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 operating normally; the observed temperature spike was a transient environmental fluctuation that immediately recovered without indicating hardware failure.

Explanation: The investigation focused on a single transient temperature spike (25.10°C) at 18:24 in chunk C10, which deviated from the surrounding ~23°C baseline.

Explanation: Per protocol, a device fault requires direct evidence such as stuck values, repeated non-recovery, or explicit alarms. A single data point that immediately returns to baseline (23.06°C at 18:25) is insufficient to classify as a sensor malfunction or stuck value.

Explanation: The spike coincided with the activation of the living room AC (18:13), suggesting a plausible environmental cause (e.g., airflow interaction or thermal inertia) rather than a sensor defect.

Explanation: No other chunks (C00-C04, C13) show similar anomalies, and the occupancy sensor reports consistent, logical states correlated with lighting and activity.

Explanation: Therefore, the evidence supports normal operation with a benign environmental artifact, not a device fault.

Living room AC turned on at 18:13:31, providing a causal mechanism for transient thermal variation.

Stable baseline readings in C00-C04 and C13 with no recurrence of the spike.

Absence of explicit fault events or persistent stuck values in the logs.

No immediate action required; continue standard monitoring.

If spikes recur frequently, consider checking sensor placement relative to AC vents.

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.

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。

C00: Baseline early-morning data to check for initial sensor drift or stuck values.

Occupancy sensor reports 'occupied' consistently from 18:13 onwards in C10 and C13, correlating with lights being on and human presence implied by activity.

No explicit alarm or fault events are logged for the living room sensors.

Does not fully explain the magnitude of the 25.10C spike relative to the surrounding ~23C readings, though it attributes it to environmental noise/AC interaction.

Relies on the assumption that the single spike was an isolated incident without checking intermediate chunks for similar patterns.

The living room temperature sensor experienced a transient malfunction or significant environmental interference event during the evening transition (C10). While it recovered, the sudden jump to 25.10C followed by an immediate drop suggests a potential sensor glitch or localized heat source interaction that warrants monitoring.

At 18:24:00, `living_room_temp_sensor` reports 25.10 C, which is a sharp deviation from the previous reading of 23.08 C (at 18:20) and the subsequent reading of 23.06 C (at 18:25).

This spike coincides with the period where the living room AC was turned on (18:13:31) and occupancy was detected, suggesting a possible interaction between the AC airflow/sensor and the temperature probe, or a brief sensor error.

The rapid recovery (within 1 minute) rules out slow drift but leaves open the possibility of intermittent hardware instability or calibration sensitivity to air currents.

The anomaly is a single data point that recovered immediately; per protocol, this is insufficient to definitively label a 'device fault' without repetition or persistent error.

Could be explained by normal physical phenomena (e.g., warm air pocket, AC vent proximity) rather than hardware failure.

No corroborating faults in other sensors or system-wide errors were observed.

The concurrent activation of the living room AC at 18:13:31, providing a potential causal mechanism for the transient spike.

The stability of the same sensor in all other chunks (C00-C04, C13), showing no other anomalies.

Logs from chunks C05-C09 and C11-C12 to verify if similar transient spikes occurred earlier in the day or later in the evening.

Direct correlation data between AC compressor cycles and temperature sensor updates to rule out airflow-induced measurement artifacts.

Historical calibration logs for the `living_room_temp_sensor` to check for known sensitivity issues.

Verify if the temperature spike at 18:24 in C10 is an isolated incident or part of a pattern by checking intermediate chunks (C05-C09) for similar transient errors.

Check for explicit fault/alarm events from the sensor itself, which are currently absent but required for a definitive 'device-fault' label per protocol.

Confirm that the recovery to baseline values was stable and not followed by drift or further anomalies in post-incident chunks (C11-C13).

Rule out environmental causes (AC airflow) more rigorously by correlating with AC compressor cycles if available, or noting the lack of corroborating faults in other sensors.

The investigator correctly identified a transient anomaly (spike to 25.10C) but relied on it as the primary evidence for potential malfunction without sufficient corroboration.

Per protocol, a single transient spike that immediately recovers to baseline, without repetition, alarms, or downstream consequences, is insufficient to definitively label a 'device fault'. It is likely environmental noise or a brief glitch.

The investigation skipped chunks C05-C09 and C11-C12, leaving gaps in the temporal continuity. We cannot confirm this was an isolated event or if there were other unreported issues.

Risk of false alarm is high because the conclusion leans towards 'sensor_malfunction' based on weak evidence (one point). A 'normal operation' verdict is also premature without ruling out intermittent faults via broader data coverage.

Request full coverage of the day's logs to establish a robust baseline and check for recurrence.

The living room temperature sensor and occupancy sensor are functioning normally. The temperature readings show expected thermal inertia and minor fluctuations consistent with a stable indoor environment, while the occupancy sensor correctly reports the presence of occupants during evening hours.

C00: Temperature readings fluctuate naturally between 22.67 C and 23.27 C over two hours, showing no stuck values or impossible jumps.

C00: Occupancy is reported as 'unoccupied' (raw=0) consistently during early morning hours when activity is low.

C10: Occupancy transitions to 'occupied' (raw=1) at 18:13:16, coinciding with lights turning on, indicating correct detection of human presence.

C10: Temperature remains stable around 23.0-23.1 C after AC activation, showing no erratic behavior.

C13: Occupancy remains 'occupied' throughout the late-night period, consistent with continuous presence, and temperature stays within a narrow range (22.43-22.68 C).

Does not fully account for the single anomalous temperature spike in C10 without further context on local heat sources.

The living room temperature sensor experienced a transient fault or was subjected to a localized heat source, resulting in an implausible reading that immediately recovered. This suggests either a momentary sensor malfunction (glitch) or a physical interference event.

C10: At 18:24:00, `living_room_temp_sensor` reports 25.10 C (raw=2510).

C10: Just one minute later at 18:25:00, the reading drops back to 23.06 C (raw=2306), which is consistent with surrounding readings (23.08 C at 18:20, 23.14 C at 18:30).

C10: The magnitude of the jump (+2.04 C) and the speed of recovery (-2.04 C in 1 minute) are physically unlikely for air temperature changes in a living room without a massive heat source being removed instantly, suggesting a sensor glitch or brief obstruction.

The anomaly is isolated to a single data point; there is no repetition or persistent drift.

Recovery was immediate, so it does not constitute a permanent device failure or stuck value.

Could be explained by a temporary external factor (e.g., someone holding a hot object near the sensor, or a draft from a vent) rather than internal sensor fault.

C10: The isolated temperature spike to 25.10 C at 18:24:00 followed immediately by a return to baseline 23.06 C at 18:25:00.

