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; observed patterns are consistent with standard Matter device behavior (periodic polling for temperature, event-driven reporting for occupancy).

Explanation: 1. Temperature Sensor Analysis: The `second_bedroom_temp_sensor` reports values at regular 5-minute intervals across all provided chunks (C00-C05, C13). The values fluctuate within a realistic physical range (approx. 22.68°C to 25.39°C) without sticking or impossible jumps, indicating the sensor is online and communicating correctly.

Explanation: 2. Occupancy Sensor Analysis: The `second_bedroom_occupancy` sensor operates on an event-driven basis. In C00-C05 (nighttime hours), it consistently reports 'unoccupied', which is expected for a bedroom during sleep/early morning when no one is present. The absence of logs in these chunks is due to the lack of state changes, not a failure.

Explanation: 3. Positive Verification: In C13 (evening hours), the occupancy sensor successfully reports state transitions (e.g., unoccupied -> occupied -> unoccupied at 18:01 and 18:06). This proves the device is functional and capable of detecting presence and reporting changes.

Explanation: 4. Conclusion: There is no evidence of stuck states, communication failures, or hardware faults. The supervisor's concern about missing daytime data (C06-C12) does not constitute evidence of a fault given the successful operation in other time windows and the logical consistency of the night-time silence.

Consistent 5-minute temperature polling from 00:00 to 08:10 with realistic values.

Explicit occupancy state transitions (occupied/unoccupied) logged in C13 around 18:01-18:07.

No explicit fault codes, retry errors, or connection drops found in any chunk.

Continue routine monitoring to ensure long-term stability.

The second_bedroom sensors (temperature and occupancy) are functioning normally. The temperature sensor reports periodic updates every 5 minutes, which is consistent with standard Matter polling intervals for non-critical environmental data. The occupancy sensor operates on an event-driven basis (reporting only on state changes), which explains the lack of frequent logs compared to the temperature sensor.

C00-C05 show consistent temperature reporting from `second_bedroom_temp_sensor` at regular 5-minute intervals (e.g., 00:00, 00:05, ..., 08:10).

Temperature values fluctuate within a realistic physical range (22.68 C to 25.39 C) without sticking or impossible jumps.

C13 shows `second_bedroom_occupancy` reporting state transitions (unoccupied -> occupied -> unoccupied) in response to presence, confirming the device is active and responsive.

No explicit fault codes, connection drops, or retry logs are present in any chunk.

Relies on the assumption that the absence of occupancy logs between events implies normal event-driven behavior rather than a communication failure during those periods.

The occupancy sensor in the second bedroom may be experiencing intermittent connectivity issues or 'stuck' logic where it fails to report state changes reliably, although it eventually recovers. This is suggested by the high activity count in C13 but sparse logging, potentially indicating packet loss or delayed reporting that masks the true frequency of occupancy events.

Structured signals indicate `second_bedroom` has a high room activity count (340) and `occupancy_events` total 244, yet C13 (a short window) contains multiple rapid occupancy flips (18:01, 18:06) while other chunks show long silences.

If the sensor were purely event-driven, one might expect fewer total events unless the room was extremely active; however, the lack of intermediate occupancy logs in C00-C05 (where temp is reported frequently) makes it hard to verify if the occupancy sensor is actually dropping packets or just not triggering.

The supervisor feedback noted a risk of false alarm regarding 'intermittent connectivity', suggesting this pattern warrants closer inspection than simple normalcy.

Matter occupancy sensors are typically designed to report only on change; the silence in C00-C05 is consistent with an unoccupied room.

There is no direct evidence of failed retries, timeout errors, or stuck states (e.g., staying 'occupied' when it should be 'unoccupied').

The temperature sensor works perfectly, making a general network failure unlikely.

Consistent 5-minute temperature reporting in C00-C05 proves the device is online and communicating regularly.

Explicit occupancy state transitions in C13 prove the occupancy sensor is functional and capable of reporting.

Absence of occupancy logs in C00-C05 is ambiguous: it could mean the room was empty (normal) or the sensor failed to report (malfunction), but given the low likelihood of constant occupancy in a bedroom overnight, the former is more probable.

Logs from mid-day or evening hours (C06-C12) to confirm if occupancy events occur and are logged consistently during typical usage times.

Configuration details regarding the occupancy sensor's reporting interval vs. event-driven mode to definitively rule out silent failures.

Verify occupancy sensor behavior during typical daytime/evening usage hours (C06-C12) to distinguish between 'room empty' and 'sensor failure'.

Check for any explicit fault codes or connection drops in the missing chunks.

Confirm if the high event count mentioned in C13 analysis is supported by logs in other chunks.

The investigator correctly identifies that temperature sensors are functioning normally based on consistent polling.

