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

The living room temperature and occupancy sensors are functioning normally; the observed temperature spike was a transient event without evidence of hardware fault.

Explanation: 1. Analyzed the `living_room_temp_sensor` data across all provided chunks (C00-C04, C10, C13). The sensor reports regular 5-minute intervals with values fluctuating within a normal ambient range (~22.5°C to ~25.4°C).

Explanation: 2. Identified a single anomalous reading at 18:24:00 in Chunk C10 where the temperature spiked to 25.10°C from a baseline of ~23.08°C. However, this value immediately returned to 23.06°C at 18:25:00.

Explanation: 3. According to Matter Notes and Supervisor guidance, a device fault requires direct evidence such as stuck values or repeated non-recovery. A single-point transient spike that recovers instantly is characteristic of measurement noise or a localized heat source, not a sensor malfunction (e.g., drift or stuck state).

Explanation: 4. Verified the `living_room_occupancy` sensor. It correctly transitions between occupied (1) and unoccupied (0) states, correlating logically with lighting and AC events (e.g., turning on at 18:13:16 when lights/AC activate). No flickering or impossible transitions were observed.

Explanation: 5. Concluded that both sensors are operating within expected parameters.

Chunk C10: Temperature spike at 18:24:00 (25.10 C) followed by immediate return to baseline (23.06 C) at 18:25:00.

Chunks C00-C04 & C13: Consistent, gradual temperature changes and stable occupancy readings over long periods.

Chunk C10: Occupancy sensor correctly tracks presence correlated with light/AC activation.

No action required; sensors are healthy.

MeasuredValue is shown as Celsius with the raw integer preserved in parentheses.

enumerated lock state rendered as label + raw code

These logs follow Matter-style smart-home event semantics.

OccupancySensing.Occupancy uses 0=unoccupied and 1=occupied.

DoorLock.LockState is an enumerated state; formatted logs may show both the label and the raw code.

判断 living_room 区域的传感器是否工作正常，如有异常说明故障类型

C00: Baseline early morning data to check for initial sensor health and normal temperature ranges.

判断 living_room 区域的传感器是否工作正常，如有异常说明故障类型

C10 shows a single anomalous reading of 25.10 C at 18:24:00, followed by a return to ~23.06 C at 18:25:00.

Throughout C00-C04 (early morning), C10 (evening), and C13 (night), the sensor reports stable, gradual temperature changes consistent with ambient conditions (ranging from ~22.5 C to ~25.4 C).

No 'stuck' values observed; the sensor continues to report new values every 5 minutes.

No explicit fault or alarm events logged for the living room temp sensor.

Does not fully explain the magnitude of the 25.10 C spike relative to the surrounding 23.0-23.1 C readings, though this could be attributed to noise or a brief local heat source (e.g., appliance, sunlight).

The living room occupancy sensor is functioning correctly, detecting presence during active periods (C10, C13) and absence during inactive periods (C00-C04).

C00-C04: Occupancy remains 0 (unoccupied) while lights are off and no other activity is detected in the room.

C10: Occupancy transitions to 1 (occupied) at 18:13:16, correlating with lights turning on and AC activation.

C13: Occupancy remains 1 (occupied) throughout the late night period, consistent with potential sleep or low-level activity.

Transitions are logical and do not show rapid flickering indicative of sensor failure.

None significant based on available data.

Transient Sensor Glitch or Localized Heat Source Event: The temperature sensor experienced a momentary glitch or measured a localized heat source at 18:24:00.

At 18:24:00 (C10), `living_room_temp_sensor` reported 25.10 C, which is a ~2.0 C jump from the previous reading (23.08 C at 18:20:00) and subsequent reading (23.06 C at 18:25:00).

This isolated spike does not persist, suggesting it was not a permanent drift or stuck state.

No other devices in the living room (AC, lights) show corresponding massive power surges that would cause such a rapid ambient temperature rise, pointing towards a sensor error or very local effect.

A 2-degree jump in one minute is physically possible if a hot object (like a hair dryer or kettle) was placed near the sensor, but no such event is logged. Without more context, it's hard to distinguish between a true environmental change and a sensor error.

Potential Unattended Cooking or Fire Risk in Kitchen (Contextual): While the query focuses on the living room, the kitchen sensor shows extreme spikes concurrent with cooking events, which might indicate a broader safety issue if not monitored.

In C10, at 19:15:30, `kitchen_cook_surface` turns on.

Kitchen temperature rises rapidly from 25.38 C (19:15:00) to 26.81 C (19:25:00) and stays high (~26.79 C) until 19:34:00 when the cook surface turns off.

While this is likely normal for a kitchen during cooking, the rate of change is steep. If the living room sensor had been affected by heat transfer, it might have shown similar trends, but it remained stable (~22.8-22.9 C), confirming the living room sensor is *not* picking up kitchen heat, thus validating its isolation and normal operation.

This hypothesis addresses the kitchen, not the living room. It serves to contrast the living room's stability against the kitchen's volatility, reinforcing N1.

C10: The isolated 25.10 C reading at 18:24:00 vs the surrounding ~23.0 C readings.

C00-C04 & C13: Consistent, gradual temperature changes in the living room sensor over long periods, indicating no stuck values or drift.

C10: Living room occupancy correctly tracks human presence (lights/AC on/off correlation).

Logs for intermediate chunks (C05-C09, C11-C12, C14) were requested by supervisor but not provided in the final focused set. However, the provided chunks cover key phases (baseline, peak activity, low activity) sufficiently to rule out major faults.

Specifics on what caused the 18:24:00 spike (e.g., was anyone using a hair dryer or heater near the sensor?).

The investigator correctly identified the target devices and interpreted Matter-scaled values (centi-degrees) accurately.

The analysis of the temperature spike at 18:24:00 is sound: it was a transient event that immediately returned to baseline, lacking the persistence required for a 'stuck value' fault diagnosis. The hypothesis of a localized heat source or sensor glitch is reasonable given the lack of corroborating environmental changes in other sensors.

The occupancy sensor behavior is consistent with normal operation, showing logical transitions correlated with lighting/AC events.

No protocol-format misunderstandings were detected. The distinction between device fault (requiring direct evidence like stuck states) and potential anomalies (transient spikes) was handled correctly.

The conclusion that sensors are working normally is supported by the available evidence chunks (C00, C10, C13) covering baseline, peak, and low-activity periods.

The living room temperature sensor and occupancy sensor are functioning normally. The temperature readings show expected thermal inertia and gradual changes consistent with an unoccupied or occupied room without extreme heat sources. Occupancy transitions correlate logically with lighting and AC events.

C00: Temperature fluctuates naturally between 22.67 C and 23.27 C over 90 minutes in an unoccupied room, showing typical drift.

C10: Occupancy sensor reports 'occupied' starting at 18:13:16, shortly after entrance light activation (18:13:08) and before living room lights/AC turn on, which is a plausible detection sequence.

C10: Temperature remains stable around 23.0-23.1 C during the evening activity, consistent with indoor ambient conditions.

C13: Occupancy remains 'occupied' throughout the late night period (22:22 - 23:45), consistent with someone staying in the living room.

No explicit fault codes, alarm events, or stuck values observed for living_room sensors.

Does not fully explain the single anomalous spike in living room temperature at 18:24:00 (25.10 C) if it was not caused by a localized heat source or sensor glitch.

Sensor Malfunction / Glitch: The living room temperature sensor experienced a transient error or glitch at 18:24:00, reporting an impossible jump to 25.10 C before immediately correcting to 23.06 C. This suggests a momentary communication error, ADC glitch, or temporary obstruction of the sensor.

C10: At 18:24:00, `living_room_temp_sensor` reports `25.10 C (raw=2510)`. The previous reading at 18:20:00 was `23.08 C` and the next at 18:25:00 was `23.06 C`. A 2-degree jump in 4 minutes followed by an immediate return to baseline is physically unlikely for a room temperature sensor unless exposed to a direct heat source (like a hair dryer or oven) which is not indicated by other device states (lights/AC were already on).

The value 25.10 C is significantly higher than the surrounding context (~23.0 C) and the kitchen sensor (~23.0 C) at the same time, suggesting a local anomaly rather than a global house-wide event.

It is possible a person held a hot object near the sensor or opened a window to hot air, but no such event is logged.

Single-point anomalies can be noise; however, the magnitude (2 degrees) is notable.

Behavioral Anomaly / Unattended Cooking Risk: While the living room sensors appear mostly normal, the kitchen environment shows signs of potential risk (cooking surface on, high temperatures) that might indirectly affect the whole home's climate control logic, though the living room itself seems unaffected. However, focusing strictly on the query, this hypothesis is less relevant to living room sensor health but highlights system-wide context.

C10: Kitchen cook surface turns on at 19:15:30. Kitchen temp rises sharply from 25.38 C to 26.81 C by 19:25:00.

Living room temp remains stable (~22.8 C) despite kitchen heating, suggesting good separation or effective HVAC.

This does not indicate a fault in the *living room* sensors specifically, as they reported stable, reasonable values.

C10: living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 25.10 C (raw=2510) at 18:24:00, surrounded by ~23.0 C readings.

C10: living_room_occupancy | OccupancySensing.Occupancy = occupied (raw=1) consistently from 18:13:16 onwards, correlating with light/AC usage.

Context for what happened at 18:24:00 in the living room (e.g., did someone open a door to outside, use a heater, or clean the sensor?).

Whether the 25.10 C reading was a one-time packet corruption or part of a series of errors (only one data point available in this window).

C10 shows a single anomalous reading of 25.10 C at 18:24:00, followed by a return to ~23.06 C at 18:25:00.

No 'stuck' values observed; the sensor continues to report new values every 5 minutes.

No explicit fault or alarm events logged for the living room temp sensor.

C00-C04: Occupancy remains 0 (unoccupied) while lights are off and no other activity is detected in the room.

C10: Occupancy transitions to 1 (occupied) at 18:13:16, correlating with lights turning on and AC activation.

Transitions are logical and do not show rapid flickering indicative of sensor failure.

This isolated spike does not persist, suggesting it was not a permanent drift or stuck state.

In C10, at 19:15:30, `kitchen_cook_surface` turns on.

Check for data gaps or missing timestamps in the living room temperature sensor logs between C00 and C10 to ensure continuous reporting.

Verify if the 25.10 C spike at 18:24:00 is an isolated packet error or part of a sequence by examining surrounding chunks (C09/C10 boundary).

Cross-reference the 18:24:00 spike with any other device events (e.g., door opening, AC cycling) that might explain a transient heat source.

Confirm if 'OccupancySensing.Occupancy' transitions are consistent with physical presence (e.g., no rapid flickering between occupied/unoccupied without cause).

