


DF-04-FP: 门锁响应延迟但最终成功锁定

The entrance contact sensor is functioning correctly; all state changes align logically with manual lock operations and expected door closing cycles.

Explanation: Manual lock events (LockOperationType=1) consistently coincide with the lock state changing to '2' (locked), followed immediately by the contact sensor reporting 'False' (door open/ajar) for a brief moment before returning to 'True' (door closed).

Explanation: This pattern represents a standard mechanical sequence: user unlocks/locks while holding the door or during the act of locking, causing a transient opening signal that resolves once the door is secured.

Explanation: No evidence of sensor failure exists; the transition from 'False' back to 'True' confirms the sensor accurately detects the door's final closed position, and no contradictory states (e.g., locked but contact permanently False) are observed.

[2026-06-10T07:13:25] front_door_contact | BooleanState.StateValue = False

[2026-06-10T07:13:28] front_door_contact | BooleanState.StateValue = True

Continue routine monitoring; no intervention required.

Verify physical door hardware if intermittent sticking occurs in future logs.

Raw voltage or signal strength logs for the entrance contact sensor to check for hardware instability

Sequence of events immediately following each 'LockOperation' to confirm if the state update is delayed or erroneous

## 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: 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": 1121,
  "salient_event_count": 60,
  "focus_event_count": 109,
  "room_activity": {
    "kitchen": 19,
    "living_room": 34,
    "bedroom": 21,
    "bathroom": 20,
    "entrance": 15
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-10T07:13:23] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-10T07:13:29] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-10T18:13:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-10T22:14:35] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-10T06:27:14] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-10T07:13:23] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-10T07:13:29] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-10T15:24:03] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-10T15:24:08] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-10T18:13:00] front_door_lock | DoorLock.LockState = 2",

## 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 contact sensor (front_door_lock) exhibits intermittent state reporting or logic inconsistency, potentially failing to accurately reflect physical door status.",
      "supported_by": [
        "[2026-06-10T07:13:29] front_door_lock | DoorLock.LockState = 1",
        "[2026-06-10T15:24:08] front_door_lock | DoorLock.LockState = 1",
        "[2026-06-10T22:14:35] front_door_lock | DoorLock.LockState = 1"
      ],
      "contradicted_by": [
        "[2026-06-10T07:13:23] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
        "[2026-06-10T07:13:29] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)"
      ]
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "Door lock operations are functioning as intended with manual and automated cycles occurring at expected intervals.",
      "supported_by": [
        "Multiple sequential LockOperation events matching LockState transitions",
        "Standard time gaps between morning (07:13), afternoon (15:24), evening (18:13), and night (22:14) lock/unlock cycles"
      ],
      "contradicted_by": [
        "No explicit contradiction found in the provided snippet; however, H1 suggests a potential sensor lag or glitch that needs raw log verification."
      ]
    }
  ],
  "most_concerning_signals": [
    "Discrepancy between 'LockOperation' event timestamps and immediate 'LockState' updates",
    "Potential false positive/negative readings where state changes do not perfectly align with operation commands"
  ],
  "what_to_verify_in_raw_log": [
    "Timestamp precision of 'ContactSensor' readings vs. 'DoorLock' state changes to rule out clock skew",


DF-02-FP: 夏季午后持续升温（正常日照效应）

温度上升后在午后到达峰值并回落，符合日间正弦曲线；而真正的漂移是不回落的单向偏移

Living room occupancy sensor readings are consistent with the absence of detected human activity in that specific zone during the monitored period; no system malfunction or security breach is indicated.

Explanation: The raw log shows continuous '0' (empty) readings for living_room_occupancy from 00:00 to 06:30, indicating no motion was detected in that zone.

Explanation: Activity was successfully detected and triggered events (lights/windows) in other zones (bedroom, bathroom), proving the occupancy sensors themselves are functional and not globally stuck.

Explanation: The lack of any state changes or event triggers associated with living_room devices confirms the sensor's 'empty' report matches the physical reality of an unoccupied space.

"room_activity": { ... "living_room": 36, ... }

所有传感器均在午夜零点统一复位为'0'，这可能是正常的每日重置周期，而非故障。

对比同一时间段内 bedroom 和 kitchen 的 occupancy 传感器读数变化趋势，排除全局性数据丢失问题。

所有传感器均在午夜零点统一复位为'0'，这可能是正常的每日重置周期，而非故障。

## 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": 1131,
  "salient_event_count": 60,
  "focus_event_count": 111,
  "room_activity": {
    "kitchen": 20,
    "living_room": 36,
    "bedroom": 23,
    "bathroom": 20,
    "entrance": 12
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-09T07:14:23] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-09T07:14:30] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-09T18:13:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-09T22:02:33] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-09T06:19:14] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-09T07:14:23] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-09T07:14:30] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-09T18:13:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-09T22:02:23] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
    "[2026-06-09T22:02:33] 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": "客厅运动传感器 (living_room_occupancy) 在长达数小时的时间段内持续报告无人员活动，而家庭其他区域（如卧室、厨房）存在明确的活动记录，表明传感器可能处于故障状态或环境设置不当。",
      "supported_by": ["[2026-06-09T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0", "[2026-06-09T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0", "[2026-06-09T01:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0", "[2026-06-09T01:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0"],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "anomaly",
      "description": "尽管客厅报告显示无人，但系统日志中显示 living_room 区域有 36 次活动记录 (room_activity)，这与传感器持续的'0'状态相矛盾，暗示传感器未能检测到实际发生的事件。",
      "supported_by": ["\"room_activity\": { ... \"living_room\": 36, ... }"],
      "contradicted_by": ["living_room_occupancy 传感器在多个时间点持续返回 Occupancy = 0"]
    },
    {
      "id": "H3",
      "type": "normal",
      "description": "所有传感器均在午夜零点统一复位为'0'，这可能是正常的每日重置周期，而非故障。",
      "supported_by": ["[2026-06-09T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0", "[2026-06-09T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0", "[2026-06-09T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0"],
      "contradicted_by": ["后续半小时至一个小时内，其他房间也有类似重置行为，且 living_room 在此后长时间未更新任何非零状态，而其他房间随后有活动记录"]
    }
  ],
  "most_concerning_signals": [
    "living_room_occupancy 传感器在 T00:00 至 T01:30 期间连续多次报告空房状态，与 room_activity 统计中的 36 次事件严重不符。",
    "缺乏针对 living_room 的具体事件时间戳，无法确认那 36 次活动是否被该传感器捕获。"
  ],
  "what_to_verify_in_raw_log": [
    "查询 raw log 中 00:00 至 01:30 之间是否有触发 living_room 相关设备（如灯、空调、窗帘）开关或状态变更的事件，以验证是否有人活动但未上报。",
    "检查 living_room 运动传感器的配置参数（如灵敏度、遮挡检测模式），确认是否存在物理遮挡或环境干扰导致漏报。",
    "对比同一时间段内 bedroom 和 kitchen 的 occup


DF-01-FP: 空调恒温控制导致温度稳定

有微小波动（±0.2°C），不是完全固定值；且空调处于开启状态

The living room occupancy sensor is functioning correctly, reporting an empty state consistent with the confirmed departure of residents and lack of activity in other zones.

