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 environmental fluctuation that self-corrected immediately.

Explanation: Analysis of C00 (early morning) shows stable baseline temperatures (~22.6-23.3°C) and consistent unoccupied status, indicating normal sensor operation overnight.

Explanation: In C10, the `living_room_temp_sensor` recorded a transient spike to 25.10°C at 18:24, but this value immediately reverted to 23.06°C at 18:25. This single-point deviation without persistence or corroborating safety alarms (e.g., smoke, fire) is characteristic of measurement noise or minor local heat interference, not a hardware fault like 'stuck' or 'drift'.

Explanation: The `living_room_occupancy` sensor demonstrates correct logical integration with actuators (lights/AC turning on upon entry at 18:13) and maintains accurate state transitions throughout the evening (C10 and C13), confirming it is responsive and functional.

Explanation: No evidence of communication failure, data gaps, or impossible state transitions exists for the living room sensors in the provided chunks.

Temperature reading recovered from 25.10°C to 23.06°C within one minute (18:24-18:25), ruling out stuck values.

Occupancy sensor correctly triggered lighting and AC events at 18:13, verifying responsiveness.

Consistent temperature baselines across all three time chunks (C00, C10, C13) with no drift.

No immediate action required; continue routine monitoring.

If similar spikes recur frequently, investigate potential localized heat sources or sensor placement issues.

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。如果异常，请说明可能的故障类型。

C00: Baseline check for temperature sensor stability and occupancy reporting in the early morning.

C13: Check late-night behavior for consistency and potential stuck states or missed transitions.

The spike to 25.10°C at 18:24:00 was isolated; the next reading at 18:25:00 returned to 23.06°C, indicating immediate recovery rather than a persistent fault.

Occupancy transitions (`occupied`/`unoccupied`) align logically with other device states (lights on/off, AC usage) and human activity patterns (evening entry at 18:13, late-night presence at 22:22).

No explicit fault codes, alarm events, or communication errors were logged for the living room sensors.

Does not fully explain the physical cause of the 25.10°C spike, though it attributes it to noise/environmental factors which is plausible.

The living room temperature sensor experienced a momentary glitch or local heat source interference at 18:24, but this does not constitute a functional failure as it self-corrected instantly.

At 18:24:00, `living_room_temp_sensor` reported 25.10°C, which is a ~2°C jump from the previous reading (23.08°C) and inconsistent with the bedroom (22.17°C) and kitchen (23.06°C) sensors in the same timeframe.

This value deviates significantly from the established baseline (~23°C) for the room.

The anomaly was transient (lasted only one data point) and did not persist, failing the criteria for 'stuck value' or 'repeated non-recovery'.

No corroborating evidence of a fire or major heat event (e.g., smoke detector, AC failure) exists.

Per guidelines, a single transient spike without further context is insufficient to declare a device fault; it is more likely noise or minor environmental variance.

The rapid recovery of the temperature reading from 25.10°C back to 23.06°C within one minute (18:24 to 18:25) strongly suggests a transient error or environmental fluctuation rather than a hardware fault.

Consistent correlation between `living_room_occupancy` state changes and lighting/AC actuator commands confirms the occupancy sensor is responsive and logically integrated.

Contextual logs for any specific appliance activation or window/door status at exactly 18:24 to rule out localized heat sources (e.g., direct sunlight, heater blast) causing the spike.

Check for data gaps or missing timestamps in the living room sensors between C00 and C10 (approx. 02:00 to 18:00) to rule out communication failures or sensor power loss.

Verify if the 'None' values in kitchen_temp_sensor (C10) indicate a broader network issue or specific device failure that might correlate with the living room spike.

Investigate the cause of the 25.10°C spike at 18:24 more deeply by checking surrounding actuator states (e.g., was a heater turned on? Was a window opened?) which are not fully detailed in the current chunks.

The investigator correctly identified the transient temperature spike but dismissed it as noise without sufficient evidence from the full day's log. The gap between C00 (ends 01:50) and C10 (starts 18:13) is significant; we need to ensure the sensor didn't fail or go offline during this period.

While the spike self-corrected, a single point of failure analysis is insufficient for a 'device health' verdict. We must confirm continuous operation throughout the unobserved hours.

The risk of false alarm is medium because dismissing a potential hardware glitch based solely on recovery time is risky if the underlying cause (e.g., intermittent connection) persists.

Refinement is needed to cover the entire timeline and rule out systemic issues before concluding the device is healthy.

The living room temperature sensor and occupancy sensor are functioning normally. The temperature readings show expected thermal inertia and gradual changes consistent with a stable indoor environment, while the occupancy sensor correctly reports presence/absence transitions triggered by human activity.

Temperature readings in C00 (00:00-01:50) show a gradual increase from 22.67°C to 23.27°C, which is physically plausible for a room without active cooling/heating or significant heat sources.

In C10 (18:13-19:35), the AC is turned on at 18:13:31. Subsequent temperature readings (e.g., 23.26°C at 18:15, dropping to 23.08°C at 18:20, then fluctuating around 22.9-23.1°C) reflect the expected response time of a thermostat system and thermal mass, not sensor failure.

Occupancy sensor in C10 transitions from unoccupied (implied before 18:13) to occupied at 18:13:16, coinciding with lights and AC turning on, indicating correct correlation with user behavior.

In C13 (22:22-23:45), occupancy remains 'occupied' (raw=1) throughout the period, consistent with people staying in the living room overnight, and temperature remains stable around 22.5°C.

No explicit fault codes, stuck values, or impossible state transitions were observed for the living room sensors.

Does not account for the single transient 'None' value in the kitchen sensor (C10), though this is not a living room device.

Assumes the AC system is working as intended; if the AC was failing, the temperature drop might be slower, but the current data shows a reasonable cooldown.

Potential temporary sensor glitch or communication dropout in the living room temperature sensor during the evening activity period (C10), evidenced by a brief anomalous spike followed by immediate recovery, although it may also be a valid physical event (e.g., direct sunlight or appliance heat).

At 18:24:00 in C10, the living_room_temp_sensor reports 25.10°C, which is a sharp jump from 23.08°C just 4 minutes prior (18:20:00).

This value (25.10°C) is significantly higher than the surrounding readings (~23.0°C) and the bedroom/kitchen sensors (~22.1°C/23.0°C).

However, the very next reading at 18:25:00 drops back to 23.06°C, suggesting a transient error or a very short-lived heat source.

The rapid recovery makes a permanent sensor malfunction unlikely, but a transient glitch is possible.

The spike is isolated and immediately corrected, lacking persistence required for a definitive 'malfunction' classification per guidelines.

It could be explained by a physical cause, such as a person holding a hot object near the sensor, a draft from an open door/window, or a reflection of light, rather than a device fault.

No other sensors in the house showed similar spikes at that exact moment, but cross-room correlation is weak due to different thermal environments.

Possible unattended cooking or fire risk in the kitchen, which indirectly affects the living room environment if ventilation is poor, though the living room sensors themselves appear normal.

In C10, the kitchen_cook_surface turns on at 19:15:30 and stays on until 19:34:00 (approx 19 minutes).

Kitchen temperatures rise sharply from 25.38°C at 19:15 to 26.81°C at 19:25, indicating significant heat generation.

While the living room sensors do not show a corresponding temperature spike (remaining ~22.8-22.9°C), suggesting good isolation or ventilation, the high kitchen activity warrants monitoring.

Note: This hypothesis focuses on the broader context, as the query specifically asks about living room sensors, but A1 is more relevant to the specific device health question.

The living room temperature did not rise, so there is no direct evidence of heat transfer affecting the living room sensors.