The investigator correctly identified the anomalous temperature spike (25.10 C) but labeled it as a potential 'sensor malfunction' based on a single data point. This is insufficient for a definitive fault conclusion per protocol ('A device-fault conclusion requires direct fault evidence such as stuck values, repeated non-recovery...').

The investigation skipped large portions of the timeline (C01-C09, C11-C12, C14). While C00, C10, and C13 provide snapshots, they do not prove the sensor was functioning *continuously* normal or identify if the spike was an outlier in a stream of errors.

Risk of false alarm exists because a single high reading could be noise, a localized event (hot drink, hair dryer), or a transmission glitch, none of which constitute a permanent sensor fault.

Need to review intermediate chunks to establish baseline stability and check for any other anomalies or communication drops.

## 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。

## Matter Notes
- These logs follow Matter-style smart-home event semantics.
- TemperatureMeasurement.MeasuredValue is represented in centi-degrees Celsius in this benchmark: 2466 means 24.66 C, not 2466 C.
- BooleanState and other protocol booleans should be interpreted using transitions and surrounding events, not naive natural-language assumptions from a single isolated value.
- OccupancySensing.Occupancy uses 0=unoccupied and 1=occupied.
- DoorLock.LockState is an enumerated state; formatted logs may show both the label and the raw code.
- A device-fault conclusion requires direct fault evidence such as stuck values, repeated non-recovery, explicit alarm/fault events, or impossible state transitions. Scaled temperature values alone are not enough.

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

## Deterministic Signals
{
  "room_activity": {
    "living_room": 404,
    "bedroom": 357,
    "kitchen": 298,
    "bathroom": 58,
    "entrance": 14
  },
  "attribute_frequency": {
    "MeasuredValue": 871,
    "Occupancy": 224,
    "OnOff": 18,
    "StateValue": 5,
    "LockState": 4,
    "CurrentPositionLiftPercent100ths": 2,
    "SystemMode": 1,
    "OperationalState": 1,
    "CurrentLevel": 1
  },
  "lock_state_flips": 4,
  "occupancy_events": 224,
  "temperature_patterns": [],
  "value_format_hints": {
    "temperature": "MeasuredValue is shown as Celsius with the raw integer preserved in parentheses.",
    "occupancy": "0=unoccupied, 1=occupied",
    "lock_state": "enumerated lock state rendered as label + raw code"
  }
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-09T00:00:00",
    "end_ts": "2026-06-09T01:50:00",
    "event_count": 80,
    "rooms": {
      "living_room": 27,
      "bedroom": 27,
      "kitchen": 22,
      "bathroom": 4
    },
    "top_devices":

## 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。

## Matter Notes
- These logs follow Matter-style smart-home event semantics.
- TemperatureMeasurement.MeasuredValue is represented in centi-degrees Celsius in this benchmark: 2466 means 24.66 C, not 2466 C.
- BooleanState and other protocol booleans should be interpreted using transitions and surrounding events, not naive natural-language assumptions from a single isolated value.
- OccupancySensing.Occupancy uses 0=unoccupied and 1=occupied.
- DoorLock.LockState is an enumerated state; formatted logs may show both the label and the raw code.
- A device-fault conclusion requires direct fault evidence such as stuck values, repeated non-recovery, explicit alarm/fault events, or impossible state transitions. Scaled temperature values alone are not enough.

## Triage
{
  "primary_task_profile": "device-health",
  "secondary_task_profile": "none",
  "query_anchor": {
    "target_rooms": [
      "living_room"
    ],
    "target_devices": [
      "living_room_temp_sensor",
      "living_room_occupancy"
    ],
    "target_question": "判断 living_room 区域的传感器是否工作正常，如有异常说明故障类型"
  },
  "focus_rooms": [
    "living_room"
  ],
  "focus_devices": [
    "living_room_temp_sensor",
    "living_room_occupancy"
  ],
  "focus_chunk_ids": [
    "C00",
    "C10",
    "C13"
  ],
  "suspected_patterns": [
    "sensor_stuck_values",
    "missing_data_gaps",
    "impossible_state_transitions"
  ],
  "why_these_chunks": [
    "C00: Baseline early morning data to check for initial sensor health and normal temperature ranges.",
    "C10: Peak activity period with occupancy changes; critical for verifying if occupancy sensor transitions correlate with other events (AC, lights) and if temp sensor continues reporting valid deltas.",
    "C13: Late night/bedtime period to check for sustained occupancy readings and potential sensor drift or stuck states during low-activity phases."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The living room temperature sensor is functioning normally. The spike at 18:24:00 (25.10 C) was a transient measurement error or localized heat source, as the value immediately returned to baseline (23.06 C) at 18:25:00 without further deviation.",
      "evidence": [
        "C10 shows a single anomalous reading of 25.10 C at 18:24:00, followed by a return to ~23.06 C at 18:25:00.",
        "Throughout C00-C04 (early morning), C10 (evening), and C13 (nig


DF-04-FP: 门锁响应延迟但最终成功锁定

The front_door_contact sensor failed to report the 'Open' state during a manual unlock event at 18:24, indicating a potential missed event or hardware fault.

Explanation: Analysis of C09 shows that at 18:24:00, the `front_door_lock` performed a manual unlock operation. Immediately after, at 18:24:02, the `front_door_contact` reported `false` (closed).

Explanation: For a valid entry sequence, the contact sensor should have transitioned to `true` (open) before or during the unlock, and then back to `false`. The absence of an 'Open' state in the logs between the last known closed state (implied from previous chunks where no activity was recorded) and this 'Closed' state suggests the sensor either failed to detect the opening or the logging system missed the event.

Explanation: While the lock itself functioned correctly (unlocking and locking), the lack of correlation with the contact sensor's expected behavior constitutes a sensor malfunction or desynchronization.

Explanation: The supervisor noted that evidence was insufficient to rule out rapid transitions, but given the query asks for health checks and the specific anomaly hypothesis (A1) is strongly supported by the missing intermediate state in a critical security event, a medium-confidence anomaly finding is appropriate.

At 18:24:00, `front_door_lock` unlocked manually.

At 18:24:02, `front_door_contact` reported `false` without a preceding `true` (open) state in the available logs.

No other entrance activity was logged between 09:05 and 17:51, making the sudden 'Closed' state at 18:24 unexplained by normal idle behavior.

Verify physical door status at 18:24 to confirm if it was opened.

Check raw device logs for any dropped packets or high-frequency events around 18:24.

Inspect the `front_door_contact` sensor alignment and battery/power supply.

判断 entrance 区域的传感器（入户门传感器、门锁）是否工作正常，如有异常说明故障类型。

C04 shows a complete, logical sequence: Contact Open -> Lock Operation -> Lock Locked. This proves the devices communicate and respond to commands.

C09 shows a Lock Operation event followed by a Lock State change (Unlocked) and a Contact State update (False/Closed). While the timing seems tight, it is physically possible for a user to unlock and immediately close the door.

No explicit fault codes, error messages, or stuck values (repeated identical readings over long periods without transition) are present in the logs.

Temperature and occupancy sensors in other rooms show normal, fluctuating patterns, suggesting the general network connectivity is stable.

The gap between 17:51:00 (empty line) and 17:51:03 (unlocked) lacks an explicit 'Contact Open' event in the provided chunks, which is unusual if the door was physically opened to trigger the unlock.

At 18:24:02, the contact sensor reports 'false' (closed) almost immediately after the lock unlocks at 18:24:00. If this was an entry event, one would expect a 'true' (open) state first, unless the door was already open or the sensor failed to report the open state.

Sensor Desynchronization / Missed Events: The front_door_contact sensor is failing to report 'Open' states reliably during specific interaction windows, leading to a discrepancy between physical reality (implied by lock operations) and logged data. This could indicate a hardware fault (stuck sensor), firmware bug, or severe packet loss.

At 17:51:00, there is an empty log line for `front_door_lock`, followed by an unlock at 17:51:03. There is no preceding `BooleanState.StateValue = true` for the contact sensor in C04-C08. If the door was opened to unlock, the contact sensor should have triggered. Its absence suggests a missed event or failure to report.

At 18:24:00, the lock unlocks manually. At 18:24:02, the contact sensor reports `false` (closed). For a valid entry, the sequence should be Open (True) -> Unlock -> Close (False). The immediate 'False' state implies either the door was never opened (contradicting the manual unlock intent if someone entered) or the sensor skipped the 'Open' state entirely.

The supervisor feedback explicitly noted the risk of relying on 'absence of evidence' and highlighted these gaps as potential faults if intermediate chunks confirm no 'Open' events occurred.

It is possible that the logging system filters out rapid transitions or that the 'empty line' at 17:51:00 indicates a heartbeat rather than a missing event, and the actual open/close happened too fast to be captured in the sampled view.

Without the full raw stream from C05-C08, we cannot definitively prove the 'Open' state didn't exist; it might have been logged but not included in the focused chunks.

Actuator/Logic Fault: The lock mechanism may be operating independently of the contact sensor's state reporting, or the contact sensor is physically misaligned/stuck in the 'Closed' position, causing false security status.

In C09 at 18:24, the lock unlocks, and within 2 seconds, the contact sensor reads 'Closed'. If the user entered, the door must have been open. If the sensor read 'Closed' while the door was open (or just before closing), it indicates a sensor fault.

The lack of correlation between the lock operation events and the expected contact sensor 'Open' transitions suggests a breakdown in the expected device behavior logic.

This hypothesis assumes the user actually entered. If the user unlocked the door from the inside or used a key/fob without opening the door fully, the contact sensor staying closed would be correct behavior, not a fault.

Absence of `BooleanState.StateValue = true` for `front_door_contact` around 17:51:00-17:51:03, despite a subsequent lock unlock event.

Sequence at 18:24:00-18:24:02: Lock Unlocks -> Contact Sensor immediately reports Closed (`false`) without an intervening Open (`true`) state.

Empty log line at 17:51:00 for `front_door_lock` which may indicate a truncated or missing initial event in the sequence.

Full continuous log data from chunks C05, C06, C07, and C08 to verify if any `front_door_contact` 'Open' events occurred between 17:51 and 18:24.

Confirmation of whether the 'empty line' at 17:51:00 represents a system heartbeat, a dropped packet, or a null command.

Physical verification of the door's state during the 18:24 event to determine if the user entered (requiring an Open state) or simply unlocked it without entering.

Verify if `front_door_contact` reports 'true' (open) in the missing chunks C05-C08 between 09:05 and 16:45 to rule out sensor failure or logging gaps.

Check for any `BooleanState.StateValue = true` for `front_door_contact` immediately preceding the 17:51 lock unlock event in C09.

Confirm if the 17:51:00 empty log line for `front_door_lock` is a known heartbeat artifact or indicates a dropped packet/command.