Explanation: All living_room_occupancy readings between 00:00 and 08:30 consistently show '0' (empty).

Explanation: Contextual evidence confirms resident departure at 23:15 (door unlock) and re-entry only occurs later at 08:18 in the bedroom.

Explanation: No temperature spikes or light activations occurred in the living room during the night period, supporting the 'empty' status rather than a sensor failure.

[2026-06-14T08:18:00] bedroom_occupancy | OccupancySensing.Occupancy = 1

Check for any motion events in living_room between 23:15 and 02:00 that might not have triggered the occupancy update.

Verify if other sensors (e.g., temperature, lights) show activity or state changes corresponding to human presence.

Inspect battery voltage or last calibration timestamp for the living_room_occupancy device to rule out power issues.

Compare raw PIR signal logs vs. processed occupancy state to detect filtering errors.

## 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": 1349,
  "salient_event_count": 60,
  "focus_event_count": 108,
  "room_activity": {
    "kitchen": 21,
    "living_room": 40,
    "bedroom": 26,
    "bathroom": 18,
    "entrance": 3
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-14T23:15:22] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-14T08:18:15] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-14T10:01:14] living_room_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-14T23:15:15] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
    "[2026-06-14T23:15:22] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-14T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-14T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-14T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-14T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-14T00:30:00] bedroom_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 stuck or malfunctioning, reporting 'empty' (0) for the entire monitored period despite potential activity context.",
      "supported_by": [
        "[2026-06-14T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-14T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-14T01:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-14T01:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-14T02:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "Living room occupancy sensor is functioning correctly, and the room was genuinely empty during the night hours (00:00 to 02:00).",
      "supported_by": [
        "Consistent '0' readings across all time intervals suggest a stable state rather than erratic sensor failure.",
        "Correlation with bedroom_window opening at 23:15:22 suggests residents may have vacated the home before these timestamps."
      ],
      "contradicted_by": []
    }
  ],
  "most_concerning_signals": [
    "[2026-06-14T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-14T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-14T01:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-14T01:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-14T02:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0"
  ],
  "what_to_verify_in_raw_log": [
    "Check for any motion events in living_r


DF-01-FP: 空调恒温控制导致温度稳定

有微小波动（±0.2°C），不是完全固定值；且空调处于开启状态

The living_room occupancy sensor is malfunctioning by reporting a persistent '0' (empty) state despite clear evidence of human activity and device usage in the same area.

Explanation: Living room temperature sensors show continuous heating activity from 00:00 to 06:15, indicating the HVAC system is actively conditioning the space, implying presence or at least system engagement.

Explanation: At 06:28:04, the bathroom occupancy sensor detects presence ('1') and the bathroom light turns on; given the proximity and typical home layout, this strongly suggests movement through or near the living room during the period when the living room sensor reported '0'.

Explanation: Later at 21:59:05, the living_room_occupancy sensor finally reports '1', confirming that humans were indeed present in the living room earlier in the day, contradicting the long duration of the '0' reading.

[2026-06-09T06:28:04] bathroom_occupancy | OccupancySensing.Occupancy = 1 && bathroom_light | OnOff.OnOff = True

[2026-06-09T21:59:05] living_room_occupancy | OccupancySensing.Occupancy = 1

Inspect the living_room occupancy sensor battery and physical connections for failure.

Re-calibrate or replace the living_room occupancy sensor immediately.

High frequency of focus events in living_room (36 vs 60 total salient events) despite the sensor consistently reading 0, creating a discrepancy between system attention and reported state.

Check for battery voltage levels or signal strength (RSSI) of the living_room_occupancy sensor around the 00:00-02:00 timestamp range to rule out power issues causing false zeros.

Verify if there were any 'MotionDetected' or 'PersonFound' events logged simultaneously with the 'Occupancy=0' updates; if motion was detected but not converted to an occupancy update, the logic pipeline is broken.

Cross-reference camera feeds (if available) or other room sensors (e.g., bedroom lights turning on at 07:29) to confirm actual human presence in the home during the period where living_room reports 0 occupancy.

## 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": 111,
  "room_activity": {
    "kitchen": 20,
    "living_room": 36,
    "bedroom": 24,
    "bathroom": 19,
    "entrance": 12
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-09T07:29:14] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-09T07:29:21] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-09T18:01:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-09T21:58:42] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-09T06:15:11] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-09T07:29:14] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-09T07:29:21] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-09T18:01:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-09T21:58:35] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
    "[2026-06-09T21:58:42] 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": "The living_room occupancy sensor is reporting a persistent 'empty' state (0) throughout the entire monitoring period, including times when other rooms show activity or door locks are manipulated, suggesting potential sensor failure or misconfiguration.",
      "supported_by": [
        "[2026-06-09T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-09T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-09T01:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-09T01:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "The house was genuinely empty during the late night/early morning hours (00:00 - 01:30), and the sensor is functioning correctly by accurately reporting no motion.",
      "supported_by": [],
      "contradicted_by": [
        "Front door lock manipulation events at 07:29 and 18:01 suggest human presence/activity earlier in the day which might imply the house wasn't empty for the full duration if the timeline is continuous, though strictly within the provided logs, the 00:00-01:30 window could be a valid empty period."
      ]
    }
  ],
  "most_concerning_signals": [
    "Persistent zero occupancy reading across multiple timestamps (00:00, 00:30, 01:00, 01:30) without any variation, which often indicates a stuck sensor state rather than dynamic absence of people.",
    "High frequency of focus events in living_room (36 vs 60 total salient events) despite the sensor consistently reading 0, creating a discrepancy between system attention and reported state


DF-02-FP: 夏季午后持续升温（正常日照效应）

The living room occupancy sensor is malfunctioning and stuck in 'empty' mode while other sensors correctly detect human presence and activity in adjacent rooms.

Explanation: Living room occupancy sensor consistently reports 0 from midnight until 18:25, despite temperature sensors showing significant heating activity (indicating HVAC usage or human presence).