The query is specific to living room sensor health, making this a secondary concern.

Living room temperature stability across all chunks (C00, C10, C13) with no persistent drift or stuck values.

Occupancy sensor consistency with user actions (lights/AC on/off) in C10 and continuous presence in C13.

The single transient anomaly at 18:24:00 (25.10°C) in C10, which recovered immediately, is the only potential indicator of a non-permanent issue.

Context for the 18:24:00 temperature spike: Was there any specific event (e.g., oven opening, direct sunlight) occurring at that time?

Sensor calibration history or baseline accuracy metrics for the living room temp sensor.

Network connectivity logs to rule out packet loss causing the transient 'None' or spike.

No explicit fault codes, alarm events, or communication errors were logged for the living room sensors.

This value deviates significantly from the established baseline (~23°C) for the room.

Verify if the transient temperature spike at 18:24 (25.10°C) correlates with any specific event logs (e.g., door opening, appliance usage) in surrounding chunks to rule out environmental causes.

Check for network connectivity issues or packet loss around 18:24 that could cause data corruption or interpolation errors.

Confirm if 'None' values in kitchen sensors indicate a broader system logging issue or isolated device failure.

The investigator correctly identified that the living room sensors are largely functional based on stable readings and logical occupancy transitions.

However, the hypothesis A1 regarding a 'sensor glitch' relies on a single transient spike (25.10°C) which recovered immediately. While flagged as weak, it is not dismissed entirely, creating ambiguity.

Per guidelines, a device-fault conclusion requires direct fault evidence (stuck values, repeated non-recovery). The current evidence shows only one anomalous point without corroboration of a persistent fault.

The investigation should explicitly conclude whether this single spike constitutes a 'fault' or is an acceptable anomaly/noise. If no further evidence supports a fault, the verdict should be 'Normal' with a note on the transient anomaly, rather than leaving it ambiguous.

No additional chunks are strictly necessary if the decision is to classify the single spike as noise/non-fault, but the reasoning must be tightened to avoid false-alarm risk from over-interpreting transient data.

## 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",
    "sensor_no_data",
    "impossible_state_transition"
  ],
  "why_these_chunks": [
    "C00: Baseline check for temperature sensor stability and occupancy reporting in the early morning.",
    "C10: Check for activity-triggered events (AC on, occupancy change) to verify sensor responsiveness during active use.",
    "C13: Check late-night behavior for consistency and potential stuck states or missed transitions."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The living room temperature and occupancy sensors are functioning normally. The transient temperature spike at 18:24 was a brief environmental fluctuation or measurement noise that immediately corrected, consistent with normal sensor behavior in a dynamic environment.",
      "evidence": [
        "Temperature readings for `living_room_temp_sensor` are stable and physically plausible throughout the day (ranging approx. 22.5°C - 23.3°C), showing no signs of drift or stuck values.",
        "The spike to 25.10°C at 18:24:00 was isolated; the next reading at 18:25:00 returned to 23.


DF-04-FP: 门锁响应延迟但最终成功锁定

Entrance sensors (contact and lock) are functioning normally; the observed behavior is consistent with standard operation despite sparse logging.

Explanation: The primary access sensors, `front_door_contact` and `front_door_lock`, demonstrate coherent and logical state transitions in both C04 (morning exit/lock) and C09 (evening entry/unlock). Specifically, the contact sensor correctly reports 'true' upon opening and 'false' upon closing, while the lock state updates appropriately.

Explanation: The empty log entry for `front_door_lock` at 17:51:00 in C09 is a transient artifact that self-corrects within seconds (unlocked -> locked), lacking the persistence or recurrence required to classify as a hardware fault or communication dropout under Matter diagnostic standards.

Explanation: The absence of `entrance_occupancy` logs is attributed to the likely non-existence of such a sensor in the entrance area or its configuration not reporting frequent updates, rather than a malfunction, as no explicit fault codes or impossible states are present.

Explanation: While the supervisor noted incomplete data coverage (missing chunks C00-C03, C10-C13), the available evidence from the two distinct interaction windows shows no anomalies. Without evidence of silent failures in the unobserved periods, the most probable conclusion based on current data is normal operation.

C04: `front_door_contact` transitioned from false to true at 07:15:22, followed by immediate lock operation, indicating correct sensor-actuator correlation.

C09: At 18:24, manual unlock triggered `front_door_contact` to go false and `entrance_light` to turn on, confirming functional linkage.

No stuck values, repeated non-recovery, or explicit alarm events were found for the entrance devices.

Monitor the system over a longer period to confirm if the transient log gap at 17:51:00 recurs, which might indicate intermittent network issues.

Verify if an occupancy sensor is intended for the entrance area; if so, check its configuration or physical installation status.

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

C04: `front_door_contact` transitions from false to true at 07:15:22, followed immediately by `front_door_lock` operation and state change to 'locked'. This indicates a successful locking event after entry/exit.

C09: At 18:24, `front_door_lock` unlocks manually, followed by `front_door_contact` going false (door open), then `entrance_light` turning on. This sequence demonstrates correct sensor-actuator correlation.

No stuck values or impossible state transitions were observed in the contact or lock logs.

The empty log line at 17:51:00 for `front_door_lock` was followed by valid state changes (unlocked -> locked) within seconds, suggesting a transient logging gap or rapid automated cycle rather than a permanent fault.

Does not fully explain the absence of an explicit `entrance_occupancy` or motion sensor log triggering the light, though manual switch or timer remains a plausible alternative.

The `entrance_light` is controlled by a manual switch or a timer/schedule rather than a motion/occupancy sensor, explaining the lack of corresponding occupancy logs despite the light turning on.

In C09, the light turns on at 18:24:14, shortly after the door unlocks and opens. While this could be sensor-triggered, there is no `entrance_motion` or `entrance_occupancy` log in C09 or surrounding chunks (C05-C08) showing an 'occupied' state for the entrance area.

Other rooms (living_room, bedroom) have frequent occupancy updates, but the entrance does not, suggesting either no sensor exists or it is not reporting in the same manner.

Relies on the assumption that if a motion sensor existed, it would report 'occupied' during the brief window of the door opening/lighting up, which might be too short for some sensors to register depending on polling rates.

Potential intermittent communication dropout or logging artifact for the front door lock, indicated by the empty log entry at 17:51:00.

At 17:51:00 in C09, there is a timestamped entry for `front_door_lock` with no attribute value (`[2026-06-12T17:51:00] front_door_lock | `).

This is followed by valid state changes at 17:51:03 (unlocked) and 17:51:08 (locked).

The device recovered immediately; there is no evidence of persistent failure or stuck state.

Single isolated empty lines can be caused by network jitter or log buffering issues rather than hardware faults.

Does not meet the threshold for 'device-fault conclusion' as defined in Matter Notes (requires repeated non-recovery or explicit alarm).

Missing or unreported occupancy sensing for the entrance area, potentially creating a blind spot for security monitoring or automation logic dependent on presence detection.

Despite multiple entries/exits (C04, C09), no `entrance_occupancy` or `entrance_motion` device logs appear in any chunk.

The query specifically asks about 'sensors', and the absence of occupancy data contrasts with the detailed occupancy logs for other rooms.

If the system relies on occupancy for security alerts, this gap represents a functional deficiency.

Absence of evidence is not evidence of malfunction; the sensor may simply not exist or be configured to not report frequently.

The supervisor feedback explicitly notes that speculating on occupancy failure without direct evidence of a missing expected event is weak.

Coherent state transitions in C04 (Contact True -> Lock Locked) and C09 (Lock Unlocked -> Contact False -> Light On) prove the primary access sensors are functionally linked and responding to physical events.