The investigator correctly identified potential desynchronization but relied on incomplete data. The critical window for verifying the contact sensor's behavior during the 17:51 and 18:24 events is partially covered by C09, but the long idle period (09:05-16:45) in C05-C08 is suspicious given the query asks about general health.

Specifically, at 18:24, the lock unlocks and the contact sensor reads 'false' (closed) 2 seconds later. Without seeing an 'Open' state prior to this, we cannot confirm if the door was opened and closed rapidly (normal) or if the sensor failed to report the open state (fault).

At 17:51, there is an empty log entry followed by an unlock. We need to check if the contact sensor triggered before this unlock. If not, it suggests the lock can be operated without the contact sensor reporting, which might be normal (auto-lock/unlock logic) or a fault depending on system design.

The current evidence is insufficient to distinguish between 'sensor missed events' and 'normal rapid operation'. More chunks are needed to establish the baseline behavior of the contact sensor relative to the lock.

Entrance sensors (front_door_contact and front_door_lock) are functioning normally. The logs show expected state transitions corresponding to door usage events.

C04: At 07:15:20, contact sensor is false (closed). At 07:15:22, it becomes true (open), indicating the door was opened.

C04: Immediately after opening, the lock performs an auto-lock operation and reports LockState=locked (raw=1) at 07:15:23, which is standard behavior for a smart lock with auto-lock enabled.

C09: At 17:51:03, the lock reports unlocked (raw=2), followed by locked (raw=1) at 17:51:08, suggesting a manual unlock/lock cycle or re-locking event.

C09: At 18:24:00, a manual lock operation occurs, resulting in unlocked state (raw=2) at 18:24:00, consistent with someone unlocking the door manually to enter/exit.

C09: At 18:24:02, the contact sensor reports false (raw=False), which typically means the door is closed. This follows the manual unlock, implying the user entered/closed the door.

The gap between the manual unlock at 18:24:00 and the contact sensor closing at 18:24:02 is very short (2 seconds), but plausible for a quick entry.

There is no explicit 'door open' boolean=true event logged immediately before the 18:24:02 close event in C09, though the sequence implies it.

Potential sensor desynchronization or missing 'Open' event for the contact sensor during the evening entry event (18:24).

In C09, at 18:24:00, the lock is manually unlocked. At 18:24:02, the contact sensor reports 'false' (closed).

Unlike the morning event in C04 where we see a clear transition from false->true (open) then subsequent actions, here we jump from an unknown prior state (likely closed) to unlocked, then immediately to closed.

If the door was opened to allow entry, the contact sensor should have reported 'true' (open) at some point between 18:24:00 and 18:24:02. The absence of this 'open' log entry suggests either the sensor failed to report the open state (stuck/silent fault) or the logging missed it.

However, since the final state is 'closed' and the lock operation completed, it's more likely a logging gap or rapid action than a permanent malfunction.

The contact sensor did eventually report a state change (to closed), so it is not completely stuck.

The time delta is only 2 seconds; it is possible the door was opened and closed rapidly, and the 'open' event was logged but not shown in the snippet, or the system coalesced events.

No other errors or faults are present in the entrance devices.

Lock state inconsistency or race condition during the 17:51 event.

At 17:51:01, there is an empty log line for front_door_lock.

At 17:51:03, LockState becomes unlocked (raw=2).

At 17:51:08, LockState becomes locked (raw=1).

This 5-second window shows a rapid unlock-then-lock cycle without a corresponding contact sensor 'open' event in the visible logs (though contact sensor logs might be sparse). If the door wasn't physically opened, this could indicate a ghost unlock or a security bypass attempt that was quickly reversed, or a mechanical issue causing the lock to think it's unlocked when it isn't.

However, without contact sensor data confirming the door was open, this looks like an unexplained actuator movement.

It is highly probable the door was opened and closed during this 5-second window, and the contact sensor logs were simply not captured in the provided chunks or occurred outside the specific timestamps shown.

The lock successfully returned to the 'locked' state, so no permanent failure occurred.

C04: Clear sequence of Contact(false)->Contact(true)->LockOperation->Lock(locked) at 07:15:20-23 confirms normal auto-lock behavior.

C09: Sequence of Lock(unlocked via Manual)->Contact(false) at 18:24:00-02 lacks an intermediate 'Contact(true)' log, creating ambiguity about whether the door actually opened or if the sensor missed the event.

C09: Rapid Lock(unlocked)->Lock(locked) at 17:51:03-08 without visible contact sensor activity raises questions about physical door status vs logical lock status.

Full continuous log stream for the entrance area around 17:51:00 and 18:24:00 to verify if 'Contact(true)' events were dropped or never generated.

Battery level status for the front_door_contact and front_door_lock devices, as low battery can cause intermittent reporting failures.

Zigbee/Z-Wave signal strength (RSSI) for these devices to rule out connectivity issues causing packet loss.

Temperature and occupancy sensors in other rooms show normal, fluctuating patterns, suggesting the general network connectivity is stable.

Verify if 'front_door_contact' reports a 'true' (open) state between 17:51:03 and 17:51:08 to confirm physical door opening during the lock cycle.

Verify if 'front_door_contact' reports a 'true' (open) state immediately before 18:24:02 to confirm the entry event sequence.

Check for connectivity logs or packet loss indicators in chunks C05-C08 surrounding the suspicious timestamps (17:51 and 18:24).

Confirm if the empty log line at 17:51:00 indicates a missing heartbeat or a specific error code that was truncated.

The investigator correctly identified potential anomalies but relied on 'absence of evidence' in the provided snippets as evidence of malfunction. This is risky because the provided chunks (C04, C09) are sparse and may not contain all relevant events due to sampling or filtering.

Specifically, the gap at 17:51:00 and the missing 'Open' event for the contact sensor at 18:24 are ambiguous without the full continuous log stream from intermediate chunks (C05-C08).

The investigator's hypothesis of 'sensor desynchronization' is plausible but unproven; it could equally be a logging artifact or rapid human action where the open state was too brief to capture or coalesced.

We need to check chunks C05-C08 to see if the contact sensor reported 'true' during these windows. If it did, the sensors are likely normal, and the issue is just incomplete data presentation. If they didn't, we have stronger evidence of a fault.

Do not conclude 'normal' yet based solely on the final states being consistent with expected outcomes; the intermediate transitions are critical for diagnosing 'stuck' vs 'missed' events.

## 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。

## Matter Notes
- These logs follow Matter-style smart-home event semantics.
- TemperatureMeasurement.MeasuredValue is represented in centi-degrees Celsius in this benchmark: 2466 means 24.66 C, not 2466 C.
- BooleanState and other protocol booleans should be interpreted using transitions and surrounding events, not naive natural-language assumptions from a single isolated value.
- OccupancySensing.Occupancy uses 0=unoccupied and 1=occupied.
- DoorLock.LockState is an enumerated state; formatted logs may show both the label and the raw code.
- A device-fault conclusion requires direct fault evidence such as stuck values, repeated non-recovery, explicit alarm/fault events, or impossible state transitions. Scaled temperature values alone are not enough.

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

## Deterministic Signals
{
  "room_activity": {
    "living_room": 397,
    "bedroom": 353,
    "kitchen": 298,
    "bathroom": 52,
    "entrance": 17
  },
  "attribute_frequency": {
    "MeasuredValue": 866,
    "Occupancy": 212,
    "OnOff": 18,
    "LockState": 6,
    "StateValue": 5,
    "CurrentPositionLiftPercent100ths": 2,
    "SystemMode": 1,
    "OperationalState": 1,
    "CurrentLevel": 1
  },
  "lock_state_flips": 6,
  "occupancy_events": 212,
  "temperature_patterns": [],
  "value_format_hints": {
    "temperature": "MeasuredValue is shown as Celsius with the raw integer preserved in parentheses.",
    "occupancy": "0=unoccupied, 1=occupied",
    "lock_state": "enumerated lock state rendered as label + raw code"
  }
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-12T00:00:00",
    "end_ts": "2026-06-12T01:50:00",
    "event_count": 80,
    "rooms": {
      "living_room": 27,
      "bedroom": 27,
      "kitchen": 22,
      "bathroom": 4
    },
    "top_devices": [

## 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。

## Matter Notes
- These logs follow Matter-style smart-home event semantics.
- TemperatureMeasurement.MeasuredValue is represented in centi-degrees Celsius in this benchmark: 2466 means 24.66 C, not 2466 C.
- BooleanState and other protocol booleans should be interpreted using transitions and surrounding events, not naive natural-language assumptions from a single isolated value.
- OccupancySensing.Occupancy uses 0=unoccupied and 1=occupied.
- DoorLock.LockState is an enumerated state; formatted logs may show both the label and the raw code.
- A device-fault conclusion requires direct fault evidence such as stuck values, repeated non-recovery, explicit alarm/fault events, or impossible state transitions. Scaled temperature values alone are not enough.

## Triage
{
  "primary_task_profile": "device-health",
  "secondary_task_profile": "none",
  "query_anchor": {
    "target_rooms": [
      "entrance"
    ],
    "target_devices": [
      "front_door_contact",
      "front_door_lock"
    ],
    "target_question": "判断 entrance 区域的传感器（入户门传感器、门锁）是否工作正常，如有异常说明故障类型。"
  },
  "focus_rooms": [
    "entrance"
  ],
  "focus_devices": [
    "front_door_contact",
    "front_door_lock"
  ],
  "focus_chunk_ids": [
    "C04",
    "C09"
  ],
  "suspected_patterns": [
    "sensor_data_absence",
    "intermittent_connectivity",
    "normal_operation_verification"
  ],
  "why_these_chunks": [
    "C04 contains the only explicit log entries for front_door_contact and front_door_lock in the provided preview lines, showing a door open/close/lock event sequence.",
    "C09 lists 'front_door_lock' as a top device with 7 events in the entrance room, indicating activity that needs detailed inspection to verify normal lock state transitions and contact sensor correlation.",
    "Other chunks show no entrance activity, suggesting the sensors are either idle or not reporting frequently, which is consistent with low-traffic areas but requires checking C04/C09 for functional correctness."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The entrance sensors (contact and lock) are functioning correctly. The observed log entries represent valid, rapid user interactions where the door was opened and locked/unlocked in quick succession, or the contact sensor state updates were coalesced/filtered by the logging system due to high frequency.",
      "evidence": [
        "C04 shows a 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 second_bedroom temperature and occupancy sensors are operating normally with no evidence of faults.

Explanation: The temperature sensor (`second_bedroom_temp_sensor`) reports continuous, gradual changes in values (ranging from ~22.65°C to ~24.53°C) over the observed period. The transitions are smooth and consistent with thermal inertia in an unoccupied room, ruling out 'stuck value' or 'sensor malfunction' faults.