Explanation: Adjacent sensors (bedroom and bathroom) correctly transition to 'Occupancy=1' at 06:22 and 06:34 respectively, proving the system's occupancy logic works when people are present.

Explanation: The discrepancy between the living room sensor reporting 0 while the bedroom/bathroom report 1 during active hours confirms a specific hardware or logic failure in the living room unit rather than an empty house scenario.

[2026-06-29T06:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0

[2026-06-29T06:30:00] bedroom_occupancy | OccupancySensing.Occupancy = 1

[2026-06-29T06:34:07] bathroom_occupancy | OccupancySensing.Occupancy = 1

Check power supply and battery status of the living room occupancy sensor.

Clean the sensor lens if obstructed by dust or cobwebs.

Calibrate or replace the living room occupancy sensor if cleaning and power checks fail.

[2026-06-29T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0

[2026-06-29T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0

[2026-06-29T01:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0

[2026-06-29T01:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0

Raw packet timestamps for 'living_room_occupancy' events between 07:00 and 22:00 to see if packets exist but contain value 0, or if packets are entirely missing.

Correlation between 'room_activity' increments and specific 'occupancy=1' events for the living room.

Power status or heartbeat intervals for the 'living_room_occupancy' device ID to rule out offline status.

Events for 'kitchen' and 'bedroom' occupancy sensors during the 18:25-22:00 window to confirm if they were functioning correctly while living_room failed.

## 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": 1127,
  "salient_event_count": 60,
  "focus_event_count": 111,
  "room_activity": {
    "kitchen": 21,
    "living_room": 37,
    "bedroom": 22,
    "bathroom": 20,
    "entrance": 11
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-29T07:20:19] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-29T07:20:23] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-29T18:25:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-29T22:04:48] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-29T06:22:15] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-29T07:20:19] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-29T07:20:23] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-29T18:25:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-29T22:04:38] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
    "[2026-06-29T22:04:48] 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 non-functional or permanently reporting 'empty' due to a power/logic failure, as it fails to detect presence during the day (07:00-22:00) when other rooms show activity.",
      "supported_by": ["Multiple consecutive timestamped events from 00:00 to 01:30 showing living_room_occupancy = 0 despite high room_activity count (37) in living_room and kitchen activity at 18:25.", "Absence of any positive occupancy event ('Occupancy=1') for the living room throughout the entire log period, while bedroom and bathroom also report 0 (likely coincidental timing or similar failure mode)."],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "The house was completely empty during the monitoring period (e.g., night time or away mode), and all sensors correctly reported zero occupancy.",
      "supported_by": ["front_door_lock events indicate the door was locked manually at 07:20 and 18:25, suggesting residents might be away or securing the home.", "All three occupancy sensors (living_room, bedroom, bathroom) consistently report 0.", "No temperature patterns are recorded, which could imply a lack of HVAC interaction typical of an empty house."],
      "contradicted_by": ["High room_activity counts (37 in living_room, 21 in kitchen) contradict a scenario where no one is present. Activity counters usually increment on motion detection, implying the system *thinks* someone moved there, yet the occupancy sensor says 'no one'.", "Kitchen activity at 18:25 suggests cooking occurred; if people cooked, they likely occupied the adjacent living room."]
    }
  ],
  "most_concerning_signals": [
    "[2026-06-29T00:00:00] living


DF-04-FP: 门锁响应延迟但最终成功锁定

The front door lock exhibits high-frequency state oscillation (chattering) between locked and unlocked states within seconds, indicating a mechanical or sensor failure rather than normal user behavior.

Explanation: Analysis of raw logs reveals a rapid cycle at 07:15:18 where the lock was manually locked, but by 07:15:23 (5 seconds later) it was automatically unlocked, contradicting standard dwell times.

Explanation: Timestamps show repeated identical short-duration cycles (approx 5 seconds) at both 07:15 and 17:51, which is characteristic of sensor bounce or firmware instability, not human interaction.

Explanation: The 'front_door_contact' sensor state flips rapidly (False then True) immediately following the manual lock command, suggesting the magnetic reed switch is failing to maintain a stable 'closed' position required to keep the lock engaged.

[2026-06-12T07:15:18] ... LockOperationType=1, OperationSource=Manual

[2026-06-12T07:15:23] ... LockOperationType=0, OperationSource=Auto

[2026-06-12T07:15:22] front_door_contact | BooleanState.StateValue = True

Physically inspect the front door strike plate and latch for obstructions or misalignment causing contact bounce.

Clean the magnetic reed switch and its mounting surface to remove debris interfering with the magnetic field.

If cleaning fails, replace the front door lock module or the specific contact sensor assembly.

Rapid alternation of DoorLock.LockState between 2 (Locked) and 1 (Unlocked) within 5-second intervals (e.g., 07:15:18 vs 07:15:23).

Correlation of these rapid states with mixed OperationSources (Manual followed immediately by Auto) which may indicate a sensor reading conflict or logic loop.

High frequency of focus events (108 total, 15 in entrance) relative to room activity count, indicating potential noise generation.

Verify the raw millisecond-level timestamp of the magnetic reed switch closure/opening vs. the motor driver command execution to distinguish between physical bounce and digital glitch.

Check battery voltage logs for the front_door_lock device during the oscillation periods to rule out low-power induced instability.

Cross-reference the 'OperationSource' field definition to confirm if 'Auto' can legitimately trigger an unlock immediately after a 'Manual' lock in less than 5 seconds, or if this indicates a stuck relay state.

Inspect the 'front_door_contact' (if separate from lock) for coincident state flips that might explain the lock's erratic behavior via interlock logic.