The empty log line at 17:51:00 is the only potential technical anomaly, but it self-corrects rapidly.

Complete absence of `entrance_occupancy` logs across all chunks suggests either no such sensor exists or it is not part of the monitored telemetry stream.

Confirmation of whether an `entrance_motion` or `entrance_occupancy` sensor is physically installed and intended to be part of the active device list.

Clarification on the control mechanism for `entrance_light` (manual vs. sensor) to rule out automation logic errors.

Investigation into the cause of the empty log line at 17:51:00 (e.g., checking raw packet data if available) to distinguish between logging error and communication drop.

Verify if `entrance_light` is actually an occupancy-sensor-triggered device or manually controlled (query asks about 'sensors', but light behavior might be a red herring for sensor health).

Check chunks C00-C03 and C10-C13 for any other `front_door_contact`, `front_door_lock`, or `entrance_occupancy` events to establish a complete daily baseline.

Investigate the empty log entry at 17:51:00 in C09 more closely; while it recovered, determine if this indicates intermittent connectivity issues common in Matter devices on weak networks.

Confirm if an `entrance_occupancy` sensor exists in the system configuration. If not, its absence is normal, not a fault.

The investigator correctly identified that the primary access sensors (contact/lock) show coherent state transitions in C04 and C09, supporting a 'normal' hypothesis for those specific devices.

However, the query asks about 'sensors' in the entrance area generally. The investigator notes the absence of `entrance_occupancy` logs but treats it as a potential weakness rather than a definitive check for device existence/configuration.

The 'anomaly' regarding the empty log at 17:51:00 is flagged as low risk by the investigator, which is correct, but the lack of broader context (other chunks) means we cannot rule out intermittent network issues affecting the whole zone.

Crucially, the investigation is limited to C04 and C09. We have not seen the full day's data (C00-C03, C10-C13 are missing). A single day's snapshot with only two interaction points is insufficient to declare 'normal' operation for security-critical sensors, nor to definitively diagnose 'intermittent' faults without seeing the gaps.

Risk of false alarm is medium because concluding 'normal' based on sparse positive evidence ignores the possibility of silent failures or unreported states in the unexamined timeframes.

Action: Refine investigation to include remaining chunks to build a complete temporal picture before finalizing the verdict.

Entrance sensors (door contact and lock) are functioning normally. The low activity count (17 events for entrance vs hundreds for other rooms) is consistent with a front door that is rarely used or only used during specific entry/exit windows, which explains the sparse logging in the provided chunks.

C04 shows a coherent sequence: Door Contact opens (false->true), followed immediately by Lock Operation and LockState change to locked. This indicates the sensor correctly detected the state change and the lock responded.

C09 shows another coherent sequence: Lock unlocks (raw=2), then locks again (raw=1) within seconds, followed later by a manual unlock operation and subsequent light activation. These transitions are logically consistent with user entry/exit behavior.

No stuck values, impossible state transitions, or explicit fault alarms were observed in the focused chunks.

The analysis is limited to two short time windows (morning and late afternoon). It does not cover the entire day, so intermittent failures outside these windows are not ruled out.

The 'entrance_light' turning on at 18:24 suggests occupancy or motion was detected, but no corresponding 'entrance_occupancy' or 'entrance_motion' event is explicitly logged in the focused chunks, though this could be due to log filtering rather than sensor failure.

Potential partial sensor data loss or reporting gap for the entrance area, specifically regarding occupancy/motion detection, although the primary access control sensors (contact/lock) appear functional.

In C09, at 18:24:14, `entrance_light` turns on. Typically, this is triggered by an occupancy or motion sensor in the entrance. However, there is no preceding or concurrent `OccupancySensing.Occupancy` event from an 'entrance_occupancy' device in the logs, unlike the living_room_occupancy event at 18:24:24.

The structured signals show 'entrance' has only 17 activity events compared to 397 for living_room, which might indicate missing telemetry if the entrance is a high-traffic area.

At 17:51:00 in C09, there is a brief empty log line for `front_door_lock` before it reports unlocked, suggesting a potential transient communication glitch or log drop, though it recovered quickly.

The absence of an explicit occupancy event for the entrance light trigger could simply mean the system uses a different mechanism (e.g., direct switch, timer, or a sensor whose logs were filtered out in the focused chunks) rather than a malfunction.

The lock and contact sensors themselves show valid state transitions and operations, so calling it a general 'sensor malfunction' is too broad; it's more likely a specific reporting gap for one type of sensor or a log aggregation issue.

The brief empty log at 17:51:00 resolved itself immediately, which is characteristic of network jitter rather than hardware failure.

C04: Coherent transition from BooleanState.StateValue false->true (door open) to LockOperation and LockState locked confirms basic sensor-actuator linkage works.

C09: Light activation at 18:24:14 without a corresponding explicit entrance occupancy log entry raises questions about coverage of motion/occupancy sensing in the entrance zone.

Low total event count (17) for entrance compared to other rooms supports the hypothesis of infrequent use rather than constant failure, but requires context on household traffic patterns.

Logs for the full 24-hour period to determine if the low event count is typical or if there are long periods of expected activity with zero logs.

Explicit presence of an 'entrance_occupancy' or 'entrance_motion' sensor definition and its recent history to verify if the light trigger was indeed from a sensor that failed to report.

Network connectivity logs for the entrance devices to rule out Wi-Fi/Zigbee dropout as the cause for the empty log line at 17:51:00.

No stuck values or impossible state transitions were observed in the contact or lock logs.

This is followed by valid state changes at 17:51:03 (unlocked) and 17:51:08 (locked).

Despite multiple entries/exits (C04, C09), no `entrance_occupancy` or `entrance_motion` device logs appear in any chunk.

The query specifically asks about 'sensors', and the absence of occupancy data contrasts with the detailed occupancy logs for other rooms.

If the system relies on occupancy for security alerts, this gap represents a functional deficiency.

Verify if 'entrance_light' is controlled by a motion/occupancy sensor or a manual switch/timer.

Check for explicit 'entrance_occupancy' or 'entrance_motion' device logs in the full timeline to confirm if the light trigger was sensor-based.

Investigate the empty log line at 17:51:00 for `front_door_lock` to determine if it indicates a communication dropout or just a logging artifact.

Confirm if the door contact sensor reported state changes corresponding to the lock operations in C09 (specifically around 18:24).

The investigator correctly identified that the primary access sensors (contact/lock) show coherent behavior in the sampled chunks (C04, C09).

However, the hypothesis of 'sensor malfunction' relies heavily on the absence of an explicit occupancy event for the entrance light. This is weak evidence because the light could be triggered manually or via a different mechanism not captured in the focused chunks.

The query asks about 'sensors' generally. The current analysis focuses on contact/lock but speculates on occupancy/motion without direct evidence of failure (only absence of logs).

To rule out false alarms regarding the light trigger and the brief lock log gap, we need to see the surrounding context (other chunks) to establish baseline traffic and verify if an occupancy sensor exists and is reporting elsewhere.

Do not conclude 'normal' yet due to the unresolved ambiguity of the light trigger source and the potential data gap.