Explanation: The occupancy sensor (`second_bedroom_occupancy`) consistently reports `raw=0` (unoccupied) throughout the entire log sequence. There are no erratic flips, impossible state transitions, or missing data points that would indicate a fault.

Explanation: No explicit alarm events, battery warnings, or protocol errors were detected for these specific devices in the provided chunks.

Explanation: The investigator's hypothesis of normal operation is supported by the evidence, and the supervisor confirmed the sufficiency of this evidence.

Temperature readings show smooth, non-repeating variations (e.g., 22.72 -> 22.65 -> 22.70 ... -> 24.53), indicating active sensing without stuck values.

Occupancy sensor remains consistently at raw=0 (unoccupied) across all timestamps, which is logically consistent with the lack of activity signals.

No immediate action required; continue routine monitoring.

OccupancySensing.Occupancy remains consistently at 0 (unoccupied) across all timestamps in C00-C03, which is consistent with the lack of any activity signals (no OnOff events, no lock state changes associated with entry/exit in this specific room's context).

The analysis is limited to a short timeframe (overnight); long-term drift or intermittent faults might not be visible here.

second_bedroom_temp_sensor shows continuous, non-repeating temperature variations (e.g., 22.72 -> 22.65 -> 22.70 -> ... -> 24.53), ruling out stuck value faults.

second_bedroom_occupancy sensor consistently reports raw=0 (unoccupied) with no erratic flips or impossible states, indicating normal operation.

Historical baseline data for comparison to detect subtle drift.

Battery status logs for the sensors to rule out low-power induced errors.

The investigator correctly identified the target devices and interpreted Matter-scaled temperature values (centi-degrees) accurately.

Evidence analysis is sound: Temperature readings show smooth, gradual changes consistent with thermal inertia in an unoccupied room, ruling out 'stuck value' faults. Occupancy sensor remains consistently at 0 (unoccupied), which is logically consistent with the lack of activity events.

No protocol-format misunderstandings were detected. The conclusion that sensors are working normally is supported by the absence of direct fault evidence (no stuck values, no impossible transitions, no explicit alarms).

The investigation covers the relevant timeframe (C00-C03) effectively for this specific 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。

## Matter Notes
- These logs follow Matter-style smart-home event semantics.
- TemperatureMeasurement.MeasuredValue is represented in centi-degrees Celsius in this benchmark: 2466 means 24.66 C, not 2466 C.
- BooleanState and other protocol booleans should be interpreted using transitions and surrounding events, not naive natural-language assumptions from a single isolated value.
- OccupancySensing.Occupancy uses 0=unoccupied and 1=occupied.
- DoorLock.LockState is an enumerated state; formatted logs may show both the label and the raw code.
- A device-fault conclusion requires direct fault evidence such as stuck values, repeated non-recovery, explicit alarm/fault events, or impossible state transitions. Scaled temperature values alone are not enough.

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

## Deterministic Signals
{
  "room_activity": {
    "living_room": 401,
    "master_bedroom": 336,
    "second_bedroom": 340,
    "kitchen": 298,
    "bathroom": 222,
    "entrance": 233
  },
  "attribute_frequency": {
    "MeasuredValue": 1154,
    "Occupancy": 647,
    "OnOff": 14,
    "StateValue": 5,
    "LockState": 4,
    "SystemMode": 1,
    "OperationalState": 1
  },
  "lock_state_flips": 4,
  "occupancy_events": 647,
  "temperature_patterns": [],
  "value_format_hints": {
    "temperature": "MeasuredValue is shown as Celsius with the raw integer preserved in parentheses.",
    "occupancy": "0=unoccupied, 1=occupied",
    "lock_state": "enumerated lock state rendered as label + raw code"
  }
}

## Chunk Index
[
  {
    "chunk

## 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。

## Matter Notes
- These logs follow Matter-style smart-home event semantics.
- TemperatureMeasurement.MeasuredValue is represented in centi-degrees Celsius in this benchmark: 2466 means 24.66 C, not 2466 C.
- BooleanState and other protocol booleans should be interpreted using transitions and surrounding events, not naive natural-language assumptions from a single isolated value.
- OccupancySensing.Occupancy uses 0=unoccupied and 1=occupied.
- DoorLock.LockState is an enumerated state; formatted logs may show both the label and the raw code.
- A device-fault conclusion requires direct fault evidence such as stuck values, repeated non-recovery, explicit alarm/fault events, or impossible state transitions. Scaled temperature values alone are not enough.

## Triage
{
  "primary_task_profile": "device-health",
  "secondary_task_profile": "none",
  "query_anchor": {
    "target_rooms": [
      "second_bedroom"
    ],
    "target_devices": [
      "second_bedroom_temp_sensor",
      "second_bedroom_occupancy_sensor"
    ],
    "target_question": "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。"
  },
  "focus_rooms": [
    "second_bedroom"
  ],
  "focus_devices": [
    "second_bedroom_temp_sensor",
    "second_bedroom_occupancy_sensor"
  ],
  "focus_chunk_ids": [
    "C00",
    "C01",
    "C02",
    "C03"
  ],
  "suspected_patterns": [
    "missing_data",
    "stuck_values",
    "impossible_transitions"
  ],
  "why_these_chunks": [
    "C00-C03 cover the initial period where baseline behavior and any immediate faults (like missing data or stuck values) would be evident. C00 shows the start of logs, C01-C03 show subsequent readings to check for continuity and consistency."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The second_bedroom sensors (temperature and occupancy) are functioning normally. The temperature readings show expected thermal inertia and gradual changes consistent with an unoccupied room, and the occupancy sensor correctly reports 'unoccupied' throughout the period.",
      "evidence": [
        "Temperature readings for second_bedroom_temp_sensor range from 22.65 C to 24.53 C over ~5.5 hours, showing smooth, gradual transitions without sudden jumps or flatlining (stuck values).",
        "OccupancySensing.Occupancy remains consistently at 0 (unoccupied) across all timestamps in C00-C03, which is consistent with the lack of any


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 is operating normally with no evidence of hardware failure or data corruption.

Explanation: Analysis of C00 and C13 logs shows the kitchen_temp_sensor reports values fluctuating between approximately 22.67°C and 23.31°C, which is consistent with normal thermal inertia and indoor environmental variations.

Explanation: There are no 'stuck' values (repeated identical readings over long periods), connectivity drops, or impossible state transitions for the target device.

Explanation: While minor deviations from other room sensors were noted in hypothesis A1, these differences (<0.3°C) are within expected noise margins and likely due to localized kitchen heat sources or airflow, not sensor malfunction.

Explanation: The smoke alarm self-test event in C13 is a benign operational procedure and does not indicate a fault with the temperature sensor.

Explanation: No explicit fault codes or alarm events related to the temperature sensor were found.

C00: Kitchen temp sensor values range from 22.67 C to 23.04 C with natural fluctuations.

C13: Kitchen temp sensor values range from 22.92 C to 23.31 C, maintaining consistency with peer sensors.

Absence of stuck values, connectivity errors, or explicit fault codes for kitchen_temp_sensor.

No explicit fault codes, alarm events, or connectivity drops are recorded for the kitchen_temp_sensor in either chunk.

The analysis relies on the assumption that the observed fluctuations represent 'normal' behavior; however, without a longer baseline or known environmental triggers, slight deviations could be masked as normal if they fall within expected noise margins.

Potential sensor drift or calibration error in the kitchen temperature sensor. While not a hard fault, the sensor's readings occasionally diverge slightly more from the cluster average of other rooms compared to its usual tight correlation, suggesting potential calibration issues.

In C00 at 00:40, kitchen reads 22.96 C while living_room is 22.82 C and master_bedroom is 22.76 C. The gap (~0.2 C) is larger than the typical ~0.05-0.1 C variance seen elsewhere.

In C13 at 18:00, kitchen reads 23.25 C while second_bedroom is 23.34 C and living_room is 23.28 C. Here it is actually lower, but at 18:05 it drops to 23.19 C while others stay higher (23.31/23.22/23.33), showing inconsistent tracking relative to peers.

The sensor does not exhibit a 'stuck' pattern, but the lack of perfect synchronization with adjacent rooms might indicate minor calibration drift.

Temperature differences between rooms (especially kitchen vs bedrooms) can be caused by localized heat sources (appliances, lighting) or airflow differences, so divergence alone is not definitive proof of sensor malfunction.

The variations are small (<0.3 C) and do not constitute a safety risk or critical failure.

False positive or nuisance alarm event associated with the kitchen smoke alarm, potentially interfering with system monitoring or causing user confusion, though the sensor itself appears functional.

C13 shows `kitchen_smoke_alarm` entering `TestInProgress = true` at 18:45:00 and completing self-test at 18:45:30.

While self-tests are normal maintenance, the presence of this event in the logs alongside the query about sensor health suggests investigating if the smoke alarm triggered any false occupancy or environmental alerts that might be conflated with the temperature sensor's status.

Note: This hypothesis focuses on the *system* anomaly in the kitchen area, as the temperature sensor itself shows no faults.

Self-tests are explicitly designed behaviors and not faults unless they fail repeatedly or trigger actual alarms (which they did not; `ExpressedState` returned to 0).

This does not directly explain any issue with the *temperature* sensor's accuracy or operation.

Absence of explicit fault codes or stuck values for kitchen_temp_sensor in C00 and C13.

Consistent raw integer scaling (e.g., 2268 -> 22.68 C) indicating correct protocol interpretation.

Presence of a scheduled self-test for the smoke alarm in C13, which is a benign operational event.

Longer-term historical data to establish a baseline for 'normal' temperature variance in the kitchen specifically.

Information on whether the kitchen has active heat-generating appliances during the logged periods to contextualize temperature spikes/drops.

Confirmation of whether the smoke alarm self-test was user-initiated or automatic, and if any errors occurred during the test (logs show success).

The investigator correctly interpreted Matter-scaled temperature values (centi-degrees) and did not fall for false-alarm traps regarding literal high temperatures.

The analysis appropriately distinguishes between the target device (kitchen_temp_sensor) and other devices (smoke alarm), noting that the smoke alarm self-test is a benign operational event.

The evidence provided in C00 and C13 shows normal thermal inertia and fluctuation patterns for the kitchen sensor, with no stuck values, connectivity drops, or impossible transitions.

While minor drift was noted as a hypothesis, it is correctly identified as likely environmental rather than a fault, given the small magnitude (<0.3C) and lack of other fault indicators.

The conclusion that the sensor is working normally is supported by the absence of direct fault evidence.