## 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: 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": 1117,
  "salient_event_count": 60,
  "focus_event_count": 108,
  "room_activity": {
    "kitchen": 19,
    "living_room": 34,
    "bedroom": 22,
    "bathroom": 18,
    "entrance": 15
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-12T07:15:18] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-12T07:15:23] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-12T18:24:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-12T22:09:38] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-12T06:42:16] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-12T07:15:18] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-12T07:15:23] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-12T17:51:03] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-12T17:51:08] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-12T18:24:00] front_door_lock | DoorLock.LockState = 2",

## 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": "The entrance area (specifically the front door lock and contact sensor) exhibits a high-frequency state oscillation pattern, suggesting either mechanical failure of the latch, interference from magnetic fields, or firmware instability causing 'chattering'.",
      "supported_by": [
        "[2026-06-12T07:15:18] ... LockState = 2",
        "[2026-06-12T07:15:23] ... LockState = 1",
        "[2026-06-12T17:51:03] ... LockState = 2",
        "[2026-06-12T17:51:08] ... LockState = 1"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "The observed state changes are valid operational events corresponding to manual user actions and automatic locking sequences.",
      "supported_by": [
        "[2026-06-12T07:15:18] ... OperationSource=Manual",
        "[2026-06-12T07:15:23] ... OperationSource=Auto",
        "[2026-06-12T18:24:00] ... OperationSource=Manual",
        "[2026-06-12T22:09:38] ... OperationSource=Auto"
      ],
      "contradicted_by": [
        "The time delta between state change and operation source mismatch (e.g., State 2->1 at 07:15:23 with Auto source, but no explicit Auto event logged immediately prior in the snippet for that specific transition, though implied by sequence; however, the tight 5-second interval between Manual Lock (OpType 1) and Auto Unlock (OpType 0) without intermediate dwell time is suspicious for a single interaction.",
        "The repetition of identical short-duration cycles (approx 5 seconds) suggests automated testing or rapid bouncing rather than natural human behavior."
      ]
    }
  ],
  "most_concerning_signals": [
    "Rapid alternation of DoorLock.LockState between 2 (Locked) an


触发间隔不规律（不是周期性的），且频率较低（几分钟一次不是几十秒一次）

Bedroom occupancy sensor is functioning correctly; the reported 'empty' status during midnight aligns with the absence of activity triggers, light usage, or window operations in that specific time window.

Explanation: The raw log confirms a continuous state of Occupancy = 0 for the bedroom from 00:00 to 06:23.

Explanation: No contradictory evidence (e.g., motion triggers, lights turning on, or curtains moving) exists in the log between 00:00 and 06:23 to suggest human presence while the sensor reported empty.

Explanation: The sensor correctly detected occupancy only after activity began at 06:23 (lights on, windows opened), indicating normal operation rather than a malfunction or blockage.

[2026-06-01T06:23:00] bedroom_occupancy | OccupancySensing.Occupancy = 1

```json
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Bedroom occupancy sensor is malfunctioning or blocked, reporting 'empty' (0) continuously despite potential room activity or context clues.",
      "supported_by": [
        "[2026-06-01T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-01T00:30:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-01T01:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "Bedroom sensors are functioning correctly; the room was indeed unoccupied during the midnight monitoring window.",
      "supported_by": [],
      "contradicted_by": [
        "Contextual inconsistency: H1 suggests a fault due to lack of state change, but without external confirmation of presence, a static '0' reading could be valid if no one entered."
      ]
    }
  ],
  "most_concerning_signals": [
    "bedroom_occupancy consistently reporting 0 across multiple timestamps with no transitions observed in the provided snippet.",
    "Room activity counts show 25 events for bedroom, which may imply human interaction that an empty occupancy sensor should not reflect if the user was present."
  ],
  "what_to_verify_in_raw_log": [
    "Check raw IR/RFID logs near timestamp 2026-06-01T00:00:00 - 01:30:00 to see if any motion triggers were generated but filtered out.",
    "Verify if the bedroom door lock or contact sensor triggered any entry events coinciding with the reported occupancy status.",
    "Cross-reference the bedroom curtain/window covering status changes (seen at 06:23 and 21:47) to determine if someone was interacting with the room environment while the sensor reported empty."
  ],
  "provisional_risk": "low"
}
```

## 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": 109,
  "room_activity": {
    "kitchen": 20,
    "living_room": 34,
    "bedroom": 25,
    "bathroom": 18,
    "entrance": 12
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-01T07:27:10] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-01T07:27:21] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-01T18:07:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-01T21:47:48] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-01T06:23:05] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-01T07:27:10] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-01T07:27:21] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-01T18:07:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-01T21:47:37] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
    "[2026-06-01T21:47:48] front_door_l

## 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 occupancy sensor is malfunctioning or blocked, reporting 'empty' (0) continuously despite potential room activity or context clues.",
      "supported_by": [
        "[2026-06-01T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-01T00:30:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-01T01:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "Bedroom sensors are functioning correctly; the room was indeed unoccupied during the midnight monitoring window.",
      "supported_by": [],
      "contradicted_by": [
        "Contextual inconsistency: H1 suggests a fault due to lack of state change, but without external confirmation of presence, a static '0' reading could be valid if no one entered."
      ]
    }
  ],
  "most_concerning_signals": [
    "bedroom_occupancy consistently reporting 0 across multiple timestamps with no transitions observed in the provided snippet.",
    "Room activity counts show 25 events for bedroom, which may imply human interaction that an empty occupancy sensor should not reflect if the user was present."
  ],
  "what_to_verify_in_raw_log": [
    "Check raw IR/RFID logs near timestamp 2026-06-01T00:00:00 - 01:30:00 to see if any motion triggers were generated but filtered out.",
    "Verify if the bedroom door lock or contact sensor triggered any entry events coinciding with the reported occupancy status.",
    "Cross-reference the bedroom curtain/window covering status changes (seen at 06:23 and 21:47) to determine if someone was interacting with the room environment while


DF-06-FP: 窗帘正常移动但速度慢

The second_bedroom occupancy sensor is functioning correctly as the room was unoccupied during the entire monitoring period.

Explanation: Raw logs confirm consistent 'Occupancy = 0' readings for second_bedroom between midnight and early morning.

Explanation: Contextual evidence shows window coverings were operated at 19:33 (daytime/evening), implying human activity occurred earlier.

Explanation: The subsequent continuous zero-occupancy state aligns with a normal scenario where the user left the room and did not return until the next day (evidenced by door lock events later).

[2026-06-14T19:33:00] second_bedroom_window | WindowCovering.OperationalStatus = 0b000010

[2026-06-14T19:33:30] second_bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000

[2026-06-14T19:33:30] second_bedroom_window | WindowCovering.OperationalStatus = 0b000000

[2026-06-14T23:04:16] front_door_lock | DoorLock.LockState = 1

## 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_bedroom 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。

## Layout
Layout: 两室一厅 (2BR)
- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>
- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>
- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>
- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>
- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>
- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>
- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1577,
  "salient_event_count": 60,
  "focus_event_count": 88,
  "room_activity": {
    "kitchen": 11,
    "living_room": 26,
    "master_bedroom": 11,
    "second_bedroom": 17,
    "bathroom": 10,
    "entrance": 13
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-14T23:04:16] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-14T09:51:09] living_room_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-14T19:33:01] second_bedroom_window | WindowCovering.OperationalStatus = 0b000010",
    "[2026-06-14T19:33:10] second_bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 5500",
    "[2026-06-14T19:33:20] second_bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 7000",
    "[2026-06-14T19:33:30] second_bedroom_window | WindowCovering.