## 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",
      "entrance_light"
    ],
    "target_question": "判断 entrance 区域的传感器（入户门传感器、门锁等）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": [
    "low_activity_device",
    "intermittent_reporting",
    "missing_sensor_data"
  ],
  "why_these_chunks": [
    "C04 contains the only clear 'entrance' events in the early morning (07:15), showing front_door_contact and front_door_lock activity, which is critical for baseline behavior analysis.",
    "C09 shows entrance activity later in the day (16:45-18:24) with lock operations, providing a second data point to check for consistency or gaps.",
    "Other chunks show 0 or negligible entrance events, highlighting the low frequency of this device's logs compared to others, which is key to diagnosing if it's working normally or just rarely triggered."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "Entrance sensors (contact and lock) are functioning normally. The low activity count is consistent with a rarely used entrance or a home where occupants use alternative entry methods (e.g., keypad, app, or side door) for most of the day. The specific events in C04 and C09 show coherent state transitions: door opens/closes, lock operates, and lights trigger appropriately.",
      "


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 functioning normally with consistent reporting and realistic values.

Explanation: Analysis of the provided log chunks (C00, C05, C13) shows that the `kitchen_temp_sensor` reports data consistently every 5 minutes without any gaps or stuck values.

Explanation: The raw integer values correctly convert to Celsius (e.g., 2268 -> 22.68°C), and the temperature fluctuations are within a physically realistic range for an indoor environment (approx. 22.6°C to 25.4°C).

Explanation: No explicit fault codes, connectivity drops, or impossible state transitions were observed for the temperature sensor.

Explanation: While a smoke alarm self-test was recorded in C13, it completed successfully and does not indicate a malfunction of the temperature sensor.

Consistent 5-minute reporting intervals across all sampled time blocks.

Realistic temperature readings ranging from ~22.6°C to ~25.4°C with no outliers or static values.

Successful completion of smoke alarm self-test in C13 indicates normal operation of safety devices.

No action required; device status is normal.

C05: Kitchen temp reports consistently every 5 minutes from 06:50 to 08:10, ranging from 24.98 C to 25.37 C.

C13: Kitchen temp reports consistently every 5 minutes from 17:55 to 19:05, ranging from 22.92 C to 23.31 C.

No explicit fault events, alarms, or connectivity drops associated with `kitchen_temp_sensor`.

The analysis relies on sampled chunks; if faults occurred between these windows, they would be missed. However, the query asks to judge based on the provided history.

Potential safety device issue with the kitchen smoke alarm, though not directly a temperature sensor fault. At 18:45, the `kitchen_smoke_alarm` initiated a self-test (`TestInProgress=true`) and reported an `ExpressedState=4`. While it completed successfully (`SelfTestComplete`, `ExpressedState=0`), the intermediate state '4' might indicate a specific test mode or minor anomaly depending on the manufacturer's definition. However, since it recovered immediately and fully, this is likely normal operation rather than a malfunction.

C13: `[2026-06-06T18:45:00] kitchen_smoke_alarm | SmokeCoAlarm.TestInProgress = true`

C13: `[2026-06-06T18:45:00] kitchen_smoke_alarm | SmokeCoAlarm.ExpressedState = 4`

C13: `[2026-06-06T18:45:30] kitchen_smoke_alarm | Event: SelfTestComplete()`

C13: `[2026-06-06T18:45:30] kitchen_smoke_alarm | SmokeCoAlarm.TestInProgress = false`

The smoke alarm recovered completely within 30 seconds, which is typical for a self-test cycle. Without documentation stating that `ExpressedState=4` during a test is abnormal, this is indistinguishable from normal behavior. It does not constitute a sensor malfunction for the temperature sensor.

Consistent 5-minute reporting intervals for `kitchen_temp_sensor` across all three time blocks (C00, C05, C13) without any missing entries or stuck values.

Correct conversion of raw integers to Celsius values (e.g., 2268 -> 22.68 C) confirms proper data formatting.

Temperature trends in the kitchen correlate logically with other rooms (e.g., rising in the morning, stable at night), suggesting environmental consistency rather than sensor error.

Manufacturer-specific definitions for `SmokeCoAlarm.ExpressedState` codes to definitively rule out non-standard states during the self-test.

Full 24-hour log to ensure no intermittent connectivity issues occurred outside the sampled windows.

The investigator correctly identified the target device (kitchen_temp_sensor) and analyzed the provided chunks (C00, C05, C13).

The analysis of temperature scaling is correct (raw values divided by 100), avoiding the false-alarm risk of interpreting raw integers as literal temperatures.

The conclusion that the sensor is working normally is supported by consistent reporting intervals, realistic value ranges, and lack of stuck values or data gaps in the sampled windows.

The investigation into the smoke alarm self-test was appropriately scoped as a separate potential issue but correctly dismissed as normal operation for the temperature sensor query.

No protocol-format misunderstandings were detected. The evidence is sufficient to conclude the temperature sensor is functioning within normal parameters based on the available history.

## 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",
    "C05",
    "C13"
  ],
  "suspected_patterns": [
    "sensor_stuck_value",
    "sensor_no_data",
    "impossible_state_transition"
  ],
  "why_these_chunks": [
    "C00: Initial state check to establish baseline reporting frequency and values.",
    "C05: Mid-day check for consistency with other rooms and potential drift.",
    "C13: Evening check where alarmish_count is highest (19) and kitchen_smoke_alarm appears in top devices, checking for correlated faults or data gaps."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The kitchen temperature sensor is functioning normally. The logs show consistent, periodic reporting of temperature values that fluctuate within a realistic range (approx. 22.6°C to 25.4°C) across different times of the day (night, morning, evening). The raw integer values correctly correspond to the displayed Celsius values (e.g., 2268 -> 22.68 C), indicating no scaling errors. There are no stuck values, data gaps, or impossible transitions observed in the temperature readings.",
      "evidence": [
        "C00: Kitchen temp reports consistently every 5 minutes from 00:00 to 01:20, ranging from 22.67 C to 23.13 C.",
        "C05: Kitchen temp reports consistently every 5 m


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 functioning normally with no evidence of fault.

Explanation: Analysis of the provided log chunks (C00-C06) shows that the second_bedroom_temp_sensor reports smooth, gradual temperature changes (ranging from ~22.65°C to ~25.40°C) that correlate logically with other rooms in the house, indicating normal environmental response rather than sensor drift or failure.

Explanation: The second_bedroom_occupancy sensor consistently reports 'unoccupied' (raw=0) throughout the observed period, which is consistent with the lack of any motion or activity logs specific to that room.

Explanation: There are no explicit fault events, alarms, stuck values, or impossible state transitions recorded for these devices in the available data.

Explanation: Although the supervisor noted that chunks C07-C22 were missing, the investigator's analysis of the early morning/day cycle (approx. 8.5 hours) provides strong evidence of normal operation for the requested scope. No anomaly patterns were detected in the visible data.

Temperature trend: 22.65 -> ... -> 25.40 C, showing smooth diurnal variation consistent with other sensors.

Occupancy status: Consistently unoccupied (raw=0) across all timestamps in C00-C06.

No fault codes or communication errors logged for second_bedroom sensors.

Continue monitoring the device health over the remaining time periods (evening/night) if full 24-hour coverage is required for audit purposes.

No immediate maintenance or repair actions are necessary based on current evidence.

The second_bedroom temperature and occupancy sensors are functioning normally. The temperature readings show expected gradual diurnal variation (rising from ~22.7°C to ~25.4°C) consistent with the rest of the house, and the occupancy sensor correctly reports 'unoccupied' throughout the period, which aligns with the lack of specific activity logs in that room.

Temperature values for second_bedroom_temp_sensor range from 22.65 C to 25.40 C over the observed period, showing smooth transitions without sudden jumps or flatlining indicative of a stuck sensor.

OccupancySensing.Occupancy remains at raw=0 (unoccupied) for all timestamps in C00-C06, which is a valid state for an unoccupied bedroom.

No explicit fault events, alarms, or communication errors are logged for these devices.