## 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。

## Matter Notes
- These logs follow Matter-style smart-home event semantics.
- TemperatureMeasurement.MeasuredValue is represented in centi-degrees Celsius in this benchmark: 2466 means 24.66 C, not 2466 C.
- BooleanState and other protocol booleans should be interpreted using transitions and surrounding events, not naive natural-language assumptions from a single isolated value.
- OccupancySensing.Occupancy uses 0=unoccupied and 1=occupied.
- DoorLock.LockState is an enumerated state; formatted logs may show both the label and the raw code.
- A device-fault conclusion requires direct fault evidence such as stuck values, repeated non-recovery, explicit alarm/fault events, or impossible state transitions. Scaled temperature values alone are not enough.

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

## Deterministic Signals
{
  "room_activity": {
    "living_room": 336,
    "master_bedroom": 336,
    "second_bedroom": 336,
    "kitchen": 293,
    "bathroom": 48,
    "entrance": 48
  },
  "attribute_frequency": {
    "MeasuredValue": 1152,
    "Occupancy": 240,
    "TestInProgress": 2,
    "ExpressedState": 2
  },
  "lock_state_flips": 0,
  "occupancy_events": 240,
  "temperature_patterns": [],
  "value_format_hints": {
    "temperature": "MeasuredValue is shown as Celsius with the raw integer preserved in parentheses.",
    "occupancy": "0=unoccupied, 1=occupied",
    "lock_state": "enumerated lock state rendered as label + raw code"
  }
}

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

## 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。

## Matter Notes
- These logs follow Matter-style smart-home event semantics.
- TemperatureMeasurement.MeasuredValue is represented in centi-degrees Celsius in this benchmark: 2466 means 24.66 C, not 2466 C.
- BooleanState and other protocol booleans should be interpreted using transitions and surrounding events, not naive natural-language assumptions from a single isolated value.
- OccupancySensing.Occupancy uses 0=unoccupied and 1=occupied.
- DoorLock.LockState is an enumerated state; formatted logs may show both the label and the raw code.
- A device-fault conclusion requires direct fault evidence such as stuck values, repeated non-recovery, explicit alarm/fault events, or impossible state transitions. Scaled temperature values alone are not enough.

## Triage
{
  "primary_task_profile": "device-health",
  "secondary_task_profile": "none",
  "query_anchor": {
    "target_rooms": [
      "kitchen"
    ],
    "target_devices": [
      "kitchen_temp_sensor"
    ],
    "target_question": "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。"
  },
  "focus_rooms": [
    "kitchen"
  ],
  "focus_devices": [
    "kitchen_temp_sensor"
  ],
  "focus_chunk_ids": [
    "C00",
    "C13"
  ],
  "suspected_patterns": [
    "sensor_stuck_value",
    "missing_data",
    "impossible_state_transition"
  ],
  "why_these_chunks": [
    "C00 provides the initial baseline readings for the kitchen temperature sensor to establish normal operation.",
    "C13 shows a significant spike in 'alarmish_count' (19) and includes 'kitchen_smoke_alarm' in top devices, which may correlate with or mask sensor behavior, requiring inspection for fault indicators like stuck values or explicit alarms."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "Kitchen temperature sensor is functioning normally. The readings show typical thermal inertia and gradual changes consistent with a stable indoor environment, without any signs of hardware failure or data corruption.",
      "evidence": [
        "C00: Kitchen temp sensor values fluctuate between 22.67 C and 23.13 C over 80 minutes, showing natural variation rather than being stuck at a single value.",
        "C13: Kitchen temp sensor values range from 22.92 C to 23.31 C, maintaining consistency with other room sensors (living room, bedrooms) which are all in the 22-23 C range.",
        "No explicit fault codes, alarm events, or connectivity drops a


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 temperature and occupancy sensors are operating normally with no evidence of hardware faults or data anomalies.

Explanation: Temperature sensor (`living_room_temp_sensor`) readings fluctuate naturally between 22.69°C and 24.44°C over the 5-hour period, showing no stuck values, impossible jumps, or drift beyond physical limits.

Explanation: Occupancy sensor (`living_room_occupancy`) consistently reports 'unoccupied' (raw=0) at all sampled timestamps, which is a valid state for an empty room.

Explanation: No explicit fault events, alarms, or communication errors were recorded for these devices in the provided logs.

Explanation: While an external signal mentioned 'activity', the absence of cross-referenced presence indicators (like door locks or other motion sensors triggering) means the 'unoccupied' status cannot be definitively classified as a detection failure without further evidence; thus, the device behavior is considered normal.

Temperature values range from 22.69 C to 24.44 C with regular updates every 5 minutes.

OccupancySensing.Occupancy remains raw=0 (unoccupied) throughout the entire log duration.

No immediate action required.
Continue routine monitoring.

Temperature values for `living_room_temp_sensor` fluctuate between 22.69 C and 24.44 C over the 5-hour period, showing no stuck values or impossible jumps.

Occupancy status remains consistently at `unoccupied` (raw=0) for all reported timestamps in C00-C03.

No explicit fault, alarm, or error events are present in the logs for these devices.

The frequency of temperature updates (every 5 minutes) is regular and consistent with standard polling intervals.

The hypothesis assumes that 'unoccupied' is the correct state; if people were present but not detected, this would be a detection failure rather than a total malfunction, which is harder to prove without external verification.

The occupancy sensor may have a detection sensitivity issue or blind spot, failing to detect presence if occupants were in the room. While the device itself isn't 'broken' (it reports unoccupied), it might be providing misleading data regarding room usage.

The structured signal indicates `living_room` has 403 activity events, which is significant, yet the focused chunks only show `unoccupied` states. This discrepancy suggests either the activity events are from other sensors (e.g., motion detectors not logged here) or the occupancy sensor is missing detections.

However, looking closely at the provided chunks, there are NO `occupied` transitions recorded for `living_room_occupancy`. If the 403 activity metric refers to general room activity (potentially including non-motion sources or aggregated data), the lack of any `occupied` flag in the specific occupancy sensor logs is notable.

If the 403 activity count implies human presence, the persistent `unoccupied` reading could indicate the sensor is insensitive or misconfigured.

The query specifically asks about the *sensors* working normally. A sensor reporting 'unoccupied' when the room is empty is normal behavior. Without evidence that the room *was* occupied during these times (which the logs don't explicitly confirm via other means like door locks or other sensors triggering), we cannot definitively claim a malfunction. The 'activity' count in signals might refer to network traffic or other metrics, not necessarily human presence detected by this specific sensor.

The temperature sensor shows no signs of malfunction (stuck values, drift beyond physical limits).

There is no anomaly. The system is operating as designed.

All temperature readings are physically plausible and change gradually.

All occupancy readings are consistent with a quiet night/early morning period where the living room might indeed be empty.

No error codes or communication failures are observed.

The complete absence of any `OccupancySensing.Occupancy = occupied` (raw=1) events for `living_room_occupancy` across all four chunks (C00-C03).

The consistency of temperature readings with normal environmental changes, ruling out hardware failure like stuck sensors.

External ground truth on whether anyone was actually in the living room during the 00:00-05:00 period to verify the occupancy sensor's accuracy.

Logs for other potential presence indicators (e.g., TV power state, smart plug usage) to cross-reference with the occupancy sensor.

The investigator correctly identified that the temperature sensor values are within normal physical ranges (22-24°C) and fluctuate naturally, ruling out hardware faults like 'stuck' sensors or impossible jumps.

The occupancy sensor consistently reports 'unoccupied' (raw=0). While the investigator noted a potential discrepancy with an external 'activity count' of 403, they correctly reasoned that without explicit ground truth of presence in the logs, this cannot be classified as a device fault. A sensor reporting 'unoccupied' when no one is there is correct behavior.

No explicit fault events, alarms, or communication errors were found for the target devices in chunks C00-C03.

The conclusion that the sensors are working normally is supported by the absence of direct fault evidence. The hypothesis of 'detection failure' remains speculative without cross-referenced presence data (e.g., door locks, other motion sensors) confirming presence during the log period.

The analysis adheres to the protocol: scaled temperatures were interpreted correctly, and boolean states were evaluated based on consistency rather than isolated values.

## 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。

## Matter Notes
- These logs follow Matter-style smart-home event semantics.
- TemperatureMeasurement.MeasuredValue is represented in centi-degrees Celsius in this benchmark: 2466 means 24.66 C, not 2466 C.
- BooleanState and other protocol booleans should be interpreted using transitions and surrounding events, not naive natural-language assumptions from a single isolated value.
- OccupancySensing.Occupancy uses 0=unoccupied and 1=occupied.
- DoorLock.LockState is an enumerated state; formatted logs may show both the label and the raw code.
- A device-fault conclusion requires direct fault evidence such as stuck values, repeated non-recovery, explicit alarm/fault events, or impossible state transitions. Scaled temperature values alone are not enough.

## Layout
Layout: 三室两厅 (3BR)
- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>
- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>
- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>
- kids_room: 儿童房温度传感器<temperature_sensor>, 儿童房灯<dimmable_light>, 儿童房窗帘<window_covering>, 儿童房窗户传感器<contact_sensor>, 儿童房运动传感器<occupancy_sensor>
- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>
- living_room: 客厅主灯<dimmable_light>, 客厅副灯<dimmable_light>, 客厅氛围灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘1<window_covering>, 客厅窗户传感器1<contact_sensor>, 客厅窗户传感器2<contact_sensor>, 客厅运动传感器<occupancy_sensor>
- master_bathroom: 主卫漏水传感器<water_leak_detector>, 主卫灯<onoff_light>, 主卫运动传感器<occupancy_sensor>
- master_bedroom: 主卧床头灯<onoff_light>, 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>
- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>
- second_bedroom: 次卧灯<dimmable_light>, 次卧空调<air_conditioner>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>

## Deterministic Signals
{
  "room_activity": {
    "living_room": 403,
    "master_bedroom": 520,
    "kids_room": 521,
    "kitchen": 303,
    "dining_room": 224,
    "second_bedroom": 48,
    "master_bathroom": 60,
    "entrance": 227,
    "second_bathroom": 1
  },
  "attribute_frequency": {
    "MeasuredValue": 1160,
    "Occupancy": 1098,
    "On

## 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。

## Matter Notes
- These logs follow Matter-style smart-home event semantics.
- TemperatureMeasurement.MeasuredValue is represented in centi-degrees Celsius in this benchmark: 2466 means 24.66 C, not 2466 C.
- BooleanState and other protocol booleans should be interpreted using transitions and surrounding events, not naive natural-language assumptions from a single isolated value.
- OccupancySensing.Occupancy uses 0=unoccupied and 1=occupied.
- DoorLock.LockState is an enumerated state; formatted logs may show both the label and the raw code.
- A device-fault conclusion requires direct fault evidence such as stuck values, repeated non-recovery, explicit alarm/fault events, or impossible state transitions. Scaled temperature values alone are not enough.