## 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_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": "The second_bedroom occupancy sensor is likely malfunctioning (stuck at 'Empty') despite room activity events.",
      "supported_by": ["second_bedroom has 17 recorded events in room_activity, indicating device interaction or presence was detected by the system logic elsewhere"],
      "contradicted_by": ["suspicious_signals shows second_bedroom_occupancy reporting Occupancy = 0 at multiple timestamps (midnight, 00:30, 01:00)"]
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "The window covering in second_bedroom operated normally between 19:33 and 19:33:30.",
      "supported_by": ["OperationalStatus changed from 0b000010 to 0b000000 (likely Open/Closed state change) while CurrentPositionLiftPercent100ths increased linearly from 5500 to 10000 (full open/close cycle)"],
      "contradicted_by": []
    }
  ],
  "most_concerning_signals": [
    "[2026-06-14T00:00:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-14T00:30:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0"
  ],
  "what_to_verify_in_raw_log": [
    "Check raw motion detection packets for 'second_bedroom_occupancy' around 19:33 and subsequent hours to see if raw IR/Microwave pulses were received but not reported as Occupancy=1.",
    "Verify if the 17 'events' in room_activity for second_bedroom correspond to specific device commands that should have triggered an occupancy update.",
    "Cross-reference with power consumption logs for the bedroom to confirm if devices were active during the times occupancy was reported as 0."
  ],
  "provisional_risk": "medium"
}

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


DF-02-FP: 夏季午后持续升温（正常日照效应）

The living room occupancy sensor is functioning correctly; the house was confirmed empty at the time of the reported 'empty' state (00:00-23:11), and occupants only returned after midnight.

Explanation: Stage 1 hypothesis H2 (normal operation) is supported by raw logs showing Occupancy=0 for the entire period from 00:00 to 23:11.

Explanation: Crucially, the raw log shows bedroom occupancy became 1 at 23:11:14, followed immediately by window closing (23:11:19) and door locking (23:11:22).

Explanation: This sequence confirms that when the front door was locked and the system registered the home as secured (and living room empty), residents were actually inside the bedrooms, validating the sensor's '0' reading rather than a false negative.

[2026-06-13T23:11:14] bedroom_occupancy | OccupancySensing.Occupancy = 1

Cross-reference with other room activity logs (bedroom, kitchen) to see if the system registered movement in adjacent areas during the same timeframe.

## 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": 1347,
  "salient_event_count": 60,
  "focus_event_count": 107,
  "room_activity": {
    "kitchen": 20,
    "living_room": 39,
    "bedroom": 25,
    "bathroom": 20,
    "entrance": 3
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-13T23:11:22] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-13T08:39:13] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-13T10:00:14] living_room_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-13T23:11:19] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
    "[2026-06-13T23:11:22] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-13T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-13T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-13T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-13T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-13T00:30:00] bedroom_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 reporting false negatives (empty state) during periods when the home is occupied (e.g., after door unlock and window closing events).",
      "supported_by": ["[2026-06-13T23:11:22] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)", "[2026-06-13T23:11:22] front_door_lock | DoorLock.LockState = 1", "[2026-06-13T23:11:19] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000"],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "All living room occupancy sensors are functioning correctly because the house was empty at midnight.",
      "supported_by": ["[2026-06-13T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0", "[2026-06-13T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0"],
      "contradicted_by": ["[2026-06-13T23:11:22] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)", "[2026-06-13T23:11:19] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000"]
    }
  ],
  "most_concerning_signals": [
    "[2026-06-13T23:11:22] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-13T23:11:19] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000"
  ],
  "what_to_verify_in_raw_log": [
    "Check raw motion detection flags for 'living_room_occupancy' between 2026-06-13T23:10:00 and 2026-06-13T23:15:00 to confirm if human presence was detected despite the 'Occupancy = 0' report.",
    "Verify battery voltage or signal strength metrics for the living_room_motion_sensor around 23:11.",
    "Cross-reference with other


触发间隔不规律（不是周期性的），且频率较低（几分钟一次不是几十秒一次）

The second_bedroom occupancy sensor is malfunctioning due to a complete data blackout (silence) while other sensors in the same house report status at regular intervals.

Explanation: All monitored occupancy sensors (living_room, master_bedroom, bathroom, entrance) successfully transmit 'Occupancy = 0' state updates every 30 minutes throughout the night shift (00:00 to 05:00).

Explanation: In contrast, the second_bedroom_occupancy sensor fails to send any state update during this entire period, despite the system logging entries for all other devices at identical timestamps.

Explanation: This discrepancy indicates a hardware failure, communication drop, or power loss specific to the second_bedroom sensor rather than a normal vacancy state, as the network and scheduler are clearly functioning.

[2026-06-10T00:30:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0

Inspect the power supply and battery status of the second_bedroom motion sensor immediately.

Replace the second_bedroom sensor if hardware failure is confirmed after checking connections.

[2026-06-10T18:04:00] front_door_lock | DoorLock.LockState = 2

[2026-06-10T21:56:46] front_door_lock | DoorLock.LockState = 1

Check the raw binary or low-level text logs for 'second_bedroom_occupancy' timestamps between 00:00:00 and 01:00:00 to confirm if packets were dropped.

Verify the 'last_seen' timestamp attribute for the second_bedroom_occupancy device ID in the system metadata.

Cross-reference with power supply logs for the second_bedroom circuit to rule out power loss affecting only that zone's sensors.

Check if the second_bedroom motion sensor has ever sent a 'motion_detected' event during this period to differentiate between a stuck 'empty' state vs. no transmission at all.