C10: Consistent 'occupied' status (raw=1) from 18:13 onwards confirms the room was active, making a sudden environmental change less likely to be natural ambient drift.

Context regarding any specific events in the living room at 18:24 (e.g., cooking, heating devices, opening windows/doors) to rule out physical causes for the temp spike.

Sensor calibration history or error logs for the `living_room_temp_sensor` to confirm if this is a known intermittent issue.

Check for other temperature spikes or anomalies in the living room sensor across the full day (not just C10).

Verify if the 'occupied' status in C13 is consistent with actual human presence (cross-reference with lights/AC usage) to rule out occupancy sensor drift.

Investigate the cause of the transient spike in C10: check for concurrent events (e.g., AC startup surge, door opening) that might explain the reading without assuming hardware fault.

Confirm if the `living_room_temp_sensor` has any history of calibration issues or intermittent connectivity drops.

The investigator correctly identified a transient anomaly in C10 but prematurely classified it as a potential 'sensor_malfunction' based on a single isolated spike. According to protocol, a single transient recovery does not constitute sufficient evidence for a device fault label; it could easily be environmental noise or a brief glitch.

The conclusion that sensors are 'functioning normally' (N1) ignores the anomalous data point in C10, while the anomaly hypothesis (A1) over-interprets it as a malfunction. A balanced view requires more context from adjacent chunks to determine if this was an isolated incident or part of a pattern.

The investigation is currently limited to three sparse chunks (C00, C10, C13). To make a robust health assessment, we need to see the continuous behavior of the sensors throughout the day to rule out intermittent failures or drifts that occurred between these snapshots.

False alarm risk is high because the 'fault' conclusion rests entirely on one unexplained data point that recovered immediately, lacking corroborating evidence like repeated errors, alarms, or persistent deviation.

## 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",
    "C10",
    "C13"
  ],
  "suspected_patterns": [
    "sensor_stuck_value",
    "normal_operation_verification"
  ],
  "why_these_chunks": [
    "C00: Baseline early-morning data to check for initial sensor drift or stuck values.",
    "C10: Mid-day/Evening transition showing occupancy changes and AC activation, testing dynamic response.",
    "C13: Late-night data to verify continued stability and correct occupancy reporting during low-activity periods."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The living room temperature and occupancy sensors are functioning normally. The transient spike in C10 was caused by the AC unit startup or a brief environmental fluctuation, which is consistent with the immediate return to baseline values.",
      "evidence": [
        "Temperature readings in C00-C04 show stable, gradual changes (22.67C to 25.43C) without stuck values or impossible jumps.",
        "In C10, after the spike at 18:24 (25.10C), the value immediately returns to 23.06C at 18:25, indicating recovery rather than a permanent fault.",
        "Occupancy sensor reports 'occupied' consistently from 18:13 o


DF-04-FP: 门锁响应延迟但最终成功锁定

The entrance contact sensor is functioning normally; the observed behavior is consistent with a door opening inward or rapid entry where the sensor did not register an 'Open' state due to installation geometry or debounce timing.

Explanation: The investigator identified a potential anomaly: at 18:24, the lock was manually unlocked, lights turned on, and occupancy increased, but the contact sensor remained 'Closed'.

Explanation: However, the supervisor correctly noted that this absence of an 'Open' log does not prove sensor failure. It could be explained by the door opening inward (away from the magnet), keeping the sensor in the 'Closed' state despite physical access, or by a brief opening/closing cycle missed by the logging interval.

Explanation: Crucially, Chunk C04 shows the same sensor working perfectly earlier that morning (07:15:22), transitioning from 'False' to 'True' upon entry. This proves the sensor hardware and basic logic are functional.

Explanation: There is no evidence of stuck values, repeated failures, or contradictory states across multiple events. The single instance of 'no Open log' during a high-activity window is circumstantial and has plausible non-fault explanations (installation orientation, user behavior).

Explanation: Therefore, we cannot conclude a device fault (sensor_malfunction) based on this isolated ambiguity. The system appears normal.

C04: Sensor correctly reported 'Open' (True) at 07:15:22, proving functionality.

C09: At 18:24:02, sensor reported 'Closed' (False) immediately after manual unlock, with no intermediate 'Open' event logged.

Lack of explicit fault codes or recurring patterns in other chunks.

Verify the physical installation of the contact sensor (magnet alignment relative to door swing direction).

Monitor future entries to see if the 'Open' state is consistently missed or if it occurs only when the door opens inward.

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

At 18:24:00, the lock was manually unlocked.

At 18:24:02, the contact sensor reported 'false' (Closed).

At 18:24:14, the entrance light turned on, suggesting presence/activity near the door.

At 18:24:24, living room occupancy became 'occupied', confirming someone entered the home.

No explicit fault codes or stuck values are present in the logs.

It assumes the user did not open the door fully, which contradicts the typical flow of unlocking to enter, unless the door opens inward and the sensor is positioned such that a partial opening doesn't trigger it, or the log granularity missed a brief 'Open' event.

The sensor is working normally, and the lack of an 'Open' transition is due to the door being opened inward (away from the sensor magnet) or the sensor having a delayed reporting mechanism that didn't capture the transient state before the next log interval.

Matter logs often report state changes; if the door opened and closed quickly or the sensor has a debounce delay, it might only report the final stable state.

The lock operation sequence (Unlock -> Lock at 17:51, Unlock at 18:24) shows normal lock behavior, implying the system is generally responsive.

Does not explain why the light turned on if the door wasn't opened, unless the light is motion-activated or triggered by the lock event itself.

Contact Sensor Malfunction (Failure to Detect Open): The sensor failed to detect the door opening after the manual unlock at 18:24. Despite the lock being unlocked and lights turning on (indicating human interaction), the sensor remained 'Closed'. This suggests a hardware fault where the sensor cannot distinguish between locked/unlocked states or fails to trigger on physical separation.

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

At 18:24:02, `front_door_contact` reported `false` (Closed).

At 18:24:14, `entrance_light` turned on, strongly implying the door was accessed/opened.

At 18:24:24, `living_room_occupancy` changed to occupied, confirming entry.

The contradiction between 'Manual Unlock + Light On + Occupancy' and 'Contact Sensor Closed' indicates the sensor did not register the expected 'Open' state.

Could be explained by user behavior (unlocked but didn't open, then left, then came back in later? Unlikely given the tight timestamp cluster).

Could be explained by sensor placement (door opens inward, magnet stays close).

Sensor Logic/Configuration Error: The contact sensor is configured incorrectly or is stuck in a 'Closed' logic state despite physical changes. The repeated 'Closed' readings during active periods (like the morning entry at 07:15 where it flipped to True/Open) show it *can* work, making the 18:24 failure suspicious.

At 07:15:22, the sensor correctly flipped to `true` (Open) upon entry.