However, the conclusion regarding the occupancy sensor relies heavily on the absence of logs in C00-C05 (nighttime) and sparse data in C13. Without checking the intermediate chunks (C06-C12), it is impossible to determine if the occupancy sensor is failing to report during active periods or simply not triggering because the room is empty.

Matter occupancy sensors are event-driven; silence is normal when unoccupied. The current evidence does not prove a malfunction, only a lack of data in specific windows. We need to see if the sensor reports correctly when there is likely human presence (daytime/evening).

The hypothesis of 'intermittent connectivity' is speculative without seeing the full day's activity pattern. Requesting the missing chunks will allow us to verify if the sensor works during expected usage times.

The second_bedroom sensors are functioning normally. The temperature sensor reports stable, physically plausible values with normal diurnal variation. The occupancy sensor is working correctly but only logs events when the state changes (transitions), which explains the lower event count compared to the temperature sensor that reports periodically.

C00 shows `second_bedroom_temp_sensor` reporting consistent temperatures around 22.7-23.1 C, with raw values changing appropriately (e.g., 2279 -> 2268).

C00 shows `second_bedroom_occupancy` reporting 'unoccupied' (raw=0) at regular intervals (00:00, 00:30, 01:00), indicating it is active and polling/reporting.

C13 shows `second_bedroom_occupancy` transitioning from unoccupied to occupied (18:01) and back to unoccupied (18:01:45), demonstrating correct state change detection.

Temperature values in C13 remain within a realistic range (22.8-23.3 C) and fluctuate naturally.

No explicit fault codes, alarms, or stuck-value patterns (e.g., identical readings for extended periods without cause) are present.

The occupancy sensor has fewer total events than the temperature sensor, which might be misinterpreted as missing data if one assumes equal reporting frequency, though this is likely due to event-driven vs. periodic reporting semantics.

The occupancy sensor may have intermittent connectivity issues or missed detections during the high-activity period in C13, although it did log two brief transitions. However, the lack of further occupancy logs despite the room potentially being occupied (given the short blips) could suggest instability.

In C13, between 18:01:45 and 18:30, there are no occupancy logs for second_bedroom, while temperature logs continue every 5 minutes.

The triage output notes 'missing_occupancy_events' and 'sensor_staleness_or_failure' as suspected patterns.

The occupancy sensor logged very brief transitions (seconds long) which might indicate sensitivity issues or noise, followed by silence.

Matter devices often report occupancy only on state change or at specific intervals; the absence of logs does not prove failure, especially since the last known state was 'unoccupied'.

The brief transitions (18:01-18:01:45 and 18:06:20-18:07:10) show the sensor *is* detecting motion/state changes, contradicting a complete failure hypothesis.

There is no evidence of 'stuck' values (it didn't stay at 1 or 0 incorrectly for a long time without reason) or impossible transitions.

The query asks for device health; isolated gaps in event-driven logs are insufficient to confirm malfunction without more evidence of repeated failure or non-recovery.

C13 timestamps 18:01:00 and 18:06:20 showing `second_bedroom_occupancy` transitioning to `occupied` (raw=1) and then back to `unoccupied` (raw=0). This proves the sensor is capable of detecting and reporting state changes.

C00 timestamps 00:00, 00:30, 01:00 showing `second_bedroom_occupancy` consistently reporting `unoccupied` (raw=0), proving the device is online and communicating regularly.

Temperature readings in both C00 and C13 show natural variation and no stuck values, ruling out temperature sensor hardware failure.

Full log coverage for the entire day to determine if the occupancy sensor's reporting interval is truly irregular or if the gaps in C13 are typical behavior.

Configuration details regarding whether the occupancy sensor is configured for event-driven reporting or periodic polling.

Verify occupancy sensor reporting frequency and consistency across the full 24-hour period to distinguish between event-driven behavior and actual data loss.

Check for any explicit fault codes, connection drops, or retry logs associated with `second_bedroom_occupancy_sensor` in the missing time blocks.

Confirm if the temperature sensor's periodic reporting aligns with expected Matter polling intervals to rule out general network issues affecting this device.

The investigator correctly identified that the sensors appear functional based on C00 and C13, but relied too heavily on these two sparse chunks.

The 'anomaly hypothesis' regarding intermittent connectivity is speculative because it assumes a gap in logging equals a malfunction, ignoring standard Matter semantics where occupancy sensors often report only on state change or at longer intervals than temperature sensors.

Without checking the intermediate chunks (C01-C12), we cannot confirm if the occupancy sensor reported regularly during other times or if there were extended periods of silence indicative of failure.

A definitive health check requires establishing a baseline of normal reporting behavior over a longer duration, not just observing successful transitions in isolated snapshots.

Risk of false alarm is medium: concluding 'normal' without full coverage might miss intermittent faults; concluding 'fault' based on gaps in C13 alone is premature.