## 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_bedroom 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。

## Layout
Layout: 两室一厅 (2BR)
- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>
- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>
- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>
- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>
- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>
- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>
- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1830,
  "salient_event_count": 60,
  "focus_event_count": 90,
  "room_activity": {
    "kitchen": 11,
    "living_room": 21,
    "master_bedroom": 11,
    "second_bedroom": 11,
    "bathroom": 12,
    "entrance": 24
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-10T07:10:21] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-10T07:10:30] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-10T18:04:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-10T21:56:46] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-10T07:10:21] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-10T07:10:30] front_door_lock | DoorLock.LockState = 1",

## 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_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": "The second_bedroom occupancy sensor is non-functional due to a complete data blackout (silence) during the monitoring period, despite activity occurring in other rooms.",
      "supported_by": ["Evidence shows explicit OccupancySensing events for living_room, master_bedroom, bathroom, and entrance at 00:00:00, 00:30:00, and 01:00:00, but zero events are recorded for second_bedroom_occupancy in the provided log snippet."],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "The second_bedroom sensor is working normally because the room was completely empty throughout the entire logging window.",
      "supported_by": ["Room_activity count for second_bedroom is 11, which could represent background noise or periodic heartbeat checks rather than human presence; however, this contradicts H1 given the silence compared to other rooms reporting 0 occupancy explicitly."],
      "contradicted_by": ["Absence of any timestamped state change or heartbeat from second_bedroom_occupancy, while other sensors actively report 'Occupancy = 0' states at regular intervals."],
      "notes": "Given the explicit 'Occupancy = 0' logs for other rooms, the total absence of logs for second_bedroom strongly suggests sensor failure rather than mere vacancy."
    }
  ],
  "most_concerning_signals": [
    "[2026-06-10T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-10T00:00:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-10T00:00:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0"
  ],
  "what_to_verify_in_raw_log": [
    "Check the raw binary or low-level text logs for 'second_bedroom_oc


DF-05-FP: 烟雾报警器正常自检

有完整的自检流程（TestInProgress=true → SelfTestComplete → TestInProgress=false），不是HardwareFault

The kitchen temperature sensor exhibits a severe drift error where the reported value (22°C scaled by 10) is consistently ~64°C higher than the living room baseline, indicating a calibration failure or hardware malfunction.

Explanation: Step 1: Analyze raw temperature logs; the 'kitchen_temp_sensor' reports values starting at 2268 and rising to 2445, while the 'living_room_temp_sensor' reports values in the 2267-2436 range.

Explanation: Step 2: Identify the scaling convention used in the logs; comparing the two sensors reveals that the kitchen reading is approximately 10x the expected Celsius value (e.g., 2268 implies 22.68°C, whereas the living room 2267 implies 22.67°C), suggesting the sensor is outputting millidegrees or has a unit conversion bug instead of reporting degrees directly.

Explanation: Step 3: Conclude the anomaly type; despite the sensor transmitting data regularly (heartbeat is functional), the magnitude of the error (~64°C offset) constitutes a critical sensor drift or calibration malfunction that would prevent accurate fire detection or environmental monitoring.

[2026-06-06T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2268 vs [2026-06-06T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2267

[2026-06-06T05:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2445 vs [2026-06-06T05:05:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2436

Immediately flag the kitchen temperature sensor for recalibration or replacement.

Verify physical sensor installation and wiring to rule out external interference causing signal distortion.

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

## 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: 两室一厅 (2BR)
- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>
- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>
- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>
- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>
- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>
- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>
- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1397,
  "salient_event_count": 60,
  "focus_event_count": 84,
  "room_activity": {
    "kitchen": 17,
    "living_room": 23,
    "master_bedroom": 11,
    "second_bedroom": 11,
    "bathroom": 11,
    "entrance": 11
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-06T18:45:00] kitchen_smoke_alarm | SmokeCoAlarm.TestInProgress = True",
    "[2026-06-06T18:45:00] kitchen_smoke_alarm | SmokeCoAlarm.ExpressedState = 4",
    "[2026-06-06T18:45:30] kitchen_smoke_alarm | SmokeCoAlarm.TestInProgress = False",
    "[2026-06-06T18:45:30] kitchen_smoke_alarm | SmokeCoAlarm.ExpressedState = 0",
    "[2026-06-06T18:45:30] kitchen_smoke_alarm | Event: SelfTestComplete()",
    "[2026-06-06T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-06T00:00:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-0

## 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 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": "normal",
      "description": "Kitchen smoke alarm is functioning correctly as it successfully completed a scheduled self-test cycle.",
      "supported_by": ["SmokeCoAlarm.TestInProgress = True followed by False", "Event: SelfTestComplete()"],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "anomaly",
      "description": "The kitchen area shows no activity events in the provided evidence packet, which may indicate a sensor failure or total lack of user interaction during the observation window.",
      "supported_by": ["room_activity.kitchen = 0 (implied by absence in list)", "No temperature/contact/occupancy logs for kitchen"],
      "contradicted_by": ["Layout defines specific sensors that should generate background telemetry if active"]
    }
  ],
  "most_concerning_signals": [
    "Absence of any kitchen-specific sensor logs (temperature, contact, motion) despite the query focusing on 'kitchen' area functionality."
  ],
  "what_to_verify_in_raw_log": [
    "Check for periodic heartbeat messages from kitchen_temperature_sensor and kitchen_window_sensor to confirm they are online but silent.",
    "Verify if the silence in room_activity.kitchen is due to a logging buffer timeout or actual device disconnection.",
    "Cross-reference with power consumption logs for the kitchen circuit to see if devices are receiving power."
  ],
  "provisional_risk": "low"
}

## Focused Raw Log
[2026-06-06T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2268
[2026-06-06T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0
[2026-06-06T00:00:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 0
[2026-06-06T00:00:00] second_bedroom_occupancy | OccupancySensing.Occupancy


触发间隔不规律（不是周期性的），且频率较低（几分钟一次不是几十秒一次）

The bedroom occupancy sensor is functioning correctly; the prolonged 'Empty' state during the night was due to the room being unoccupied (consistent with a sleeping schedule), and the sensor accurately detected human presence upon waking at 06:41.

Explanation: Analysis of raw logs shows the bedroom occupancy sensor reported '0' (Empty) from 00:00 until 06:37, which aligns perfectly with a standard nighttime sleep period where no motion occurs.

Explanation: At 2026-06-22T06:41:00, the sensor immediately transitioned to '1' (Occupied) followed by the activation of the bedroom light and window coverings, confirming the device successfully detected the user's morning routine.

Explanation: Contrast with other sensors: The bathroom sensor triggered at 06:32 before the bedroom, indicating movement in the house, while the kitchen temperature rose steadily, proving environmental changes were occurring but simply not within the empty bedroom.

Explanation: No communication errors, battery warnings, or static readings indicative of a stuck sensor were found in the provided log excerpt.

[2026-06-22T06:41:00] bedroom_occupancy | OccupancySensing.Occupancy = 1

[2026-06-22T06:41:06] bedroom_light | OnOff.OnOff = True

Continue monitoring; no action required as the system is operating as expected.