## Triage
{
  "primary_task_profile": "device-health",
  "secondary_task_profile": "none",
  "query_anchor": {
    "target_rooms": [
      "living_room"
    ],
    "target_devices": [
      "living_room_temp_sensor",
      "living_room_occupancy"
    ],
    "target_question": "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。"
  },
  "focus_rooms": [
    "living_room"
  ],
  "focus_devices": [
    "living_room_temp_sensor",
    "living_room_occupancy"
  ],
  "focus_chunk_ids": [
    "C00",
    "C01",
    "C02",
    "C03"
  ],
  "suspected_patterns": [
    "sensor_stuck_value",
    "missing_data",
    "impossible_state_transition"
  ],
  "why_these_chunks": [
    "C00-C03 cover the initial period of the logs, allowing inspection of baseline behavior and any immediate anomalies in the living room temperature sensor readings and occupancy status.",
    "These chunks contain the highest density of events for the target devices in the early timeline, providing sufficient data points to detect stuck values or communication failures."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The living room temperature sensor and occupancy sensor are functioning normally. The temperature readings show expected natural fluctuations within a comfortable indoor range (22-24°C), and the occupancy sensor correctly reports 'unoccupied' throughout the period, consistent with the low activity count in the living room compared to other areas.",
      "evidence": [
        "Temperature values for `living_room_temp_sensor` fluctuate between 22.69 C and 24.44 C over the 5-hour period, showing no stuck values or impossible jumps


DF-06-FP: 窗帘正常移动但速度慢

The master_bedroom occupancy and temperature sensors are functioning normally; the observed behavior is consistent with standard Matter protocol reporting and physical environmental changes.

Explanation: 1. Temperature Sensor Health: The `master_bedroom_temp_sensor` reports values that change gradually (e.g., from 24.32°C at 05:05 to 25.09°C at 06:55). There are no stuck values, impossible jumps, or data gaps, indicating the sensor hardware and reporting mechanism are healthy.

Explanation: 2. Occupancy Sensor Functionality: The `master_bedroom_occupancy` sensor correctly transitions from 'unoccupied' (raw=0) to 'occupied' (raw=1) at 06:04:00. This event triggers the associated light (`master_bedroom_light`) to turn on at 06:04:10, confirming the sensor's detection logic and system integration are working as intended.

Explanation: 3. Reporting Frequency Analysis: The repeated 'occupied' logs (e.g., 06:09, 06:14, 06:19...) represent periodic state confirmations or polling updates, which is normal behavior for smart home protocols to maintain state consistency. There is no evidence of rapid flickering (instability) or failure to report.

Explanation: 4. Absence of Faults: No explicit error codes, alarm events, or communication failures are present in the logs for these devices.

master_bedroom_occupancy transitioned from unoccupied (0) to occupied (1) at 2026-06-22T06:04:00.

master_bedroom_light turned on at 2026-06-22T06:04:10, confirming successful trigger response.

Temperature readings show smooth, continuous variation without stuck values or anomalies.

No action required; sensors are operating within normal parameters.

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

Checking early chunks helps establish if there are persistent issues from the start of the log sequence.

master_bedroom_occupancy transitions from 'unoccupied' (raw=0) to 'occupied' (raw=1) at 2026-06-22T06:04:00.

This occupancy change is immediately followed by master_bedroom_light turning on at 06:04:10, indicating correct system integration.

Temperature readings for master_bedroom_temp_sensor remain within a realistic range (22.76 C to 25.09 C) and fluctuate gradually without sudden jumps or stuck values.

No explicit fault codes, alarm events, or communication errors are present in the logs for these devices.

The initial assessment period (00:00-05:00) only showed the room as unoccupied, so the sensor's ability to detect presence was not tested until later.

Without knowing the exact physical location of the sensor relative to the bed, we cannot rule out minor blind spots, though the detection at 06:04 suggests general functionality.

Potential intermittent connectivity or reporting delay in the master_bedroom occupancy sensor, evidenced by multiple rapid re-confirmations of the 'occupied' state shortly after the initial trigger, which could indicate signal instability or debounce issues.

At 06:04:00, master_bedroom_occupancy becomes occupied.

Subsequent logs show repeated updates for the same state: 06:09:00 (occupied), 06:14:00 (occupied), 06:19:00 (occupied), 06:24:00 (occupied), 06:29:00 (occupied).

While occupancy sensors often poll frequently, the frequency of explicit log entries for a static 'occupied' state (every ~5 minutes) might suggest a polling mechanism that is either aggressive or recovering from a transient drop, although this is also consistent with standard Matter reporting intervals.

Frequent reporting of a stable state is normal behavior for many smart home protocols to ensure consistency; it does not inherently indicate a fault.

There is no evidence of the sensor failing to report or reporting incorrect states (e.g., flickering between 0 and 1 rapidly).

Possible false positive or delayed detection if the occupant entered earlier than 06:04 but the sensor did not register until then, potentially due to sensitivity settings or placement. However, given the light turned on, the system responded to the detection event.

The first 'occupied' signal appears at 06:04:00.

Prior to this, all other rooms were unoccupied, and the house was quiet.

If the user woke up significantly before 06:04 (e.g., 05:30) and moved around, the lack of prior occupancy signals would be anomalous.

However, there is no data to confirm movement before 06:04, making this speculative.

It is highly probable the occupant entered the room or became active exactly at 06:04.

No contradictory evidence exists to prove the occupant was present earlier.

The transition of master_bedroom_occupancy from raw=0 to raw=1 at 2026-06-22T06:04:00, followed by the master_bedroom_light turning on at 06:04:10, confirms the sensor is responsive and integrated correctly.

The absence of any 'fault', 'error', or 'alarm' messages in the structured logs or focused chunks for the master_bedroom sensors.

Temperature values for master_bedroom_temp_sensor (e.g., 24.32 C at 05:05, 24.84 C at 06:05) show smooth, continuous variation without spikes or drops indicative of hardware failure.

Context on typical wake-up times for occupants to verify if the 06:04 detection time is expected.

Configuration details of the occupancy sensor (e.g., timeout settings, sensitivity) to determine if the reporting frequency is normal.

Logs from other sensors in the immediate vicinity (e.g., master_bathroom) to cross-reference activity patterns.

Verify temperature sensor continuity in C04/C05 to ensure no data gaps or stuck values occurred after the initial period.

Analyze occupancy reporting frequency in C04/C05 to distinguish between normal Matter polling intervals and potential signal instability/debounce issues flagged by the investigator.

Check for any explicit fault codes or communication errors in the later chunks that might have been missed in the initial review.

The investigator correctly identified the target devices and interpreted Matter-scaled temperatures accurately (no false alarm risk on value interpretation).

However, the investigation is incomplete. The 'Focused Chunks' provided only cover up to 05:00 (C03), but the critical event (occupancy transition) happens at 06:04 (in C04).

The investigator's output references evidence from C04/C05 (e.g., 06:04 transition, repeated occupancy updates), but these chunks were not included in the 'Focused Chunks' list provided in the prompt context for this round, or the analysis was based on a preview not fully detailed here.

Crucially, the hypothesis A1 regarding 'intermittent connectivity' relies on observing the pattern of repeated 'occupied' logs (06:09, 06:14, etc.). This pattern exists in C04/C05. Without reviewing these specific chunks, we cannot confirm if this is normal protocol behavior or a fault.

We need to explicitly check C04 and C05 to validate the 'normal vs. faulty' distinction for the occupancy sensor's reporting rate and to ensure the temperature sensor remained stable during the occupied phase.

Current verdict is premature; further refinement is needed to rule out the 'sensor_malfunction' hypothesis definitively.

The master bedroom sensors (temperature and occupancy) are functioning normally. The temperature readings show expected gradual fluctuations consistent with a residential environment at night, and the occupancy sensor correctly reports 'unoccupied' throughout the period.

master_bedroom_temp_sensor reports valid temperature values ranging from 22.76 C to 24.35 C over the 5-hour window.

Temperature changes are gradual (e.g., +0.03 C per 5 mins), consistent with thermal inertia in a bedroom.

Values are within reasonable physical bounds for an indoor environment.

master_bedroom_occupancy consistently reports 'unoccupied' (raw=0), which is plausible for a bedroom during late night/early morning hours (00:00-05:00).

No explicit fault codes, alarms, or stuck-value patterns (constant identical values for extended periods) are observed in the logs.

The analysis is limited to the first 5 hours; faults could manifest later.

Without ground truth of actual room conditions, we assume the readings are accurate, but cannot rule out minor drift without comparison to other sensors.

Potential sensor drift or calibration issue in the master bedroom temperature sensor, as it consistently reads slightly higher than adjacent rooms (living room, kids room) during the early morning hours, though this may be due to location differences.

At 04:55, master_bedroom_temp_sensor reads 24.26 C while living_room reads 24.40 C and kitchen reads 24.41 C.

At 04:40, master_bedroom reads 24.32 C while living_room reads 24.29 C.

Generally, the master bedroom temperature tracks closely with other rooms but occasionally diverges slightly (e.g., 03:00: MB 23.72 vs Living 23.53).

However, these differences are small (<0.2 C) and could be explained by HVAC zoning, sunlight exposure, or sensor placement.

Differences are within typical sensor tolerance and environmental variance.

No evidence of 'stuck' values or non-recovery.

Matter notes explicitly state scaled temperature values alone are not enough for a device-fault conclusion.

The pattern is not inconsistent enough to definitively claim malfunction without more data or cross-validation.

Occupancy sensor might be failing to detect presence if someone was in the room, but given the time (00:00-05:00), unoccupied status is highly probable, making this a low-probability anomaly unless there is evidence of sleepwalking or unusual activity.

master_bedroom_occupancy remains 0 (unoccupied) for the entire 5-hour period.

If the user sleeps in the master bedroom, this would indicate a failure to detect presence.

However, no conflicting data (like motion from other sensors or user reports) suggests the room was occupied.

It is normal for bedrooms to be unoccupied during these hours.

No evidence contradicts the 'unoccupied' status.

Cannot confirm occupancy without additional context (e.g., bed pressure sensors, user logs).

Consistent 'unoccupied' status for master_bedroom_occupancy across all timestamps in C00-C03.

Gradual, physically plausible temperature changes in master_bedroom_temp_sensor (no stuck values).

Absence of any explicit fault events or alarm codes in the structured signals or raw chunks.

Ground truth occupancy data (e.g., from a wearable or manual log) to verify if the room was actually empty.

Comparison with a known-calibrated reference thermometer in the same room.

Logs from after 05:00 to check for any delayed fault manifestations or recovery behaviors.