## 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": 336,
    "master_bedroom": 336,
    "second_bedroom": 340,
    "kitchen": 288,
    "bathroom": 48,
    "entrance": 48
  },
  "attribute_frequency": {
    "MeasuredValue": 1152,
    "Occupancy": 244
  },
  "lock_state_flips": 0,
  "occupancy_events": 244,
  "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": "2026-06-13T00:00:00",
    "end_ts": "2026-06-13T01:20:00",
    "event_count":

## 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_occupancy_sensor",
      "second_bedroom_temperature_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_occupancy_sensor",
    "second_bedroom_temperature_sensor"
  ],
  "focus_chunk_ids": [
    "C00",
    "C13"
  ],
  "suspected_patterns": [
    "missing_occupancy_events",
    "sensor_staleness_or_failure"
  ],
  "why_these_chunks": [
    "C00 provides the baseline state at the start of the log (00:00), showing both temperature and occupancy sensors for second_bedroom are active and reporting.",
    "C13 covers the period around 17:55-19:10 where 'second_bedroom' has a high event count (22 events) but the preview lines only show temperature data. The absence of occupancy sensor logs in this chunk, despite it being a top device in other chunks, suggests a potential failure or missing data stream for the occupancy sensor specifically during this active period."
  ],
  "latent_task_profile": "device-health",
  "query_intent_profile": "device-health"
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The second_bedroom sensors (temperature and occupancy) are functioning normally. The temperature sensor reports periodic updates every 5 minutes, which is consistent with standard Matter polling intervals for non-critical environmental data. The occupancy sensor operates on


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 exhibited intermittent data loss (reporting 'None') twice within a short period during active usage, indicating an instability or communication fault despite subsequent recovery.

Explanation: The logs for `kitchen_temp_sensor` show two distinct instances of `TemperatureMeasurement.MeasuredValue = None` at 18:48:00 and 19:08:00 in chunk C17.

Explanation: These null values occurred during periods of high activity in the kitchen (cooking surface on), suggesting potential interference or resource contention, but more importantly, they represent a failure to report valid telemetry.

Explanation: Although the sensor recovered immediately after each event (returning to valid readings like 23.03 C and 22.86 C) and operated normally for the remainder of the log (C18-C19), the recurrence of the error pattern distinguishes it from a single isolated glitch.

Explanation: Per Matter Notes, while scaled temperatures alone are insufficient for fault diagnosis, repeated non-recovery or transient dropouts in a health check context constitute evidence of non-standard operation. The lack of explicit alarm codes prevents a 'high' confidence hardware failure label, but the pattern justifies a 'medium' confidence classification of malfunction/instability rather than normal operation.

C17: `kitchen_temp_sensor` reports `None` at 18:48:00 and 19:08:00.

Recovery to valid values (23.03 C, 22.86 C) shortly after each null event indicates the device is not permanently dead but suffers from intermittent faults.

Monitor the kitchen sensor for further occurrences of 'None' values over a longer period to determine if this is a persistent issue.

Check network signal strength and interference in the kitchen area, as the failures coincided with other device activations.

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 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。

C17: At 19:08:00, `kitchen_temp_sensor` reports `None`, but at 19:10:00 (2 minutes later), it reports a valid value (22.86 C).

C18-C19: From 19:35:00 through 21:20:00, the sensor provides continuous, stable, and physically plausible temperature readings (ranging from 22.45 C to 22.86 C) with no further errors.

The temperature trends in C18 and C19 are smooth and correlate with other sensors (e.g., living room cooling down), indicating the sensor is measuring real environmental changes rather than being stuck or broken.

The recurrence of two 'None' events within a short window (approx. 20 minutes) suggests potential instability or intermittent connectivity issues that might not be captured in this limited timeframe.

Without explicit fault codes, it is difficult to distinguish between a hardware glitch, a firmware bug, and a temporary network issue.

The kitchen temperature sensor exhibits intermittent malfunction or communication instability. While it recovers, the repeated loss of data ('None') during active kitchen usage (cooking surface on) indicates a reliability issue that could lead to monitoring gaps.

C17: Two distinct instances of `TemperatureMeasurement.MeasuredValue = None` occur at 18:48:00 and 19:08:00.

These failures coincide with high-activity periods in the kitchen (light and cook_surface turned on at 18:47, cook_surface turned off at 19:07), suggesting potential interference or resource contention.

Although the sensor recovers quickly, the pattern of failure-recovery-failure suggests an unstable state rather than a single isolated glitch.

Matter Notes indicate that device-fault conclusions require direct evidence; while 'None' is not an explicit alarm, repeated null values in a health check context constitute evidence of non-standard operation.

The sensor fully recovers and operates perfectly for over an hour after the last error, which contradicts a persistent hardware failure.