Verify that the delayed detection between 06:37 and 06:41 is within acceptable latency thresholds for this specific PIR sensor model if strict real-time response is required.

```json
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Bedroom occupancy sensor is reporting a persistent 'Empty' (0) state throughout the night and early morning, contradicting expected human presence or activity patterns for a residential bedroom.",
      "supported_by": [
        "[2026-06-22T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-22T00:30:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-22T01:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "The window covering in the bedroom was manually opened and closed at different times of the day, indicating the device is responsive to user interaction.",
      "supported_by": [
        "[2026-06-22T06:41:11] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
        "[2026-06-22T22:14:24] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000"
      ],
      "contradicted_by": []
    }
  ],
  "most_concerning_signals": [
    "[2026-06-22T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-22T00:30:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-22T01:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0"
  ],
  "what_to_verify_in_raw_log": [
    "Check raw packet timestamps vs. local time zone offset to ensure events aren't misaligned due to clock skew.",
    "Search for any 'OccupancyTransition' or 'WakeUp' events around 06:00 or 07:00 to see if the sensor ever detected motion.",
    "Verify if there are any communication errors or battery low warnings associated with the bedroom_occupancy node ID.",
    "Cross-reference the bedroom temperature sensor readings during these times to see if they remained static (indicating no environmental change from presence)."
  ],
  "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": 1276,
  "salient_event_count": 60,
  "focus_event_count": 107,
  "room_activity": {
    "kitchen": 19,
    "living_room": 33,
    "bedroom": 24,
    "bathroom": 20,
    "entrance": 11
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-22T07:26:16] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-22T07:26:27] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-22T18:21:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-22T22:14:30] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-22T06:41:11] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-22T07:26:16] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-22T07:26:27] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-22T18:21:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-22T22:14:24] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
    "[2026-06-22T22:14:30] front_door_l

## 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 occupancy sensor is reporting a persistent 'Empty' (0) state throughout the night and early morning, contradicting expected human presence or activity patterns for a residential bedroom.",
      "supported_by": [
        "[2026-06-22T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-22T00:30:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-22T01:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "The window covering in the bedroom was manually opened and closed at different times of the day, indicating the device is responsive to user interaction.",
      "supported_by": [
        "[2026-06-22T06:41:11] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
        "[2026-06-22T22:14:24] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000"
      ],
      "contradicted_by": []
    }
  ],
  "most_concerning_signals": [
    "[2026-06-22T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-22T00:30:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-22T01:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0"
  ],
  "what_to_verify_in_raw_log": [
    "Check raw packet timestamps vs. local time zone offset to ensure events aren't misaligned due to clock skew.",
    "Search for any 'OccupancyTransition' or 'WakeUp' events around 06:00 or 07:00 to see if the sensor ever detected motion.",
    "Verify if there are any communication errors or battery low warnings associated with the bedroom_occupancy node ID.",
    "Cross-re


触发间隔不规律（不是周期性的），且频率较低（几分钟一次不是几十秒一次）

The second bedroom occupancy sensor is functioning correctly; the room was genuinely unoccupied during the period when house activity occurred elsewhere.

Explanation: Raw logs show consistent 'OccupancySensing.Occupancy = 0' for second_bedroom throughout the night and morning (00:00 to 07:24), contradicting any claim of active presence requiring detection.

Explanation: Significant house activity (front door manual locks at 07:21 and 16:17, entrance occupancy spikes) confirms residents were present but located in other areas (Master Bedroom or Entrance).

Explanation: No missing data points or stuck states are observed for the second_bedroom_occupancy sensor in the provided raw log excerpt.

"[2026-06-18T07:24:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 1" (confirms presence elsewhere)

"[2026-06-18T07:21:00...07:24:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0" (consistent zero readings during entry)

No action required; sensor status is normal.

Continue monitoring standard operational parameters.

[2026-06-18T07:21:17] front_door_lock | DoorLock.LockState = 2

[2026-06-18T07:21:24] front_door_lock | DoorLock.LockState = 1

[2026-06-18T16:17:00] front_door_lock | DoorLock.LockState = 2

"suspicious_signals": ["[2026-06-18T07:21:17] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)"]

"suspicious_signals": ["[2026-06-18T16:17:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)"]

"suspicious_signals": ["[2026-06-18T00:00:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0"]

"suspicious_signals": ["[2026-06-18T00:30:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0"]

"room_activity": {"second_bedroom": 10}, "Event count 1839 implies significant house activity"

"suspicious_signals": ["[2026-06-18T07:21:17] front_door_lock... Manual"]

Raw event logs for 'second_bedroom_occupancy' between 07:00 and 18:00 to check if any 'Occupancy=1' events were missed or filtered out.

Timestamped correlation between the manual door lock events (07:21, 16:17) and any motion/light events in second_bedroom.

Device status history for 'second_bedroom_occupancy' to verify if it is online and transmitting at regular intervals.

## 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_bedroom 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。

## Layout
Layout: 两室一厅 (2BR)
- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>
- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>
- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>
- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>
- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>
- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>
- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1839,
  "salient_event_count": 60,
  "focus_event_count": 91,
  "room_activity": {
    "kitchen": 10,
    "living_room": 19,
    "master_bedroom": 16,
    "second_bedroom": 10,
    "bathroom": 10,
    "entrance": 26
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-18T07:21:17] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-18T07:21:24] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-18T16:17:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-18T18:14:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-18T22:28:28] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-18T07:21:17] fron

## 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_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": "Second bedroom occupancy sensor is malfunctioning (False Negative) or has a configuration error, failing to detect presence despite the room being active.",
      "supported_by": [
        "\"room_activity\": {\"second_bedroom\": 10}",
        "\"suspicious_signals\": [\"[2026-06-18T07:21:17] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)\"]",
        "\"suspicious_signals\": [\"[2026-06-18T16:17:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)\"]"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "The second bedroom occupancy sensor is working correctly and the room was genuinely unoccupied during the logged period.",
      "supported_by": [
        "\"suspicious_signals\": [\"[2026-06-18T00:00:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0\"]",
        "\"suspicious_signals\": [\"[2026-06-18T00:30:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0\"]"
      ],
      "contradicted_by": [
        "\"room_activity\": {\"second_bedroom\": 10}, \"Event count 1839 implies significant house activity\"",
        "\"suspicious_signals\": [\"[2026-06-18T07:21:17] front_door_lock... Manual\"]"
      ]
    }
  ],
  "most_concerning_signals": [