HVAC system logs to correlate temperature changes with heating/cooling cycles.

At 06:04:00, master_bedroom_occupancy becomes occupied.

The first 'occupied' signal appears at 06:04:00.

Prior to this, all other rooms were unoccupied, and the house was quiet.

However, there is no data to confirm movement before 06:04, making this speculative.

Check for occupancy transitions in master_bedroom_occupancy after 05:00 (e.g., morning wake-up) to verify sensor responsiveness.

Verify if temperature readings remain physically plausible and consistent with other sensors during active hours.

Look for explicit fault events or communication errors in the full log sequence.

The investigator correctly identified that the current data (00:00-05:00) shows no obvious faults like stuck values or impossible transitions.

However, concluding 'normal' based solely on a static 'unoccupied' state and gradual temperature changes is insufficient for a definitive health check. A critical test for an occupancy sensor is its ability to detect presence when it occurs (e.g., someone entering the room).

The logs provided only cover the night period where the room is expected to be empty. We need to see if the sensor works when the room becomes occupied (likely in C04/C05 onwards).

Without observing a transition from unoccupied to occupied (or vice versa), we cannot rule out a 'blind' sensor or a sensor that fails to trigger.

Therefore, the investigation must continue to later chunks to observe dynamic behavior.

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

## Matter Notes
- These logs follow Matter-style smart-home event semantics.
- TemperatureMeasurement.MeasuredValue is represented in centi-degrees Celsius in this benchmark: 2466 means 24.66 C, not 2466 C.
- BooleanState and other protocol booleans should be interpreted using transitions and surrounding events, not naive natural-language assumptions from a single isolated value.
- OccupancySensing.Occupancy uses 0=unoccupied and 1=occupied.
- DoorLock.LockState is an enumerated state; formatted logs may show both the label and the raw code.
- A device-fault conclusion requires direct fault evidence such as stuck values, repeated non-recovery, explicit alarm/fault events, or impossible state transitions. Scaled temperature values alone are not enough.

## Layout
Layout: 三室两厅 (3BR)
- balcony: 洗衣机<laundry_washer>, 阳台灯<onoff_light>, 阳台门传感器<contact_sensor>
- dining_room: 餐厅灯<dimmable_light>, 餐厅运动传感器<occupancy_sensor>
- entrance: 入户门传感器<contact_sensor>, 入户门锁<door_lock>, 玄关灯<onoff_light>, 玄关运动传感器<occupancy_sensor>
- kids_room: 儿童房温度传感器<temperature_sensor>, 儿童房灯<dimmable_light>, 儿童房窗帘<window_covering>, 儿童房窗户传感器<contact_sensor>, 儿童房运动传感器<occupancy_sensor>
- kitchen: 厨房温度传感器<temperature_sensor>, 厨房漏水传感器<water_leak_detector>, 厨房灯<onoff_light>, 厨房灶具<cook_surface>, 厨房烟雾报警器<smoke_co_alarm>, 厨房窗户传感器<contact_sensor>, 洗碗机<dishwasher>
- living_room: 客厅主灯<dimmable_light>, 客厅副灯<dimmable_light>, 客厅氛围灯<onoff_light>, 客厅温度传感器<temperature_sensor>, 客厅烟雾报警器<smoke_co_alarm>, 客厅空调<air_conditioner>, 客厅窗帘1<window_covering>, 客厅窗户传感器1<contact_sensor>, 客厅窗户传感器2<contact_sensor>, 客厅运动传感器<occupancy_sensor>
- master_bathroom: 主卫漏水传感器<water_leak_detector>, 主卫灯<onoff_light>, 主卫运动传感器<occupancy_sensor>
- master_bedroom: 主卧床头灯<onoff_light>, 主卧温度传感器<temperature_sensor>, 主卧灯<dimmable_light>, 主卧空调<air_conditioner>, 主卧窗帘<window_covering>, 主卧窗户传感器<contact_sensor>, 主卧运动传感器<occupancy_sensor>
- second_bathroom: 次卫漏水传感器<water_leak_detector>, 次卫灯<onoff_light>
- second_bedroom: 次卧灯<dimmable_light>, 次卧空调<air_conditioner>, 次卧窗帘<window_covering>, 次卧窗户传感器<contact_sensor>, 次卧运动传感器<occupancy_sensor>

## Deterministic Signals
{
  "room_activity": {
    "living_room": 403,
    "master_bedroom": 526,
    "kids_room": 517,
    "kitchen": 303,
    "dining_room": 219,
    "second_bedroom": 48,
    "master_bathroom": 222,
    "entrance": 225,
    "second_bathroom": 1
  },
  "attribute_frequency": {
    "Occupancy": 1254,
    "MeasuredValue": 1156,

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

## Matter Notes
- These logs follow Matter-style smart-home event semantics.
- TemperatureMeasurement.MeasuredValue is represented in centi-degrees Celsius in this benchmark: 2466 means 24.66 C, not 2466 C.
- BooleanState and other protocol booleans should be interpreted using transitions and surrounding events, not naive natural-language assumptions from a single isolated value.
- OccupancySensing.Occupancy uses 0=unoccupied and 1=occupied.
- DoorLock.LockState is an enumerated state; formatted logs may show both the label and the raw code.
- A device-fault conclusion requires direct fault evidence such as stuck values, repeated non-recovery, explicit alarm/fault events, or impossible state transitions. Scaled temperature values alone are not enough.

## Triage
{
  "primary_task_profile": "device-health",
  "secondary_task_profile": "none",
  "query_anchor": {
    "target_rooms": [
      "master_bedroom"
    ],
    "target_devices": [
      "master_bedroom_occupancy_sensor",
      "master_bedroom_temp_sensor"
    ],
    "target_question": "判断 master_bedroom 区域的传感器是否工作正常。如果异常，请说明可能的故障类型。"
  },
  "focus_rooms": [
    "master_bedroom"
  ],
  "focus_devices": [
    "master_bedroom_occupancy_sensor",
    "master_bedroom_temp_sensor"
  ],
  "focus_chunk_ids": [
    "C00",
    "C01",
    "C02",
    "C03"
  ],
  "suspected_patterns": [
    "sensor_stuck_value",
    "missing_data",
    "impossible_state_transition"
  ],
  "why_these_chunks": [
    "C00-C03 cover the initial period (00:00-05:00) where baseline behavior and any immediate faults (like stuck values or missing data) would be evident. The preview lines show consistent temperature readings and occupancy transitions, which are key indicators for health checks.",
    "Checking early chunks helps establish if there are persistent issues from the start of the log sequence."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The master_bedroom sensors (occupancy and temperature) are functioning normally. The occupancy sensor correctly detected the transition from unoccupied to occupied at 06:04, triggering associated lights. Temperature readings show physically plausible gradual changes consistent with a sleeping environment warming up slightly or ambient fluctuations.",
      "evidence": [
        "master_bedroom_occupancy transitions from 'unoccupied' (raw=0) to 'occupied' (raw=1) at 2026-06-2


状态 vs 实际位置不一致

The bedroom temperature and occupancy sensors are functioning normally; observed behaviors such as brief occupancy detection and light activation are consistent with normal user activity.

Explanation: 1. Temperature Sensor Analysis: The `bedroom_temp_sensor` data (C00-C04) shows a smooth, monotonic increase from ~21.7°C to ~24.4°C over the morning period. The rate of change is physically plausible for an unoccupied room heating up. There are no stuck values, impossible jumps, or sensor drift anomalies. Brief periods where the value remains constant (e.g., 22.99°C in C02) correspond to the standard 5-minute polling interval, not a hardware fault.

Explanation: 2. Occupancy Sensor Analysis: The `bedroom_occupancy` sensor transitions to 'occupied' at 06:29:00 and back to 'unoccupied' at 06:31:42. This short duration (~2.5 minutes) correlates perfectly with the `bedroom_light` turning on at 06:29:02, indicating a valid automation trigger based on real user presence. The subsequent return to 'unoccupied' is consistent with PIR sensor behavior after a person leaves the field of view.

Explanation: 3. Actuator Context: While the `bedroom_light` remained on until 07:28:05 (approx. 1 hour), this is an actuator/automation configuration issue, not a sensor fault. The query specifically asks about the *sensors*. The sensors correctly reported the state changes that triggered the event.

Explanation: 4. Conclusion: Both sensors exhibit expected behavior patterns without evidence of malfunction, stuck states, or data corruption.

Temperature readings show smooth thermal inertia (21.7°C to 24.4°C) with no stuck values.

Occupancy transition to 'occupied' at 06:29:00 immediately triggers `bedroom_light` ON at 06:29:02.

Occupancy returns to 'unoccupied' at 06:31:42, consistent with user exit.

Review automation rules for `bedroom_light` timeout settings if the long duration is unintended.

判断 bedroom 区域的传感器是否工作正常，如有异常说明故障类型

判断 bedroom 区域的传感器是否工作正常，如有异常说明故障类型

No 'stuck' values or impossible jumps are observed in the temperature data.

The rate of change (~0.3-0.4°C per 5 mins) is physically plausible for a passive indoor environment.

None identified regarding the temperature sensor itself.

The bedroom occupancy sensor is functioning normally; the brief 'occupied' state (06:29-06:31) corresponds to a user entering the room, triggering the light, and then leaving or moving out of detection range.

At 06:29:00, `bedroom_occupancy` transitions to occupied (raw=1).

Immediately following this, at 06:29:02, `bedroom_light` turns on, indicating a logical automation trigger based on occupancy.

At 06:31:42, `bedroom_occupancy` returns to unoccupied (raw=0), which is a standard behavior for PIR sensors after a person leaves the field of view or stops moving.

The duration (~2.5 minutes) is consistent with a short visit or movement within the room before exiting the sensor's zone.

Subsequent logs show the room remaining unoccupied until the end of the log, which is consistent with the user having left the bedroom area.

Without knowing the exact layout and sensor placement, it's hard to rule out sensitivity issues, but the event sequence is logically coherent.

Potential false positive or ghost detection by the bedroom occupancy sensor, though less likely given the correlated light activation.

The occupancy event was very short (approx. 2.5 minutes). If the user did not enter/leave during this specific window, it could be a glitch.

However, the simultaneous light turn-on makes a simple glitch less likely than a valid detection followed by quick exit.

The correlation with the light turning on strongly suggests a real event rather than a random fault.

No repeated false positives were observed in the provided chunks.

Actuator failure: The bedroom light remained on for an extended period (from 06:29 to 07:28) without manual intervention or auto-off, potentially indicating a failed automation or stuck actuator.

If the automation is set to turn off after a short timeout (e.g., 5-10 mins), the light staying on for an hour indicates either a configuration error, a missed off-command, or a manual override that wasn't logged as such.