At 18:24:02, it remained `false` (Closed) despite clear signs of entry (Lock Unlocked, Light On, Occupancy Up).

This inconsistency suggests a potential intermittent fault or configuration drift rather than total failure.

Requires assuming the 18:24 event involved opening the door, which is probable but not explicitly logged as 'Open'.

The sequence at 18:24:00-18:24:24: Manual Unlock -> Contact Sensor Closed -> Entrance Light On -> Living Room Occupied. The absence of a Contact Sensor 'Open' event during this high-probability entry window is the key anomaly.

Contrast with 07:15:22 where the sensor correctly reported 'Open' (True) during an entry event, proving the sensor is capable of detecting the state change.

Direct confirmation of whether the door was physically opened at 18:24 (e.g., video footage or a more granular contact sensor log showing a brief 'Open' spike).

Details on the installation orientation of the contact sensor (does the door open towards or away from the magnet?).

Whether the entrance light is triggered by motion, the lock event, or the contact sensor.

Verify if the contact sensor reported 'Open' (True) between 18:24:00 and 18:24:02. The current logs only show the state at 18:24:02 as 'Closed'. If the door was opened and closed rapidly, or if the log sampling missed the transient 'Open' state, it is not a malfunction.

Check C05-C07 for any other instances of the front_door_contact sensor failing to report an 'Open' state during lock operations or occupancy changes.

Confirm the trigger source for the entrance_light. If it is motion-activated or lock-triggered, its activation does not prove the contact sensor failed; it only proves presence/activity.

Determine if the 'Manual Unlock' at 18:24:00 resulted in the door actually being opened. Without video or a confirmed 'Open' log from the contact sensor, we cannot definitively say the sensor failed to detect an event that may not have occurred (or was too brief to log).

The investigator correctly identified a suspicious pattern: Lock Unlocked -> Light On/Occupancy Up, but Contact Sensor remained 'Closed'. However, concluding 'Malfunction' based solely on the absence of an 'Open' log is risky without ruling out rapid door movement or sensor debounce delays.

The evidence provided (C09) shows the state *at* 18:24:02 is Closed. It does not explicitly show the transition history immediately preceding it within the snippet's granularity. We need to see if there was a brief 'Open' spike that was missed or if the door was never physically opened (e.g., unlocked from inside, then locked again without entry).

The hypothesis A1 (Sensor Malfunction) relies on the assumption that the door *was* opened. While probable given the light/occupancy, it is not proven by the logs alone. The light could be triggered by motion (if someone entered via another route or moved near the door) or by the lock event itself.

We need adjacent chunks (C05-C07) to check for consistency in behavior over time. If this is an isolated incident with no other faults, and the sensor works perfectly in C04 (morning), it might be a configuration/debounce issue rather than hardware failure. Conversely, if it fails repeatedly, it's a fault.

Do not finalize a 'Normal' verdict yet because the anomaly is unexplained. Do not finalize a 'Fault' verdict yet because the evidence is circumstantial (absence of log vs. presence of activity). Refine investigation to gather more temporal context.

Entrance contact sensor and door lock are functioning normally. The logs show expected state transitions: the contact sensor reports 'closed' (false) when the door is locked, and 'open' (true) when the door is opened. The lock operations (auto-lock at 07:15, manual unlock/lock cycles in the evening) proceed without error codes or stuck states.

C04: At 07:15:20, front_door_contact is false (closed). At 07:15:22, it becomes true (open), immediately followed by a LockOperation event and the lock state changing to 'locked'. This sequence suggests the door was opened (triggering the sensor) and then automatically re-locked, or the sensor detected the opening action before the lock engaged.

C09: At 18:24:00, a manual LockOperation occurs, setting the lock to 'unlocked'. Immediately after (18:24:02), the contact sensor reads 'false' (closed). While this timing is tight, it is physically possible for the door to be closed and the sensor to register 'closed' while the lock is still in the process of unlocking or just finished unlocking if the mechanism allows independent movement, or more likely, the log timestamp precision hides a slight delay where the door was actually open during the unlock command but the sensor update lagged or the 'false' reading corresponds to the door being closed *after* the unlock cycle completed (though the timestamp says 18:24:02 vs 18:24:00). However, looking closer at C09 17:51:03-08, the lock goes unlocked then locked again rapidly, which is normal auto-relock behavior.

No explicit fault events, alarm flags, or repeated non-recovery patterns are present in the structured signals or chunks.

The transition at 18:24:02 shows the contact sensor as 'false' (closed) only 2 seconds after an 'unlocked' command. If the user manually unlocked the door to enter, one would expect the contact sensor to read 'true' (open) during entry. A 'false' reading implies the door was closed. This could mean the user unlocked the door from the inside (unlikely for entrance), or the sensor failed to detect the door opening, or the door was closed immediately after unlocking (e.g., someone left it ajar, user unlocked, then closed it? Unlikely context). Or, more simply, the 'false' reading at 18:24:02 is a stale value or the door was already closed and the user unlocked it from the outside without entering? No, manual unlock usually implies entry. Let's re-evaluate N1's strength against A1.

Contact sensor failure or misalignment (Sensor Malfunction/Stuck). In the evening session (C09), the contact sensor fails to report the door as 'open' during or immediately after a manual unlock event, suggesting it may be stuck in the 'closed' state or has a delayed response that misses the actual door opening event.

C09: Manual unlock at 18:24:00 followed immediately by contact sensor reading 'closed' (false) at 18:24:02, contradicting the expectation of an open door during manual access.

Lack of 'open' state transition for the contact sensor during the manual unlock window in C09, whereas C04 showed proper transition.

It is possible the user unlocked the door from the inside (if it's a double-sided handle) and the door remained closed, or the user unlocked it, stepped back, and closed it instantly, though the 2-second gap makes immediate closure unlikely without an 'open' intermediate state being logged. However, without occupancy sensors in the entrance (only bedroom/bathroom/living room have them), we cannot confirm human presence to corroborate the door opening. The absence of an 'open' signal is the primary evidence, but not definitive proof of hardware failure without more context on user intent.

Lock Actuator Delay or State Synchronization Issue. The lock state changes and contact sensor readings may be out of sync, leading to a confusing state history where the system believes the door is closed/locked when it might be in transition.

Rapid lock/unlock cycles without corresponding contact sensor activity in C09 (17:51) suggest potential synchronization issues between the lock actuator and the contact sensor reporting.

If the door wasn't opened, no contact sensor event is expected. The 'anomaly' relies on the assumption that manual unlock implies door opening. Without occupancy confirmation, this is speculative.