The analysis is limited to chunks C00-C06 (approx. 8.5 hours). While this covers a significant portion of the early morning/day, it does not cover the full 24-hour cycle implied by 'history'. However, within this window, no faults are detected.

Second bedroom temperature trend: 22.72 -> 23.11 -> 23.40 -> 23.96 -> 24.60 -> 24.99 -> 25.14 C. This correlates well with other rooms (Living Room: 22.76 -> 23.14 -> 23.39 -> 24.07 -> 24.63 -> 25.03 -> 25.20 C), indicating normal environmental response rather than sensor drift or failure.

Occupancy status: Consistently 0 (unoccupied) across all provided chunks, with no contradictory motion or contact events suggesting a missed detection or stuck state.

Logs for chunks C07 through C22 are required to confirm behavior over the remainder of the day/night cycle, specifically checking for any intermittent failures or changes in occupancy patterns during evening/night hours.

Verify temperature trends and occupancy status for the remainder of the day (evening/night) in chunks C07-C22.

Check for intermittent data dropouts or stuck values in the second_bedroom sensors during the unobserved period.

Confirm if 'unoccupied' status for the entire morning is consistent with household activity logs (e.g., no motion in other rooms that might imply presence elsewhere).

The investigator correctly identified normal behavior in the early morning hours (C00-C06), noting smooth temperature transitions and consistent 'unoccupied' states.

However, the investigation is incomplete. The query asks to check the 'history', implying a full cycle or at least a significant portion beyond just the first 8.5 hours. The investigator explicitly admits in 'weaknesses' and 'missing_information' that C07-C22 are required.

Concluding 'normal' based on only ~1/3 of the likely 24-hour log window is insufficient for a definitive health check. There is a risk of missing an afternoon/evening fault (e.g., sensor drift, battery death, or stuck value) that occurs later in the day.

No protocol-format misunderstandings were detected; scaled values were handled correctly.

Action: Require analysis of remaining chunks to confirm stability over the full period.

The second_bedroom temperature and occupancy sensors are functioning normally. The temperature readings show expected diurnal variation (rising from ~22.7°C to ~24.6°C) with smooth transitions consistent with thermal inertia. Occupancy remains 'unoccupied' throughout the period, which is consistent with the early morning hours (00:00 - 05:30) and lack of other activity signals in that room.

Temperature values for second_bedroom_temp_sensor range from 22.65 C to 24.63 C over the log period, showing a gradual increase typical of overnight ambient temperature changes.

No stuck values detected; raw integer values change frequently and logically (e.g., 2272 -> 2265 -> 2270).

OccupancySensing.Occupancy consistently reports 0 (unoccupied) across all timestamps in C00-C03.

Cross-room correlation: Temperature trends in second_bedroom align closely with living_room and master_bedroom, suggesting no isolated sensor drift or fault.

The analysis is limited to the first 5.5 hours of data (C00-C03). If faults occur later, they are not captured here.

Continuous stream of valid, changing temperature measurements for second_bedroom_temp_sensor without gaps or impossible jumps.

Consistent 'unoccupied' status for second_bedroom_occupancy, matching the time of day and lack of conflicting motion/lock events.

Logs for chunks C04 through C22 are required to confirm health over the full requested period.

Context on whether the second bedroom was expected to be occupied during this specific timeframe (though early morning suggests unoccupied is normal).

Full temporal coverage of second_bedroom sensors (currently only C00-C03 provided)

Verification of occupancy sensor state transitions beyond 'unoccupied'

Check for stuck values or data gaps in the remaining 19 chunks

The investigator correctly identified that C00-C03 show normal behavior but explicitly noted that logs for C04-C22 are missing.

However, the Triage Output claimed all chunks C00-C22 were focused/analyzed, which contradicts the Investigator's finding and the actual provided text.

A health check cannot be concluded as 'normal' based on only ~5.5 hours of data when the query implies a full history check. The risk of missing intermittent faults in the unprovided chunks is significant.

The investigator's hypothesis N1 is weak because it admits to limited scope. We must review the remaining chunks to confirm the device health over the entire period.

## 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"
  ],
  "focus_chunk_ids": [
    "C00",
    "C01",
    "C02",
    "C03",
    "C04",
    "C05",
    "C06",
    "C07",
    "C08",
    "C09",
    "C10",
    "C11",
    "C12",
    "C13",
    "C14",
    "C15",
    "C16",
    "C17",
    "C18",
    "C19",
    "C20",
    "C21",
    "C22"
  ],
  "suspected_patterns": [
    "missing_data",
    "stuck_values",
    "impossible_transitions"
  ],
  "why_these_chunks": [
    "The query requires a comprehensive health check of the second_bedroom sensors over the entire log period. All chunks (C00-C22) contain data for the second_bedroom temperature sensor and occupancy sensor, allowing for a complete trend analysis to detect intermittent failures, stuck values, or missing data patterns."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The second_bedroom temperature and occupancy sensors are functioning normally. The temperature readings show expected gradual diurnal variation (rising from ~22.7°C to ~25.4°C) consistent with the rest of the house, and the occupancy sensor correctly reports 'unoccupied' throughout the period, which aligns with the lack of specific activity logs in that room


DF-06-FP: 窗帘正常移动但速度慢

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

Explanation: Analyzed the logs for master_bedroom_temp_sensor across chunks C00, C05, and C22. The sensor reports valid temperature values at regular intervals (every 5 minutes) with logical diurnal variation (e.g., rising from ~22.7°C to ~25.0°C in the morning, cooling to ~23°C in the evening). There are no stuck values, impossible jumps, or missing data points for this specific device.

Explanation: Analyzed the logs for master_bedroom_occupancy. The sensor correctly transitions from 'unoccupied' (raw=0) during the night to 'occupied' (raw=1) around 06:24, coinciding with other household wake-up activities. It remains occupied through the evening routine without erratic flipping or stuck states.

Explanation: Contrasted with the kitchen_temp_sensor, which exhibited transient 'None' values indicating a fault. The master_bedroom sensors did not exhibit similar dropout patterns, confirming their health relative to the faulty device.

Explanation: No direct fault evidence (such as alarm events, repeated non-recovery, or protocol violations) was found for the master_bedroom devices.

master_bedroom_temp_sensor reports continuous valid integer values (e.g., 2276, 2489, 2318 raw codes) throughout all checked timeframes.

master_bedroom_occupancy shows logical state transition from unoccupied (0) to occupied (1) at 06:24, consistent with human activity patterns.

Absence of 'None' values or error flags for master_bedroom devices, unlike the kitchen_temp_sensor which showed transient failures.

No action required; sensors are operating within normal parameters.

C00: Temperature reports consistently every 5 minutes with logical progression (22.76 -> 22.79 -> 22.68...)

C00: Occupancy remains 'unoccupied' (raw=0) during early morning hours when no activity is logged.

C05: Occupancy transitions to 'occupied' (raw=1) at 06:24, coinciding with other household wake-up activities (kids room light on, kitchen activity).

C05: Temperature continues to report valid values (24.89 C, 24.87 C...) during the occupied period without interruption.

C22: Evening occupancy remains 'occupied' (raw=1) consistent with evening routine, and temperature reports remain valid (23.18 C -> 22.92 C).

Relies on the assumption that the absence of error logs implies perfect health, though this is standard for healthy devices.

No sensor malfunction detected. While the kitchen_temp_sensor experienced transient data loss (None values) in C05 and C22, the master_bedroom sensors did not exhibit similar faults. The query specifically asks about master_bedroom, and the evidence shows it is robust compared to the faulty kitchen sensor.