    "[2026-06-18T07:21:17] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-18T16:17:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "\"room_activity\": {\"second_bedroom\": 10}"
  ],
  "what_to_verify_in_raw_log": [
    "Raw event logs for 'second_bedroom_occupancy' between 07:00 and 18:00 to c


触发间隔不规律（不是周期性的），且频率较低（几分钟一次不是几十秒一次）

The bedroom occupancy sensor is functioning correctly; it accurately reported 'Empty' during the house's unoccupied hours and successfully transitioned to 'Occupied' immediately upon user activity (lighting/window operation).

Explanation: Analysis of raw logs confirms the bedroom_occupancy sensor remained at state 0 from 00:00 until 06:43.

Explanation: At 06:41, bathroom activity occurred, followed by bedroom light turning on at 06:43 and window opening at 06:43:11.

Explanation: The bedroom_occupancy sensor updated its state to 1 at 06:43:00 (immediately after lights) and again at 06:48:00 (after window open), demonstrating correct detection latency and no false negatives.

Explanation: Subsequent events (door lock/unlock, further lighting changes) all coincided with or were preceded by accurate occupancy updates.

Explanation: The hypothesis of a stuck sensor is contradicted by the precise temporal alignment between physical actions (lights/windows) and sensor state changes.

[2026-06-08T06:41:06] bathroom_occupancy | OccupancySensing.Occupancy = 1

[2026-06-08T06:43:00] bedroom_occupancy | OccupancySensing.Occupancy = 1

Continue standard monitoring; no intervention required.

Verify that the sensor's field of view covers the entry path if future investigations are needed for edge cases.

High frequency of user interaction events (door locks, window covers) occurring shortly after the last 'empty' readout at 01:30.

Mismatch between physical presence indicators (manual door unlock, window opening/closing) and sensor readings (persistent Occupancy=0).

Temporal proximity: User enters room/opens window within minutes of sensor reporting 'Empty', indicating potential blind spots or latency issues in detection logic.

Check raw IR/Microwave Doppler data timestamps for the bedroom_occupancy sensor around 07:15 and 21:45 to verify if motion was detected but not reported.

Verify battery voltage levels for the bedroom_occupancy sensor to rule out low-power false negatives.

Review configuration settings for the bedroom_occupancy sensor's sensitivity thresholds and ignore-duration timers.

## 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": 1274,
  "salient_event_count": 60,
  "focus_event_count": 107,
  "room_activity": {
    "kitchen": 18,
    "living_room": 34,
    "bedroom": 24,
    "bathroom": 20,
    "entrance": 11
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-08T07:18:13] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-08T07:18:16] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-08T18:25:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-08T21:47:48] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-08T06:43:11] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-08T07:18:13] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-08T07:18:16] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-08T18:25:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-08T21:47:38] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
    "[2026-06-08T21:47:48] front_door_l

## 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 occupancy sensor is stuck in 'Empty' state (0) despite confirmed human activity events (Door Unlocking/Window Operation), suggesting a false negative or calibration drift.",
      "supported_by": [
        "[2026-06-08T07:18:13] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
        "[2026-06-08T07:18:16] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
        "[2026-06-08T06:43:11] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
        "[2026-06-08T21:47:48] front_door_lock | DoorLock.LockState = 1",
        "[2026-06-08T21:47:38] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000"
      ],
      "contradicted_by": [
        "[2026-06-08T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-08T00:30:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-08T01:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0"
      ]
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "The system is correctly detecting the house as empty during early morning hours (00:00 - 01:30) when no door/window interactions occurred.",
      "supported_by": [
        "[2026-06-08T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-08T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-08T01:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-08T01:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0"
      ],
      "contradicted_by": [
        "High frequency of user interaction events (door locks, window cov


触发间隔不规律（不是周期性的），且频率较低（几分钟一次不是几十秒一次）

The second_bedroom occupancy sensor is functioning correctly, consistently reporting 'empty' states during the recorded timeframe with no evidence of malfunction or environmental interference.

Explanation: The sensor reported a consistent value of 0 (empty) at all scheduled polling intervals from 00:00 to 04:30.

Explanation: There were no irregular timestamps, missing reports, or sudden state flips that would indicate a stuck or malfunctioning sensor.

Explanation: No other events in the raw log (such as light toggles, temperature drifts, or room entry/exit) suggest activity in the second_bedroom that should have triggered an occupancy change.

[2026-06-29T04:30:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0

[2026-06-29T18:05:00] front_door_lock | DoorLock.LockState = 2

[2026-06-29T21:56:48] front_door_lock | DoorLock.LockState = 1

## 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_bedroom 区域的传感器 是否工作正常。如果异常，请说明可能的故障类型。

## Layout
Layout: 两室一厅 (2BR)
- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>
- bathroom: 卫生间漏水传感器<water_leak_detector>, 卫生间灯<onoff_light>, 卫生间运动传感器<occupancy_sensor>
- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>
- kitchen: 厨房温度传感器<temperature_sensor>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>
- living_room: 客厅主灯<dimmable_light>, 客厅温度传感器<temperature_sensor>, 客厅空调<air_conditioner>, 客厅窗帘<window_covering>, 客厅窗户传感器<contact_sensor>, 客厅落地灯<onoff_light>, 客厅运动传感器<occupancy_sensor>
- master_bedroom: 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>
- second_bedroom: 次卧温度传感器<temperature_sensor>, 次卧灯<dimmable_light>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>

## Evidence Packet
{
  "sq_type": "SQ1",
  "event_count": 1659,
  "salient_event_count": 60,
  "focus_event_count": 90,
  "room_activity": {
    "kitchen": 11,
    "living_room": 23,
    "master_bedroom": 11,
    "second_bedroom": 11,
    "bathroom": 11,
    "entrance": 23
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-29T07:17:12] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-29T07:17:16] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-29T18:05:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-29T21:56:48] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-29T07:17:12] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-29T07:17:16] front_door_lock | DoorLock.LockState = 1",

## 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_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": "normal",
      "description": "The second_bedroom occupancy sensor is functioning correctly, reporting consistent 'empty' states during the recorded timeframe.",
      "supported_by": [
        "[2026-06-29T00:00:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-29T00:30:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0"
      ],
      "contradicted_by": []
    }
  ],
  "most_concerning_signals": [],
  "what_to_verify_in_raw_log": [
    "Verify if the timestamp intervals (every 30 mins) align with expected polling rates for occupancy sensors in this layout configuration.",
    "Cross-reference room_activity count (11) to ensure it corresponds to non-occupancy related events (e.g., light toggles, temperature drifts) rather than sensor failures."
  ],
  "provisional_risk": "none"
}

## Focused Raw Log
[2026-06-29T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2261
[2026-06-29T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0
[2026-06-29T00:00:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 0
[2026-06-29T00:00:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0
[2026-06-29T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0
[2026-06-29T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0
[2026-06-29T00:05:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2266
[2026-06-29T00:30:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2281
[2026-06-29T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0
[2026-06-29T00:30:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 0
[2026-06-29T00:30:00] second_bedroom_occupancy | OccupancySensing.Occupancy =