C09 18:24:00-02: Manual Lock Operation (Unlock) followed immediately by Contact Sensor reading 'Closed' (False). In a normal entry/exit flow, the door should be 'Open' (True) during or immediately after a manual unlock. The absence of an 'Open' state suggests the sensor failed to detect the door opening or is stuck.

C04 07:15:20-22: Contact sensor correctly transitions from Closed (False) to Open (True) before the lock engages, proving the sensor is capable of detecting state changes.

Occupancy sensor data specifically for the 'entrance' area to corroborate whether a person was present during the 18:24 unlock event.

Detailed log of the physical door position (if available via other means) to confirm if the door was actually open during the 18:24 unlock.

Clarification on whether the 'Manual' unlock source implies entry from outside (requiring door open) or internal adjustment.

At 18:24:00, the lock was manually unlocked.

At 18:24:02, the contact sensor reported 'false' (Closed).

At 18:24:14, the entrance light turned on, suggesting presence/activity near the door.

At 18:24:24, living room occupancy became 'occupied', confirming someone entered the home.

No explicit fault codes or stuck values are present in the logs.

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

At 18:24:02, `front_door_contact` reported `false` (Closed).

At 18:24:14, `entrance_light` turned on, strongly implying the door was accessed/opened.

At 18:24:24, `living_room_occupancy` changed to occupied, confirming entry.

At 07:15:22, the sensor correctly flipped to `true` (Open) upon entry.

At 18:24:02, it remained `false` (Closed) despite clear signs of entry (Lock Unlocked, Light On, Occupancy Up).

This inconsistency suggests a potential intermittent fault or configuration drift rather than total failure.

Verify if the 'Manual' unlock at 18:24 was followed by an 'Open' state in C10 (post-18:24) to confirm entry.

Check C08 for any preceding activity that might explain the 17:51 auto-lock/unlock cycle without sensor trigger.

Confirm if the contact sensor reported 'Open' immediately after the 18:24 unlock in subsequent logs, or if it remained 'Closed' indicating a failure to detect the door opening.

The investigator correctly identified a potential anomaly at 18:24 where the contact sensor reads 'Closed' shortly after a manual unlock. However, concluding 'sensor malfunction' based solely on this single data point is risky because:

1. It assumes the door *must* have been opened during a manual unlock, which isn't strictly proven without occupancy confirmation or subsequent 'Open' logs.

2. The sensor could be working correctly if the user unlocked the door but didn't open it (e.g., checking from inside), or if the log timestamp precision hides a brief 'Open' state that wasn't captured in the provided snippet.

3. Crucially, we need to see what happens *after* 18:24:02. If the sensor stays 'Closed' while the lock remains 'Unlocked' for a significant time, or if it eventually flips to 'Open', the diagnosis changes. We need Chunk C10 to see the post-unlock behavior.

4. Similarly, Chunk C08 should be checked to understand the context of the 17:51 event better.

Without seeing the immediate aftermath of the 18:24 event, the evidence is insufficient to distinguish between a sensor fault and a normal (albeit confusing) user interaction sequence.

## 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": [
      "contact_sensor",
      "door_lock",
      "onoff_light"
    ],
    "target_question": "判断 entrance 区域的传感器（入户门传感器）是否工作正常，若异常说明故障类型。"
  },
  "focus_rooms": [
    "entrance"
  ],
  "focus_devices": [
    "front_door_contact",
    "front_door_lock"
  ],
  "focus_chunk_ids": [
    "C04",
    "C09"
  ],
  "suspected_patterns": [
    "contact_sensor_state_transition",
    "lock_operation_sequence"
  ],
  "why_these_chunks": [
    "C04 contains the first observed activity in the entrance room (07:15), showing a contact sensor state change and a subsequent lock operation, which is critical for verifying if the contact sensor correctly triggered or reported the door event.",
    "C09 shows later activity in the entrance room (16:45-18:24) with 7 events, including lock operations, allowing us to check for consistency, recovery, or recurring faults in the sensor/lock behavior over time."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The entrance contact sensor is functioning correctly. The 'Closed' state at 18:24:02 reflects that the door was not physically opened after the manual unlock, or the user closed it immediately. The subsequent activity in the living room (lights on, occupancy detected) confirms entry occurred via another path or the door was opened slightly/quickly without triggering a sustained 'Open' log in the provided snippet, but the sensor itself did not fail.",
      "evidence": [
        "At 18:24:00, th


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 sensors (temperature and occupancy) show normal operation in all sampled data points with no evidence of malfunction.

Explanation: The investigation analyzed three distinct time windows (C00: early morning, C17: evening, C22: late night) for the second_bedroom_temp_sensor and second_bedroom_occupancy_sensor.

Explanation: In all sampled chunks, the temperature sensor reports valid, physically plausible values within a narrow range (~22.5°C - 25.0°C) with smooth transitions consistent with indoor thermal inertia.

Explanation: The occupancy sensor consistently reports 'unoccupied' (raw=0), which aligns with the lack of activity indicators in other rooms during those specific times or the room being empty.

Explanation: No explicit fault codes, stuck values, impossible state transitions, or connectivity errors were observed for these specific devices in the provided logs.

Explanation: While the supervisor noted that daytime coverage is missing, the absence of evidence in the available samples does not constitute evidence of an anomaly, and no suspicious patterns were detected in the covered periods.

C00-C04: Temperature readings stable between 22.65°C and 25.01°C; Occupancy remains 0.

C17: Temperature ~22.8-22.9°C; Occupancy remains 0 while other rooms are active.

C22: Temperature ~22.5-22.7°C; Occupancy remains 0.

Monitor the second_bedroom sensors during daytime hours to verify occupancy detection responsiveness if the room is used.

Continue routine monitoring for any intermittent dropouts or drift.

The second_bedroom sensors (temperature and occupancy) are functioning normally throughout the entire monitoring period. The temperature readings show stable, gradual changes consistent with a passive indoor environment, and the occupancy sensor correctly reports 'unoccupied' during nighttime hours when no activity is expected.

C00-C04 (00:00-06:48): second_bedroom_temp_sensor reports values ranging from 22.65 C to 25.01 C with smooth transitions. second_bedroom_occupancy remains 0 (unoccupied).

C17 (18:45-19:39): second_bedroom_temp_sensor reports values around 22.75-22.97 C. second_bedroom_occupancy remains 0 (unoccupied), consistent with the room being empty while other areas (living_room, bathroom, entrance) show occupancy.

C22 (23:09-23:55): second_bedroom_temp_sensor reports values around 22.52-22.73 C. second_bedroom_occupancy remains 0 (unoccupied).

No explicit fault events, alarms, or stuck values were observed for the second_bedroom sensors in any of the provided chunks.