C05: kitchen_temp_sensor reports None at 06:37:10 but recovers by 06:40:00.

C22: kitchen_temp_sensor reports None at 18:24:00 but recovers by 18:25:00.

Contrast: master_bedroom_temp_sensor has no 'None' entries in any chunk.

Contrast: master_bedroom_occupancy has no missing updates or stuck states in any chunk.

This hypothesis confirms normality rather than identifying an anomaly, which is the correct conclusion based on the strict definition of device fault requiring direct evidence like stuck values or repeated non-recovery.

Comparison of master_bedroom_temp_sensor vs kitchen_temp_sensor: Kitchen sensor shows explicit 'None' values indicating failure/dropout, while master_bedroom sensor maintains continuous valid integer reporting throughout all chunks.

Occupancy transition logic: master_bedroom_occupancy changes from unoccupied (0) to occupied (1) at 06:24 and stays occupied through the evening, matching the temporal context of daily life without erratic flipping or stuck states.

Long-term historical baseline for master_bedroom temperature to rule out slow drift, though current logs show no immediate fault.

Battery level or connectivity status signals if available, as these are common causes of intermittent failures seen in the kitchen sensor.

The investigator correctly identified the target devices (master_bedroom_temp_sensor, master_bedroom_occupancy) and focused on relevant chunks (C00, C05, C22).

Evidence analysis is sound: Temperature readings show logical diurnal variation without stuck values or impossible jumps. Occupancy transitions are consistent with human activity patterns.

The investigator correctly distinguished between the faulty kitchen sensor (transient None values) and the healthy master bedroom sensors, avoiding a false alarm based on unrelated device failures.

No protocol-format misunderstandings detected (scaled temperatures interpreted correctly).

Conclusion that the sensors are working normally is supported by direct evidence of continuous, valid reporting and logical state transitions.

## 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_temp_sensor",
      "master_bedroom_occupancy_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_temp_sensor",
    "master_bedroom_occupancy"
  ],
  "focus_chunk_ids": [
    "C00",
    "C05",
    "C22"
  ],
  "suspected_patterns": [
    "missing_data",
    "stuck_values",
    "impossible_transitions"
  ],
  "why_these_chunks": [
    "C00: Baseline check for normal temperature reporting and occupancy transitions at the start of the log.",
    "C05: Check for occupancy state changes (unoccupied to occupied) which are critical for sensor health verification.",
    "C22: Contains a specific anomaly where kitchen_temp_sensor reports None, serving as a reference point for data loss patterns; checking master_bedroom here ensures no similar silent failures or missing logs occur in the target room."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The master_bedroom temperature and occupancy sensors are functioning normally. The temperature readings show expected diurnal variation (rising from ~22.7°C to ~25.0°C) and stable reporting intervals. Occupancy transitions align with typical human presence patterns (unoccupied at night, occupied in the morning and evening). No stuck values, impossible transitions, or data loss events were observed for these specific devices.",


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 provides continuous, regular updates (every 5 minutes) with physically plausible temperature values ranging from 22.69°C to 25.30°C throughout the entire log period (00:00 - 07:43). There are no stuck values, impossible jumps, or data gaps for this specific device.

Explanation: The living_room_occupancy sensor consistently reports 'unoccupied' (raw=0) at all check-in points. This state is corroborated by the absence of any activity indicators (lights, other sensors) in the living room and the simultaneous detection of occupancy in other rooms (master bedroom, kids room), confirming the sensor is correctly reflecting the empty state of the room rather than failing.

Explanation: While transient `None` values were observed in the kitchen_temp_sensor, these are isolated to a different device and do not indicate a fault in the living room sensors. The living room sensors remained fully operational during these events.

living_room_temp_sensor shows stable, gradual fluctuations (e.g., 22.69 C -> ... -> 25.17 C) without errors.

living_room_occupancy remains 'unoccupied' (raw=0) consistently, aligning with the lack of activity in that zone while other zones show occupancy.

living_room_temp_sensor provides regular updates every 5 minutes with physically plausible values ranging from 22.69 C to 25.30 C.

No stuck values or impossible jumps in temperature data for the living room sensor.

living_room_occupancy consistently reports 'unoccupied' (raw=0) at all check-in points (00:00, 00:30, ..., 07:30).

Other sensors in the house (master_bedroom, kids_room) transition to 'occupied' starting around 05:59-06:13, indicating active human presence elsewhere, making it highly probable that the unreported living room is indeed empty rather than the sensor being faulty.

The investigation covers only the first ~7.5 hours of the day. A complete health check would ideally include periods of high activity if the living room were used later in the day, but within the provided scope, no faults are evident.

Potential intermittent communication dropout or transient sensor glitch affecting the kitchen sensor, but not the living room sensor. While the living room sensor appears healthy, the kitchen sensor shows a `None` value at 06:52 and 07:10, suggesting potential network or device instability in the cluster. However, this does not constitute a fault for the living room sensor itself.

kitchen_temp_sensor reports `TemperatureMeasurement.MeasuredValue = None` at 06:52:00 and 07:10:10.

These dropouts coincide with high activity in adjacent areas (dining room occupancy changes, lights turning on/off), which might suggest interference or load issues, but the living room sensor continues to report valid data during these times.

The query specifically asks about the **living_room** sensors. The anomalies observed are isolated to the kitchen sensor.

Single transient `None` values are explicitly excluded from defining a persistent malfunction according to the rules ('A single transient None... is not enough to claim sensor_malfunction').

The living room sensor shows no such errors.

living_room_temp_sensor continuous stream of valid Celsius values (e.g., 22.69 C -> ... -> 25.30 C) without gaps or stuck states.

living_room_occupancy consistent 'unoccupied' status across all timestamps, corroborated by occupancy events in other rooms (master/kids) occurring simultaneously, confirming the house state logic is working correctly.

Logs for the remainder of the day (after 07:43) to verify living room sensor behavior during potential daytime usage.

The investigator correctly identified that the living_room sensors (temperature and occupancy) are functioning normally based on the provided logs.

Evidence is sufficient: The temperature sensor shows regular updates with physically plausible values and no stuck states. The occupancy sensor consistently reports 'unoccupied', which is corroborated by the absence of other activity indicators in the living room and the presence of activity in other rooms (master/kids) during the same period.

The investigator appropriately excluded kitchen sensor anomalies as irrelevant to the specific query about the living room.

No protocol misunderstandings or false-alarm risks detected regarding the target devices.

The living room temperature sensor and occupancy sensor are functioning normally. The temperature readings show expected diurnal variation (slow rise from ~22.7°C to ~24.4°C over 5 hours) consistent with a residential environment without active heating/cooling or significant heat sources. Occupancy remains 'unoccupied' throughout, which is plausible for the early morning hours (00:00-05:00). No stuck values, data gaps, or impossible transitions are observed.

Temperature values fluctuate naturally between 22.69°C and 24.44°C with no sudden jumps or plateaus indicative of sensor failure.

OccupancySensing.Occupancy consistently reports 0 (unoccupied) across all timestamps in C00-C03.

No explicit fault events, alarms, or error codes are present in the logs.

Other sensors in the house (master_bedroom, kids_room, kitchen) show similar temperature trends, suggesting a coherent environmental state rather than an isolated device error.

The analysis is limited to the first 5 hours of data; behavior during occupied periods (daytime/evening) is not visible here.

Without motion or activity correlation, 'unoccupied' status cannot be definitively verified against human presence, though it is statistically likely for this time window.

Continuous stream of valid, varying temperature readings from living_room_temp_sensor (C00-C03) rules out sensor_stuck or sensor_malfunction.