Note: The query asks about *sensors*, but this actuator behavior is a related system anomaly worth noting if 'work normally' implies the whole ecosystem.

It is possible the user manually kept the light on or left the room with the light on intentionally.

The logs do not show any 'off' commands being sent and failing, only the final state change.

The transition of `bedroom_occupancy` to occupied at 06:29:00 immediately followed by `bedroom_light` turning on at 06:29:02 confirms the occupancy sensor triggered a valid action.

The return to unoccupied at 06:31:42 shows the sensor correctly detected the absence of motion/person again.

The temperature sensor shows no anomalies in its data stream.

Automation rules: What is the configured timeout for the bedroom light to turn off after occupancy ends?

User activity logs: Did the user actually enter and leave the bedroom between 06:29 and 06:31?

Sensor model specifications: What is the typical debounce/detection time for this specific PIR sensor?

Verify if the 'stuck' temperature values in C02/C03 (e.g., 22.99°C for 10 mins) are due to sensor reporting intervals or actual hardware freeze.

Check for correlation between bedroom_occupancy transitions and other room activities to rule out cross-talk or ghost detections.

Confirm if the light staying on until 07:28 was manual or automated, as this affects the interpretation of occupancy duration.

The investigator correctly identified that the temperature data is physically plausible and not a false alarm based on scaled values.

However, the investigation is incomplete because it stops at C03 (ending ~07:14), while the provided logs include C04 (07:15-08:55).

In C03, there are periods where `bedroom_temp_sensor` reports identical values for extended periods (e.g., 22.99°C from 03:45 to 03:50, then 22.94°C). While likely due to polling intervals, the investigator did not explicitly confirm the reporting frequency or rule out a 'stuck' value fault in those specific windows.

Crucially, the `bedroom_light` turns off at 07:28:05 in C04. The investigator's analysis of the light anomaly (A2) relies on data from C04 which was not included in their focus chunks (C00-C03). Therefore, the conclusion about the light/automation behavior is based on missing evidence in the current review scope.

To definitively conclude 'normal', we need to see if the temperature sensor resumes normal variation in C04 and if the occupancy sensor shows any further erratic behavior after the initial event.

Bedroom temperature and occupancy sensors are functioning normally. The temperature readings show expected diurnal variation (rising from ~21.7°C to ~24.0°C) consistent with the living room and kitchen trends, indicating no sensor drift or stuck values. Occupancy transitions (unoccupied -> occupied -> unoccupied) align with logical user behavior (waking up, leaving the room).

Temperature values for bedroom_temp_sensor change continuously across all chunks (C00-C03), e.g., 21.72 -> 21.69 -> ... -> 24.11 C.

No explicit fault codes or alarm events in the logs.

Occupancy state changes at 06:29 (occupied) and 06:31/07:01 (unoccupied) correlate with light activation and bathroom activity, suggesting a coherent household routine.

Raw integer values correctly map to Celsius (e.g., raw=2400 is 24.00 C), showing no scaling errors.

The short duration of 'occupied' status (approx. 2 minutes) might be unusual for a full wake-up routine, but could represent a brief check or passing through.

Sensor Malfunction / False Positive Triggering: The bedroom occupancy sensor may be overly sensitive or malfunctioning, triggering 'occupied' status briefly without sustained presence, potentially causing unnecessary actuator commands (light on) followed by rapid deactivation. This is supported by the very short 'occupied' window (06:29-06:31) compared to typical usage patterns.

bedroom_occupancy transitions to 'occupied' (raw=1) at 06:29:00.

bedroom_light turns 'on' immediately after at 06:29:02.

bedroom_occupancy returns to 'unoccupied' (raw=0) just 2 minutes later at 06:31:42.

No other significant activity (like prolonged light-on or HVAC changes) suggests the occupant did not stay in the room long enough to justify the initial trigger as a standard 'wake up' event.

It is plausible the user entered, checked something, and left quickly, which is normal behavior rather than a fault.

The temperature sensor shows no anomalies, so if there is a fault, it is isolated to the occupancy logic or PIR sensitivity.

Actuator Stuck / Logic Error: The bedroom light turned on at 06:29:02 but there is no corresponding 'off' command logged for the bedroom light in the provided chunks. While the occupancy sensor reset, the light state remains unknown/unlogged as off. If the light remained on, this would indicate an actuator control failure or missing log entry.

bedroom_light | OnOff.OnOff = on (raw=True) at 06:29:02.

No subsequent 'bedroom_light | OnOff.OnOff = off' event appears in C03 (ends at 07:14:05).

Other lights (bathroom) have clear on/off cycles, making the absence of a bedroom light off event notable.

The query specifically asks about *sensors*. The light is an actuator. A missing log line doesn't prove the light is physically stuck, only that the log doesn't show it turning off.

The user might have manually turned it off, or it might have been controlled by a different mechanism not fully captured in the specific attribute frequency summary, though the log seems comprehensive.

The sequence of bedroom_occupancy transitioning to 'occupied' at 06:29:00 and back to 'unoccupied' at 06:31:42, lasting only ~2.5 minutes.

The immediate correlation of this occupancy spike with bedroom_light turning 'on' at 06:29:02.

The lack of a corresponding 'off' event for the bedroom light in the provided log segment.

Log entries for bedroom_light after 06:29:02 to confirm if it was turned off automatically or manually.

Context on whether the user was actually present in the bedroom during the 06:29-06:31 window (e.g., via audio or other sensors).

No 'stuck' values or impossible jumps are observed in the temperature data.

The rate of change (~0.3-0.4°C per 5 mins) is physically plausible for a passive indoor environment.

At 06:29:00, `bedroom_occupancy` transitions to occupied (raw=1).

Verify if the bedroom light turned off in subsequent logs (C04+) to confirm actuator status.

Check for other occupancy sensors or motion triggers that might explain the brief 'occupied' state (e.g., hallway motion, pet activity).

Confirm if the short occupancy duration is a known characteristic of the specific PIR sensor model or if it indicates sensitivity issues.

The investigator correctly identified that temperature data shows no fault (no stuck values, reasonable scaling).

However, the conclusion regarding the occupancy sensor is speculative. The brief 'occupied' window (2 mins) could be normal behavior (user entering briefly) rather than a malfunction. Without evidence of repeated false positives or explicit fault codes, labeling it as 'malfunction' is premature.

The missing log entry for the bedroom light turning off is noted but does not constitute a sensor fault. It requires checking C04+ to see if the light was manually turned off or if the automation failed.

Current evidence is insufficient to definitively label the sensor as faulty. Further investigation into the context of the occupancy event and subsequent device states is needed.

## 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。

## Matter Notes
- These logs follow Matter-style smart-home event semantics.
- TemperatureMeasurement.MeasuredValue is represented in centi-degrees Celsius in this benchmark: 2466 means 24.66 C, not 2466 C.
- BooleanState and other protocol booleans should be interpreted using transitions and surrounding events, not naive natural-language assumptions from a single isolated value.
- OccupancySensing.Occupancy uses 0=unoccupied and 1=occupied.
- DoorLock.LockState is an enumerated state; formatted logs may show both the label and the raw code.
- A device-fault conclusion requires direct fault evidence such as stuck values, repeated non-recovery, explicit alarm/fault events, or impossible state transitions. Scaled temperature values alone are not enough.

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

## Deterministic Signals
{
  "room_activity": {
    "living_room": 401,
    "bedroom": 357,
    "kitchen": 298,
    "bathroom": 59,
    "entrance": 14
  },
  "attribute_frequency": {
    "MeasuredValue": 866,
    "Occupancy": 222,
    "OnOff": 18,
    "StateValue": 5,
    "LockState": 4,
    "CurrentPositionLiftPercent100ths": 3,
    "OperationalStatus": 3,
    "SystemMode": 1,
    "OperationalState": 1,
    "CurrentLevel": 1
  },
  "lock_state_flips": 4,
  "occupancy_events": 222,
  "temperature_patterns": [],
  "value_format_hints": {
    "temperature": "MeasuredValue is shown as Celsius with the raw integer preserved in parentheses.",
    "occupancy": "0=unoccupied, 1=occupied",
    "lock_state": "enumerated lock state rendered as label + raw code"
  }
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-19T00:00:00",
    "end_ts": "2026-06-19T01:50:00",
    "event_count": 80,
    "rooms": {
      "living_room": 27,
      "bedroom": 27,
      "kitchen": 22,
      "bathroom": 4

## 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。

## Matter Notes
- These logs follow Matter-style smart-home event semantics.
- TemperatureMeasurement.MeasuredValue is represented in centi-degrees Celsius in this benchmark: 2466 means 24.66 C, not 2466 C.
- BooleanState and other protocol booleans should be interpreted using transitions and surrounding events, not naive natural-language assumptions from a single isolated value.
- OccupancySensing.Occupancy uses 0=unoccupied and 1=occupied.
- DoorLock.LockState is an enumerated state; formatted logs may show both the label and the raw code.
- A device-fault conclusion requires direct fault evidence such as stuck values, repeated non-recovery, explicit alarm/fault events, or impossible state transitions. Scaled temperature values alone are not enough.

## Triage
{
  "primary_task_profile": "device-health",
  "secondary_task_profile": "none",
  "query_anchor": {
    "target_rooms": [
      "bedroom"
    ],
    "target_devices": [
      "bedroom_temp_sensor",
      "bedroom_occupancy"
    ],
    "target_question": "判断 bedroom 区域的传感器是否工作正常，如有异常说明故障类型"
  },
  "focus_rooms": [
    "bedroom"
  ],
  "focus_devices": [
    "bedroom_temp_sensor",
    "bedroom_occupancy"
  ],
  "focus_chunk_ids": [
    "C00",
    "C01",
    "C02",
    "C03"
  ],
  "suspected_patterns": [
    "sensor_stuck_value",
    "sensor_no_data",
    "impossible_state_transition"
  ],
  "why_these_chunks": [
    "C00-C03 cover the initial period (00:00-07:14) where baseline temperature trends and occupancy states can be established for the bedroom sensor.",
    "These chunks allow checking for immediate anomalies like stuck values or missing data right from the start of the log."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The bedroom temperature sensor is functioning normally, showing expected thermal inertia and gradual changes consistent with an unoccupied room heating up in the morning.",
      "evidence": [
        "Temperature readings for `bedroom_temp_sensor` show a smooth, monotonic increase from ~21.7°C at 00:00 to ~24.4°C by 08:55.",
        "No 'stuck' values or impossible jumps are observed in the temperature data.",
        "The rate of change (~0.3-0.4°C per 5 mins) is physically plausible for a passive indoor environment."
      ],
      "weaknesses": [
        "None identified regarding the temperature sensor itself."
      ]
    },
    {
      "id": "N2",
      "