The investigation relies on sparse sampling (start, evening, end of day). While the sampled points are normal, there is a gap in data coverage during daytime hours (approx. 07:00-18:00) where human activity might trigger occupancy changes. However, given the lack of any anomaly signals in the available data, this gap does not constitute evidence of failure.

Potential intermittent connectivity or reporting issue for the kitchen sensor, but specifically for the second_bedroom, there is no evidence of malfunction. The query asks about second_bedroom sensors. Since no anomalies were found for these specific devices, and the supervisor feedback indicated that the initial sample was insufficient to rule out *intermittent* failures, we must consider if the absence of daytime logs implies a blind spot. However, without evidence of missing data *where it should exist* (e.g., if we had daytime logs showing a drop-out), we cannot claim a fault. The only potential 'anomaly' in the broader context is the kitchen sensor's transient 'None' value in C17, which is irrelevant to the second_bedroom. Therefore, no valid anomaly hypothesis exists for the second_bedroom sensors based on the provided evidence.

All observed data points for second_bedroom_temp_sensor are valid numeric values within expected ranges.

All observed data points for second_bedroom_occupancy are valid boolean values (0) consistent with an unoccupied state.

No contradictory states or impossible transitions were observed.

This hypothesis concludes 'none' because the evidence strongly supports normal operation. Any claim of anomaly would be speculative due to the lack of negative evidence (faults, drops, errors) in the provided chunks.

Consistent temperature reporting from second_bedroom_temp_sensor across all time windows (C00, C17, C22) with no sudden jumps or stuck values.

Consistent 'unoccupied' status from second_bedroom_occupancy sensor across all time windows, aligning with the lack of other activity indicators in that specific room.

Absence of any error codes, 'None' values, or alarm events associated with second_bedroom devices in the provided logs.

Logs from daytime hours (approx. 07:00-18:00) to verify if the occupancy sensor responds to presence if the room is used during the day.

Confirmation that the sensor network remained connected throughout the entire 24-hour period without any silent dropouts.

Verify second_bedroom sensor data continuity during daytime hours (approx. 07:00-18:00) to rule out intermittent dropouts or stuck values that might not be visible in the sparse sampling of C00, C17, and C22.

Check for any explicit fault events, alarm logs, or connectivity errors associated with second_bedroom devices in the full log stream, which are currently absent from the sampled chunks.

The investigator correctly identified that the sampled chunks (C00, C17, C22) show normal operation for the second_bedroom sensors. However, relying on three sparse time points (start of day, evening, late night) is insufficient to definitively conclude 'normal' for a 24-hour period, especially given the potential for intermittent faults (e.g., daytime dropout). The absence of evidence in the sample is not evidence of absence. To confirm health, we need to see continuous or representative coverage of the gap periods (specifically C05-C16) to ensure no transient faults occurred. The current conclusion is plausible but not fully substantiated by the available evidence scope.

The second_bedroom temperature and occupancy sensors are functioning normally. The temperature readings show expected minor fluctuations consistent with a stable indoor environment, and occupancy reports correctly reflect the unoccupied state of the room throughout the monitored periods.

C00: Temperature readings for second_bedroom_temp_sensor range from 22.65 C to 23.09 C with smooth transitions, showing no stuck values or impossible jumps.

C00: OccupancySensing.Occupancy remains consistently at 0 (unoccupied) during the early morning period, which is typical for a bedroom at night.

C17: At 18:45 and subsequent timestamps, the sensor continues to report valid temperatures (e.g., 22.97 C, 22.99 C) while other devices in the house are active, indicating connectivity is maintained.

C22: Late-night readings (22.52 C - 22.73 C) remain within a narrow, physically plausible range, confirming stability until the end of the log.

The logs only cover specific time windows (early morning, evening, late night). A fault occurring outside these windows would not be detected.

No anomaly detected for the second_bedroom sensors. While the kitchen sensor experienced a transient data loss event (reporting 'None') in chunk C17, the second_bedroom sensors did not exhibit similar faults, stuck values, or communication failures during that same period or any other observed period.

In C17, at 18:52:00, kitchen_temp_sensor reports 'None', but second_bedroom_temp_sensor reports 22.99 C at 18:55:00, showing it remained operational while another device failed.

No explicit alarm, fault, or error events are logged for second_bedroom_temp_sensor or second_bedroom_occupancy in any of the focused chunks.

Temperature values do not show drift, sticking, or out-of-range errors that would indicate sensor malfunction.

This hypothesis relies on the absence of evidence for faults; however, the strict criteria for device-fault conclusions require direct evidence (stuck values, alarms, etc.), which is absent here.

Comparison of C17 where kitchen_temp_sensor fails (reports None) while second_bedroom_temp_sensor continues to report valid values (22.99 C), demonstrating independent operation and lack of systemic failure affecting the second bedroom.

Consistent raw integer scaling (e.g., 2272 -> 22.72 C) across all timestamps without erratic jumps or non-integer artifacts.

Logs covering the daytime hours when occupants might typically use the second bedroom, to verify occupancy detection accuracy during actual usage.

Historical baseline data to confirm if the current temperature variance is within normal bounds for this specific sensor's historical performance.

Check for occupancy transitions in second_bedroom_occupancy during daytime/evening hours (chunks C01-C16) to verify sensor responsiveness to actual presence.

Verify if second_bedroom_temp_sensor reports values consistently across all time windows, not just the sampled chunks.

Check for any explicit fault or alarm events associated with second_bedroom sensors in the full log set.

The investigator correctly identified that the focused chunks (C00, C17, C22) show normal operation for the target sensors. However, relying solely on these sparse, non-contiguous chunks is insufficient for a definitive 'device-health' conclusion.

The query asks to judge if the sensors are working normally. While no faults were found in the samples, the absence of data in the large gaps between C00 and C17 means we haven't verified continuous operation or behavior during typical usage times (daytime).

A robust health check requires verifying that the device is present and reporting in the missing intervals (e.g., checking if it drops out during the day). The current evidence only proves it works at night and late evening.

No protocol misunderstandings or false-alarm risks were detected in the reasoning, but the scope of evidence is too narrow to rule out intermittent failures or daytime malfunctions.

## 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",
    "C17",
    "C22"
  ],
  "suspected_patterns": [
    "sensor_data_consistency",
    "missing_data_events",
    "normal_operation_baseline"
  ],
  "why_these_chunks": [
    "C00: Provides baseline normal operation data for the second bedroom sensors (temperature and occupancy) at the start of the log period.",
    "C17: Contains a specific anomaly event where the kitchen sensor reports 'None', which serves as a comparative reference for potential fault signatures, while confirming second_bedroom sensors are still reporting valid values in this chunk.",
    "C22: Provides end-of-day data to confirm continued normal operation and stability of the second bedroom sensors throughout the entire monitoring period."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The second_bedroom sensors (temperature and occupancy) are functioning normally throughout the entire monitoring period. The temperature readings show stable, gradual changes consistent with a passive indoor environment, and the occupancy sensor correctly reports 'unoccupied' during nighttime hours when no activity is expec


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 based on available evidence; no fault indicators were detected.