Consistent 'unoccupied' status from living_room_occupancy sensor aligns with typical nighttime/early morning patterns, showing no signs of false positives or stuck states.

Absence of any fault flags or protocol errors in the structured signals and raw logs.

Logs for later time periods (after 05:00) to verify sensor behavior during potential occupancy.

Motion sensor data or other activity indicators to cross-validate the 'unoccupied' status if occupancy detection relies on passive infrared or similar technologies that might have blind spots.

Verify sensor behavior during occupied periods (daytime/evening) to detect occupancy-related faults or drift.

Check for data gaps or missing updates in later time chunks (C04+).

Confirm if 'unoccupied' status is consistent with expected human presence patterns in the full log duration.

The investigator correctly identified that the provided logs (C00-C03, 00:00-05:00) show normal temperature trends and consistent 'unoccupied' states.

However, the conclusion of 'normal' is based solely on early morning hours when the house is likely empty. This is insufficient to rule out all sensor faults (e.g., sensors failing only when triggered by motion, or drifting significantly during heating/cooling cycles which might occur later).

The query asks to judge if sensors are working normally based on the history. The current evidence covers only ~5 hours. A robust health check requires observing the device across different operational contexts (e.g., when occupancy changes, when HVAC might activate).

No protocol misunderstandings detected. Values are correctly interpreted as centi-degrees.

Recommendation: Retrieve subsequent chunks (C04 onwards) to observe behavior during potential occupancy and environmental changes before finalizing the verdict.

## 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_values",
    "missing_data_gaps",
    "impossible_state_transitions",
    "outlier_readings"
  ],
  "why_these_chunks": [
    "C00-C03 cover the initial period of the logs, allowing inspection of baseline behavior and any immediate anomalies in temperature readings or occupancy state transitions for the living room sensors.",
    "These chunks contain the highest density of preview lines for the target devices, facilitating a quick check for stuck values or missing updates."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The living room temperature and occupancy sensors are functioning normally. The temperature readings show stable, gradual fluctuations consistent with a passive indoor environment, and the occupancy sensor correctly reports 'unoccupied' throughout the entire log duration (00:00 - 07:43), which aligns with typical household behavior where the living room is not used during early morning hours while other rooms (master bedroom, kids room) become occupied.",
      "evidence": [
        "living_room_temp_sensor provides


The bathroom occupancy sensor is functioning normally; the periodic 'unoccupied' reports are standard heartbeats from an empty room.

Explanation: The logs show a valid detection cycle in C05: the sensor transitioned from 'occupied' to 'unoccupied' at 09:22, confirming it detects presence changes correctly.

Explanation: Subsequent 'unoccupied' events (e.g., 09:49, 10:19, ..., 17:49) occur at precise 20-minute intervals with a fixed :22 second offset. This strict periodicity is characteristic of a device heartbeat or status report mechanism, not random noise or a stuck fault.

Explanation: There is no evidence of actual occupancy in the bathroom after 09:22 (no light activation, no water leak detector triggers), supporting the conclusion that the room remained empty and the sensor was simply reporting its idle state periodically.

Explanation: No explicit fault codes, alarm events, or impossible state transitions were observed. The behavior is consistent with a low-power IoT device maintaining connectivity while unoccupied.

C05: Valid transition from occupied to unoccupied at 09:22.

C05-C11: Periodic 'unoccupied' reports every 20 minutes at XX:XX:22.

Absence of correlated activity (light/leak) in bathroom after 09:22 confirms room emptiness.

No action required; sensor is operating as expected.

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

Subsequent 'unoccupied' events in C06-C11 (e.g., 10:49, 11:19, 13:19, etc.) occur at regular ~20-minute intervals with a fixed timestamp offset (:22). This suggests a periodic heartbeat mechanism rather than repeated entry/exit cycles.

No 'occupied' events are logged for the bathroom after 09:22, consistent with the room being empty.

Other sensors (living_room, bedroom) show high activity, confirming the system is generally logging data correctly; the lack of bathroom logs is specific to that room's state.

The water_leak_detector and onoff_light show no activity, which is normal for an empty bathroom.

Does not explain why the heartbeat interval is exactly 20 minutes or why it persists for hours without any user interaction, though this is plausible for low-power IoT devices.

Relies on the assumption that no one used the bathroom between 09:22 and 18:03, which cannot be strictly proven by logs alone but is supported by the absence of any correlated device triggers (light, leak).

The bathroom occupancy sensor has a firmware bug or configuration error causing it to repeatedly report 'unoccupied' even if someone were present, or it is stuck in a failed state where it cannot detect presence after the initial morning use.

If these were change-only events, they would imply the person left and never returned, or left and came back multiple times without triggering 'occupied'. However, the strict periodicity suggests a heartbeat.

If the sensor is supposed to report changes only, the constant re-reporting of 'unoccupied' is redundant and potentially indicative of a stuck state or a misconfigured reporting threshold.

There is a complete absence of 'bathroom_light' or 'water_leak' events, which might have been triggered if the room were actually used (assuming auto-on lights), further supporting the 'empty' theory but raising questions about why the sensor keeps pinging if it's just idle.

The strict periodicity strongly points to a heartbeat protocol rather than a fault. A stuck sensor usually results in a single static value or erratic noise, not a clean 20-minute interval.

Without evidence of actual occupancy during these periods (e.g., light turning on), we cannot prove the sensor is failing to detect presence. It is more likely the room is simply empty.

The query asks if the sensor is working 'normally'. If the protocol requires periodic status updates, this behavior is normal.

Intermittent connectivity or packet loss is causing missed 'occupied' events if the bathroom was used later in the day, while 'unoccupied' heartbeats continue to get through.

The 'unoccupied' heartbeats are very frequent (every 20 mins). If the network is congested or the device is power-saving, it might prioritize sending status checks over full state transitions.

However, there is zero evidence of any other bathroom activity (light, leak) to corroborate usage, making this hypothesis weak due to lack of contradictory evidence.

No 'occupied' events were ever missed because none were expected based on the lack of secondary signals (lights, etc.).

The consistency of the heartbeat suggests stable connectivity for this specific device type.

The exact timing of 'unoccupied' events: all occur at XX:XX:22 seconds, spaced exactly 20 minutes apart (09:22, 09:49, 10:19...)

The transition from 'occupied' to 'unoccupied' in C05 (09:10-09:22) establishes the sensor works for detection.

The complete absence of 'bathroom_light' or 'water_leak' events throughout the entire day, which supports the conclusion that the room remained empty after the morning session.

Configuration details of the occupancy sensor (is it configured for change-only or periodic reporting?).

User confirmation of bathroom usage patterns for the rest of the day.

Logs for any other sensors in the bathroom (e.g., mirror defogger, exhaust fan) that might indicate usage.

Verify if the periodic 'unoccupied' reports (every 20 mins at :22) are standard heartbeat behavior for this specific Matter device model or a misconfiguration.

Check for any explicit fault/alarm events in the logs that might indicate sensor failure, rather than inferring from silence.

Confirm if the absence of light/leak events is consistent with the occupancy state (i.e., did the user manually turn off lights before leaving, or is the auto-off feature broken?).

The investigator correctly identifies the pattern as likely being heartbeats rather than a fault, but fails to definitively rule out a configuration error or firmware bug causing redundant reporting.

The conclusion relies heavily on the assumption that the room was empty. While plausible, the strict periodicity of the 'unoccupied' report without corresponding 'occupied' transitions later in the day is suspicious and warrants a check against device documentation or similar devices.

No direct fault evidence (stuck values, alarms) was found, so a 'fault' verdict cannot be issued. However, labeling it 'normal' without verifying the heartbeat protocol is risky. The current evidence supports 'likely normal but needs verification', not 'sufficiently proven normal'.

The analysis is on-topic and avoids false alarms by not over-interpreting the lack of activity as a safety issue.

Bathroom occupancy sensor is functioning normally. The device reports valid state transitions (occupied to unoccupied) consistent with typical short-duration usage patterns in a bathroom.

C05: Sensor reports 'occupied' at 09:10 and transitions to 'unoccupied' at 09:19, indicating a ~9 minute duration which is plausible for bathroom use.

C05: Another transition to 'unoccupied' occurs at 09:49, suggesting the user may have left briefly or the sensor logic reset.

C09: Sensor reports 'unoccupied' at 14:19, 14:49, and 15:19. While no 'occupied' event is explicitly logged before these in the provided chunks, the repeated reporting of 'unoccupied' indicates the device is active and communicating.

C11: Sensor reports 'unoccupied' at 16:49, 17:19, and 17:49, showing consistent periodic reporting.

The logs only show 'unoccupied' states for the majority of the afternoon/evening (C09, C11). Without corresponding 'occupied' events, it is impossible to verify if the sensor correctly detects presence, only that it correctly reports absence.

The lack of 'occupied' events might imply the sensor is stuck in 'unoccupied' or simply that the user was not detected during those times.

Bathroom occupancy sensor has a 'sensor_stuck' or 'missing_detection' fault. The device fails to report any 'occupied' state despite likely human presence, potentially due to hardware failure, misconfiguration, or blind spot issues.

In C09 (14:10-15:28) and C11 (16:45-18:03), the bathroom_occupancy sensor *only* reports 'unoccupied' (raw=0). There are zero 'occupied' (raw=1) events recorded for this device in these two significant time blocks.

In contrast, other rooms (living_room, bedroom) show frequent 'occupied' events, indicating the network and logging pipeline are functional.

If the bathroom was used during these periods (common for bathrooms), the complete absence of 'occupied' signals suggests the sensor is either physically stuck in the unoccupied state or failing to trigger on presence.

The pattern of reporting 'unoccupied' every ~30 minutes (e.g., 14:19, 14:49, 15:19 in C09) suggests the device is alive but consistently detecting no one, which contradicts typical high-traffic behavior unless the room was truly empty for hours.

It is possible the bathroom was genuinely unused for long stretches (e.g., 14:10-18:03), making the 'unoccupied' readings correct.

The query asks about 'sensors' generally, but we only have strong evidence for the occupancy sensor's potential issue; water leak and light sensors show no activity/logs in these chunks, so their status is unknown rather than necessarily faulty.

Intermittent connectivity or log aggregation gap for the bathroom devices. The lack of 'occupied' events and missing water leak/light logs might indicate the device is dropping packets or the gateway is filtering them, rather than a permanent sensor fault.

The bathroom_occupancy device does appear in logs (reporting 'unoccupied'), so it is not completely offline.

However, the asymmetry between its presence (reporting unoccupied) and the total absence of 'occupied' events compared to other rooms could suggest a configuration issue or intermittent packet loss specifically for positive detection events.

This hypothesis is less specific than A1 regarding the 'fault type' requested, as 'intermittent connectivity' usually implies dropped logs entirely, whereas here we see regular 'unoccupied' logs.

Presence of 'occupied' events in C05 vs. complete absence of 'occupied' events in C09 and C11 for bathroom_occupancy.

Consistent reporting of 'unoccupied' states in C09/C11 proves the device is online and communicating, ruling out total offline status.

Comparison with living_room/bedroom which show normal 'occupied' activity, confirming system-wide logging health.

Logs for bathroom_water_leak_detector and bathroom_light (OnOff) to determine if they are also silent or just not triggered.

Contextual data on actual human presence in the bathroom during C09 and C11 to validate if 'unoccupied' is the correct state.

Configuration settings for the occupancy sensor (e.g., timeout values, sensitivity) to rule out misconfiguration.

No 'occupied' events are logged for the bathroom after 09:22, consistent with the room being empty.

The water_leak_detector and onoff_light show no activity, which is normal for an empty bathroom.

Check for 'occupied' events in C06-C08 and C10 to determine if the bathroom was used between the observed chunks.

Verify water_leak_detector and onoff_light logs in all chunks to assess their status (silent vs. active).

Analyze the periodicity of 'unoccupied' reports: are they state-change events or periodic heartbeats? If heartbeats, the lack of 'occupied' is less indicative of a fault than if they are change-only.

The investigator correctly identifies that the occupancy sensor only reports 'unoccupied' in C09/C11, but concludes this might be a fault without sufficient context.

Crucially, the investigation ignores the gap between C05 (morning) and C09 (afternoon). We do not know if the bathroom was used during C06-C08. If it was used and no 'occupied' event was logged, that is strong evidence of a fault (missed detection). If it wasn't used, the 'unoccupied' readings are correct.

The current evidence is insufficient to distinguish between 'sensor stuck/failing to detect' and 'room simply empty'.

Additionally, the query asks about 'sensors' (plural), including water leak and light. The investigator notes these are missing/silent but doesn't actively check other chunks for them, leaving their status unknown rather than confirmed faulty or normal.

Need to review intermediate chunks (C06-C08, C10) to establish usage patterns before concluding a fault.

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

## 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": 482,
    "bedroom": 493,
    "kitchen": 308,
    "bathroom": 55,
    "entrance": 3
  },
  "attribute_frequency": {
    "MeasuredValue": 870,
    "Occupancy": 442,
    "OnOff": 18,
    "StateValue": 4,
    "CurrentPositionLiftPercent100ths": 3,
    "SystemMode": 1,
    "OperationalState": 1,
    "LockState": 1
  },
  "lock_state_flips": 1,
  "occupancy_events": 442,
  "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": "2026-06-07T00:00:00",
    "end_ts": "2026-06-07T01:50:00",
    "event_count": 80,
    "rooms": {
      "living_room": 27,
      "bedroom": 27,
      "kitchen": 22,
      "bathroom": 4
    },
    "top_devices": [
      "living_room_temp_s

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

## 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": [
      "bathroom"
    ],
    "target_devices": [
      "water_leak_detector",
      "onoff_light",
      "occupancy_sensor"
    ],
    "target_question": "判断 bathroom 区域的传感器是否工作正常。如果异常，请说明可能的故障类型。"
  },
  "focus_rooms": [
    "bathroom"
  ],
  "focus_devices": [
    "bathroom_occupancy",
    "bathroom_light",
    "bathroom_water_leak"
  ],
  "focus_chunk_ids": [
    "C05",
    "C09",
    "C11"
  ],
  "suspected_patterns": [
    "missing_device_logs",
    "intermittent_connectivity",
    "sensor_stuck_state"
  ],
  "why_these_chunks": [
    "C05 contains the first significant activity in the bathroom (light off, occupancy transitions), providing a baseline for device responsiveness.",
    "C09 and C11 show subsequent occupancy events ('unoccupied' at 14:19 and 16:49) which are critical to verify if the sensor is reporting correctly or if logs are missing due to connectivity issues.",
    "These chunks allow comparison of event frequency and specific device presence against other active rooms to detect silent failures."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The bathroom occupancy sensor is functioning correctly, but the room was unoccupied for the majority of the day. The 'unoccupied' reports are periodic heartbeats or state-change confirmations from a single morning usage event.",
      "evidence": [
        "C05 shows a clear usage pattern: Occupancy transitions to 'occupied' at 09:10 and back to 'unoccupied' at 09:22. This indicates a valid detection cycle.