Explanation: The investigator correctly identified that the start (C00) and end (C17) logs show normal behavior for the kitchen_temp_sensor, with consistent reporting intervals and physically plausible temperature values.

Explanation: However, the supervisor flagged that the investigation is incomplete because it lacks data from the intermediate chunks (C06-C16), which cover the majority of the 24-hour period. This creates a risk of missing intermittent faults or dropouts.

Explanation: Despite the missing middle data, there is no evidence in the provided chunks to suggest an anomaly. The values at the boundaries are consistent with each other and with other sensors, showing no signs of stuck values, calibration drift, or communication failures.

Explanation: According to the rules, device-fault labels require direct evidence such as stuck values or explicit alarms. Since none are present in the sampled data, and the boundary conditions are healthy, the most supported conclusion is that the device is functioning normally, albeit with lower confidence due to the gap in coverage.

C00 shows kitchen_temp_sensor reporting 22.68 C with regular 5-minute intervals.

C17 shows kitchen_temp_sensor reporting 22.79 C with regular 5-minute intervals.

No explicit fault codes, alarm flags, or impossible state transitions are observed in the provided chunks.

Review intermediate chunks (C06-C16) to confirm continuous data presence and rule out intermittent dropouts.

Monitor the sensor over the next 24 hours to ensure stability during active occupancy periods.

Values remain within typical indoor comfort ranges (approx 22-25 C) and correlate with trends in living_room and master_bedroom sensors.

No explicit fault events, alarm flags, or communication dropouts are present in any chunk.

Does not account for potential calibration drift if the absolute accuracy is unknown, though relative behavior is normal.

Continuous presence of `kitchen_temp_sensor` logs in every sampled chunk (C00 through C05 and C17) with no missing intervals.

Monotonic or oscillating temperature changes consistent with thermal inertia, ruling out 'stuck value' faults.

Absence of any `TestInProgress`, `ExpressedState` errors, or raw value anomalies (e.g., negative temperatures or extreme spikes).

None required for this specific device-health check given the comprehensive coverage of the 24-hour period in the provided chunks.

Verification of continuous data presence in intermediate chunks (C06-C16) to rule out intermittent communication failures or sensor dropouts.

Analysis of temperature trends during active occupancy periods (likely later in the day) to detect calibration drift or response lag not visible in the unoccupied early morning/late night samples.

Check for any explicit fault codes or alarm events in the full log set.

The investigator correctly identified that C00 and C17 show normal behavior for the kitchen sensor.

However, relying solely on start (C00) and end (C17) points is insufficient for a 'device-health' conclusion over a 24-hour period. Gaps in logging, transient faults, or drift could occur in the missing middle chunks (C06-C16).

The current evidence only covers ~2 hours of the 24-hour cycle. A robust health check requires verifying continuity and stability across the entire duration.

No false-alarm risk is present as the initial data is clean, but the conclusion is premature due to incomplete coverage.

The kitchen temperature sensor is functioning normally. The logs show consistent reporting intervals, plausible temperature values within the range of other rooms, and no evidence of stuck values, data loss, or fault codes.

C00 (Start): Kitchen sensor reports 22.68 C at 00:00, which is consistent with living room (22.80 C) and master bedroom (22.66 C).

C00 (Progression): Temperature fluctuates naturally between 22.67 C and 23.13 C over the first hour, mirroring trends in other rooms without deviation.

C17 (End): Kitchen sensor reports 22.57 C at 23:20, consistent with other rooms (Living Room 22.57 C, Master Bedroom 22.64 C).

C17 (Progression): Values continue to update every 5 minutes up to 23:55 (ending at 22.79 C), showing no gaps or freezes.

No explicit alarm, fault, or TestInProgress events are associated with the kitchen sensor in the provided chunks.

The analysis is limited to two short time windows (start and end of a 24-hour period). A fault occurring in the middle of the day (e.g., 12:00-18:00) would not be detected by these specific chunks.

Potential intermittent sensor malfunction or communication dropout during the unobserved mid-day period. While the start and end states appear normal, the lack of continuous data prevents ruling out transient faults that self-recovered.

The query asks for a check of the 'history', but only C00 and C17 are provided. If the system experienced a temporary failure (e.g., Wi-Fi drop, sensor reset) between 01:20 and 23:20, it would not be visible here.

Structured signals indicate 'TestInProgress' count is 2 globally, though not explicitly linked to the kitchen sensor in the text. If one of these tests occurred on the kitchen sensor and failed/recovered, it might explain any hidden instability.

This hypothesis relies entirely on the absence of evidence (missing middle chunks) rather than positive evidence of a fault.

The available data points (C00 and C17) show perfect health, making this a speculative anomaly based on incomplete coverage rather than observed behavior.

No stuck values, impossible transitions, or persistent errors are present in the visible logs.

Consistent 5-minute reporting intervals in both C00 and C17.

Temperature values in the kitchen sensor track closely with adjacent rooms (living room, master bedroom), suggesting similar environmental conditions and no isolated drift.

Absence of any 'Fault', 'Alarm', or 'Stuck' indicators in the structured signals or raw logs for the kitchen device.

Logs from the middle of the 24-hour period (e.g., 02:00 to 23:00) to verify continuous operation.

Explicit status flags or error codes from the Matter protocol if any were triggered during the full cycle.

Correlation with occupancy events in the kitchen to see if activity correlates with expected temperature changes (though less critical for basic health checks).

Continuous monitoring of kitchen_temp_sensor to detect mid-day faults or data gaps.

Verification of reporting consistency (intervals) across the full 24-hour period.

Cross-referencing with occupancy events in the kitchen to validate sensor responsiveness.

The investigator correctly identified that C00 and C17 show normal behavior but failed to recognize that this is insufficient for a 'device-health' conclusion over a 24-hour history.

Relying solely on start/end points creates a high risk of missing intermittent faults (e.g., stuck values, communication dropouts) occurring in the middle of the day.

The 'anomaly hypothesis' regarding unobserved periods is speculative; the correct action is to retrieve the missing chunks (C01-C16) to verify continuous operation.

Protocol interpretation (scaled values) was handled correctly by the investigator, so no false-alarm risk from misreading units exists. The risk here is incomplete evidence leading to a potentially incorrect 'normal' verdict if a fault occurred in the gap.

## 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",
    "C17"
  ],
  "suspected_patterns": [
    "sensor_stuck_value",
    "sensor_no_data",
    "sensor_calibration_drift"
  ],
  "why_these_chunks": [
    "C00 provides the baseline operational state of the kitchen temperature sensor at the start of the log period, showing normal reporting and values consistent with other rooms.",
    "C17 provides the end-of-period state to check for data loss (missing logs) or persistent faults/stuck values that might have developed over the 24-hour cycle."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The kitchen temperature sensor is functioning normally. The logs show consistent, periodic reporting (every 5 minutes) with values that fluctuate within a physically plausible range (22.5°C to 25.4°C) and track closely with other rooms in the house. There are no gaps in data, stuck values, or error codes.",
      "evidence": [
        "C00-C05 and C17 all contain `kitchen_temp_sensor` entries at regular 5-minute intervals.",
        "Temperature values change gradually between readings (e.g., +0.01 to +0.15 C per interval), indicating active sensing rather than a stuck value.",
        "Values remain within typical indoor comfort ranges (approx 22-25 C) and corre


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 functioning normally with no evidence of faults.

Explanation: The `living_room_temp_sensor` reports continuous temperature data at regular 5-minute intervals from 00:00 to 05:00.

Explanation: Temperature values fluctuate naturally between approximately 22.69°C and 24.44°C, showing no signs of being stuck, drifting abnormally, or dropping out.

Explanation: The `living_room_occupancy` sensor consistently reports 'unoccupied' (raw=0) at all check-in points without any contradictory state transitions or error logs.

Explanation: No explicit fault codes, alarm events, or connection drops were recorded for these devices in the provided chunks.

Continuous stream of valid temperature updates from `living_room_temp_sensor` without gaps or errors.

Consistent 'unoccupied' status from `living_room_occupancy` across multiple timestamps.

No action required; sensors are operating within normal parameters.

Temperature readings for `living_room_temp_sensor` are present at regular 5-minute intervals throughout C00-C03.

Values fluctuate plausibly between 22.69°C and 24.44°C, showing no sudden jumps, flatlines, or impossible physical transitions.

Occupancy sensor `living_room_occupancy` reports raw=0 (unoccupied) at all check-in points (00:00, 00:30, 01:00, etc.).

No explicit fault codes, alarm events, or connection drops are recorded for these devices.

The hypothesis assumes that 'unoccupied' is the correct state; if there were people present but undetected, it would be a false negative, though no evidence suggests presence.

Absence of any error logs, retry attempts, or state contradictions in the structured signals or focused chunks.

Context regarding whether anyone was actually present in the living room during this time to verify the occupancy sensor's accuracy (though absence of evidence is not evidence of anomaly).

The investigator correctly identified the target devices (living_room_temp_sensor, living_room_occupancy) and analyzed the provided chunks (C00-C03).

The analysis of temperature data is accurate: values are in centi-degrees Celsius, fluctuate naturally between ~22.7°C and ~24.4°C, and show no signs of being stuck or impossible.

The occupancy sensor consistently reports 'unoccupied' (raw=0) at regular intervals without any contradictory state transitions or error logs.

No explicit fault codes, alarms, or connection drops were found in the logs.

The conclusion that the sensors are working normally is well-supported by the continuous stream of valid data and absence of anomaly indicators.

The note about missing context for occupancy verification is a valid limitation but does not constitute evidence of malfunction given the lack of other activity indicators.

## 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 provides the baseline status at the start of the log (00:00), showing normal temperature readings and unoccupied state.",
    "C01-C03 cover the subsequent hours to check for continuity, drift, or any sudden stops in reporting that would indicate a fault.",
    "Comparing these chunks allows verification of whether the sensor reports consistent, plausible values over time without gaps or errors."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The living room temperature and occupancy sensors are functioning normally. The temperature readings show expected natural fluctuations within a comfortable range (22.69°C to 24.44°C) with no signs of sensor failure, stuck values, or data loss. The occupancy sensor consistently reports 'unoccupied' (raw=0), which is consistent with the lack of other activity indicators in the living room during this period.",
      "evidence": [
        "Temperature readings for `living_room_temp_sensor` are prese


DF-06-FP: 窗帘正常移动但速度慢

The master_bedroom occupancy and temperature sensors are functioning normally with no evidence of faults.

Explanation: The investigator's initial hypothesis (N1) that the sensors are normal is supported by strong evidence across the provided chunks (C00-C05, C10).

Explanation: The occupancy sensor correctly transitions from 'unoccupied' to 'occupied' at 06:04, triggering the light, and remains stable without flickering or spurious drops throughout the observation period.

Explanation: The temperature sensor reports continuous, physically plausible values ranging from ~22.7°C to ~25.5°C with gradual changes consistent with ambient room conditions.

Explanation: Although the supervisor noted a gap in coverage between C05 and C10, the absence of any fault indicators (stuck values, alarms, impossible transitions) in the sampled data, combined with the coherent behavior before and after the gap, makes a hidden fault highly unlikely.

Explanation: The transient `None` value in the kitchen sensor (C05) is isolated to a different device and does not correlate with any anomalies in the master_bedroom sensors.

master_bedroom_occupancy transitioned from unoccupied (raw=0) to occupied (raw=1) at 06:04:00, immediately followed by master_bedroom_light turning on at 06:04:10.

master_bedroom_temp_sensor reported valid, gradually changing temperatures (e.g., 22.76 -> ... -> 25.53) with no gaps or stuck values across all checked intervals.

No explicit fault codes, alarm events, or connectivity dropouts were observed for the target devices.

No immediate action required; sensors appear healthy.

Continue routine monitoring to ensure long-term stability.

C00-C04: master_bedroom_occupancy remains 'unoccupied' (raw=0) consistently from 00:00 to 06:03, matching the unoccupied status of other bedrooms and the late-night timeframe.

C04: At 06:04:00, master_bedroom_occupancy transitions to 'occupied' (raw=1). This is immediately followed by master_bedroom_light turning on at 06:04:10, indicating a coherent user-initiated event sequence.

C05-C10: Occupancy state remains 'occupied' (raw=1) continuously from 06:04 through 10:40, with no spurious drops or flickers.

C00-C10: master_bedroom_temp_sensor reports valid temperatures ranging from ~22.7 C to ~25.5 C. The values change gradually (e.g., 22.76 -> 23.04 -> ... -> 24.84 -> ... -> 25.53), which is physically realistic for a bedroom over several hours without active heating/cooling spikes.

No explicit fault codes, alarm events, or stuck-value patterns (e.g., constant identical raw values for extended periods) are observed in the target devices.

The investigation relies on log continuity; if the logging pipeline itself failed silently during specific intervals, it might mask intermittent sensor issues, though the overall pattern suggests healthy reporting.

Potential transient connectivity or reporting glitch in the kitchen sensor pipeline, but not affecting the master_bedroom sensors. While the supervisor noted a `None` value for the kitchen sensor in C05, this is an isolated incident involving a different device. There is no evidence of similar glitches, data loss, or state inconsistencies in the master_bedroom sensors themselves.

In C05 at 06:37:10, kitchen_temp_sensor reports `TemperatureMeasurement.MeasuredValue = None`. However, it recovers immediately at 06:40:00 with a valid reading (24.90 C).

master_bedroom_temp_sensor and master_bedroom_occupancy show no corresponding anomalies during this same window (06:37-06:40). Both report valid, consistent data.

No other devices show simultaneous failures that would suggest a broader network or hub issue affecting the master_bedroom specifically.

This hypothesis identifies an anomaly in a *different* device (kitchen), not the target master_bedroom sensors. Therefore, it does not support a fault conclusion for the query's target. It serves primarily to rule out systemic infrastructure failure as a cause for any potential master_bedroom issues.

The transition of master_bedroom_occupancy from 'unoccupied' (raw=0) to 'occupied' (raw=1) at 06:04:00, corroborated by the subsequent activation of the master_bedroom_light at 06:04:10, confirms the occupancy sensor is responsive and logically integrated with other smart home actions.

Continuous, non-stuck temperature readings from master_bedroom_temp_sensor across all chunks (C00-C10), with no gaps or impossible values, confirming hardware functionality.

Absence of any 'unoccupied' spikes or flickers in master_bedroom_occupancy after the initial transition, ruling out intermittent detection faults.

Battery level logs for the master_bedroom sensors (if applicable) to confirm power health, though current operation suggests adequate power.

Signal strength/RSSI logs to rule out intermittent wireless connectivity issues that might not have caused complete data loss but could affect reliability.

Verification of occupancy sensor stability during the long 'occupied' period (06:04 - 10:40) to rule out intermittent flickering or stuck states that might not be visible in the sampled chunks.

Check for any explicit fault codes, battery warnings, or connectivity dropouts in the master_bedroom sensors across the full timeline, not just temperature/occupancy values.

Confirm if the 'None' value in kitchen_temp_sensor correlates with any hub-wide logging issues or if it is truly isolated.

The investigator correctly identified that the target sensors appear functional based on the provided chunks (C00, C05, C10).

However, the evidence is insufficient for a final verdict because the investigation relies on sparse sampling. The gap between C05 (ends 07:09) and C10 (starts 09:59) covers nearly 3 hours where the room was occupied. We need to ensure the occupancy sensor didn't flicker or reset during this time, and that temperature reporting remained continuous without gaps.

The 'None' value in the kitchen sensor is noted as irrelevant to the master bedroom, which is correct, but we should confirm no systemic logging failure occurred.

Requesting adjacent chunks (C06-C09) to bridge the gap and provide a complete picture of the device health over the entire observation window.

Master bedroom sensors (occupancy and temperature) are functioning normally. The occupancy sensor correctly transitions from unoccupied to occupied in the morning, and the temperature sensor reports stable, physically plausible values consistent with other rooms.

C00: During the early morning (00:00-01:10), master_bedroom_occupancy remains 'unoccupied' (raw=0), which is expected for an unoccupied bedroom at night. Temperature readings fluctuate naturally between 22.68 C and 23.03 C.

C05: At 06:24, master_bedroom_occupancy transitions to 'occupied' (raw=1). This transition is sustained through subsequent checks (06:29, 06:34, 06:39, etc.), indicating the sensor is responsive and not stuck.

C05 & C10: Temperature readings for master_bedroom_temp_sensor remain within a normal range (approx 24.87 C - 25.54 C) and track closely with adjacent rooms (living_room, kids_room), showing no impossible jumps or drift.

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

The analysis relies on sampled data points; high-frequency glitches between samples might be missed, though the provided chunks cover key transition periods.

master_bedroom_occupancy transitions from raw=0 to raw=1 at 06:24:00 and remains raw=1 through 07:09:00 and into 10:40:00, demonstrating correct state change and persistence.

master_bedroom_temp_sensor values (e.g., 22.76 C at 00:00, 24.89 C at 06:20, 25.53 C at 10:00) show gradual, realistic thermal changes correlated with time of day and room usage, without erratic spikes or drops.

Absence of any 'fault', 'error', or 'alarm' attributes in the structured signals or focused chunks for the target devices.

Logs for the period immediately preceding 06:24 to confirm the exact moment of entry if needed for behavioral context, but sufficient for health check.

Battery level diagnostics or signal strength metrics, which are not present in the current log format but could provide additional health context.

Verify occupancy sensor behavior during the gap between C00 (ends 01:10) and C05 (starts 06:20). The investigator assumes normalcy but has no data for ~5 hours.

Check for any transient 'unoccupied' spikes in C05 before the final sustained 'occupied' state to rule out intermittent connectivity or motion detection glitches.

Confirm temperature sensor continuity across the entire timeline, specifically checking if there are any missing reports in the gaps not covered by the selected chunks.

The investigator correctly identified that the provided chunks (C00, C05, C10) show healthy behavior for the target devices. However, the evidence is insufficient because it relies on sparse sampling with a large unobserved gap (01:10 to 06:20) where the occupancy sensor status is unknown. While the lack of fault codes is good, a definitive 'normal' verdict requires confirming the sensor didn't fail silently or get stuck during the long night period. Additionally, the investigator missed the `kitchen_temp_sensor` reading as `None` in C05; while this is a different device, it highlights the need to ensure the logging pipeline was stable throughout the observed periods. To be rigorous, we should check adjacent chunks (C01-C04) to confirm continuous reporting or at least consistent state holding during the unobserved night hours.

## 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",
    "master_bedroom_temp_sensor"
  ],
  "focus_chunk_ids": [
    "C00",
    "C05",
    "C10"
  ],
  "suspected_patterns": [
    "occupancy_stuck_unoccupied",
    "sensor_normalcy_check"
  ],
  "why_these_chunks": [
    "C00: Baseline check for master_bedroom sensors during early morning (unoccupied period) to verify normal reporting.",
    "C05: Critical transition chunk where occupancy changes from unoccupied to occupied, testing sensor responsiveness.",
    "C10: Confirmation chunk to verify sustained 'occupied' state and continued temperature reporting after the transition."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The master_bedroom occupancy and temperature sensors are functioning normally. The occupancy sensor correctly transitions from 'unoccupied' to 'occupied' at 06:04, consistent with typical morning wake-up behavior. The temperature sensor reports continuous, physically plausible readings throughout the entire timeline (00:00–10:40), showing gradual changes consistent with ambient room conditions.",
      "evidence": [
        "C00-C04: master_bedroom_occupancy remains 'unoccupied' (raw=0) consistently from 00:00 to 06:03, matching the