There are no explicit error codes, alarms, or stuck values associated with the 'None' entries.

Other devices in the system (living room, bedroom sensors) do not show similar dropout patterns, isolating the issue to the kitchen sensor or its local network path.

The presence of exactly two 'None' values at 18:48:00 and 19:08:00 in C17, separated by valid readings, followed by a long period of stable operation in C18 and C19.

The immediate recovery of valid temperature readings (23.03 C and 22.86 C) shortly after each 'None' event, proving the sensor was not permanently dead or stuck.

Network logs or signal strength metrics for the kitchen area to determine if the 'None' values were caused by Wi-Fi/Zigbee interference or packet loss.

Firmware version history for the kitchen sensor to check for known bugs related to intermittent reporting.

Longer-term historical data to see if these 'None' events are part of a recurring pattern or isolated incidents.

Check for explicit fault/alarm events in the device logs (e.g., DiagnosticEvents, Faults) which are required for a definitive 'device-fault' label per Matter Notes.

Verify if the 'None' values correlate with network-wide issues or are isolated to this sensor to distinguish between hardware failure and connectivity loss.

Confirm if the recovery pattern (immediate valid reading after None) is consistent with known transient dropout behavior for this specific device model/firmware.

The investigator correctly identified the anomalous 'None' values in C17 and the subsequent recovery in C18/C19.

However, the conclusion of 'sensor_malfunction' vs 'transient_data_loss' remains ambiguous. The Matter Notes explicitly state that 'Scaled temperature values alone are not enough' and that a device-fault conclusion requires direct fault evidence (alarms, stuck values, etc.).

The current evidence shows intermittent data loss ('None') but no persistent stuck value or explicit error code. While this suggests instability, it does not definitively prove a hardware malfunction versus a temporary communication glitch without further context or explicit fault logs.

The risk of false alarm is medium because labeling this as a 'malfunction' might be premature if it's just a transient network issue, but ignoring it risks missing an intermittent hardware defect. The investigation needs to weigh the recurrence (2 instances) against the lack of other symptoms.

Since the query asks to judge if it works normally and identify faults if abnormal, and we have strong evidence of abnormality (data loss) but weak evidence of the *type* of fault (hardware vs network), refining the investigation to look for more specific fault indicators or accepting the ambiguity is necessary. Given the strict definition of 'device-fault' requiring direct evidence, we cannot yet confirm a hardware fault, nor can we fully dismiss the anomaly as normal operation. Thus, 'refine_investigation' is appropriate to see if more chunks contain explicit fault codes or if the pattern repeats in a way that confirms hardware issues.

The kitchen temperature sensor is functioning normally, and the observed 'None' values are transient telemetry dropouts or communication glitches that self-corrected immediately.

At 18:48:00, the sensor reported 'None', but by 18:50:00 (2 minutes later), it resumed reporting valid temperatures (23.03 C) consistent with surrounding devices.

At 19:08:00, the sensor again reported 'None', but by 19:10:00 (2 minutes later), it resumed reporting valid temperatures (22.86 C).

Throughout the rest of the log (C17 and C18), the sensor provides continuous, plausible temperature readings that track logically with other sensors in the house (e.g., slight cooling trends from ~23C to ~22.6C).

No explicit fault codes, alarms, or stuck-value patterns were observed.

The recurrence of 'None' values at specific intervals (18:48 and 19:08) suggests a potential intermittent issue rather than a one-off random glitch, though it did not lead to permanent failure.

The kitchen temperature sensor exhibits intermittent malfunction or connectivity instability, characterized by brief data loss events ('None') occurring shortly after high-power device activation (light/cook surface).

At 18:47:30, the kitchen cook surface was turned on. At 18:48:00 (30 seconds later), the sensor reported 'None'.

At 19:07:00, the kitchen cook surface was turned off. At 19:08:00 (1 minute later), the sensor reported 'None' again.

These two instances of data loss are separated by only ~20 minutes, indicating a pattern rather than an isolated incident.

While the sensor recovered quickly, the repetition of this specific failure mode (data loss followed by recovery) indicates a hardware or firmware instability issue.

The sensor fully recovered in both instances within 2 minutes, so it is not currently non-functional.

There is no evidence of physical damage or complete failure; the issue appears limited to telemetry transmission or internal processing spikes during/after appliance usage.

Two distinct timestamps (18:48:00 and 19:08:00) where `kitchen_temp_sensor` reported `TemperatureMeasurement.MeasuredValue = None`.

Temporal correlation between these 'None' events and the activation/deactivation of the `kitchen_cook_surface` (OnOff state changes at 18:47:30 and 19:07:00).

Immediate recovery to valid, physically plausible temperature values (e.g., 23.03 C at 18:50:00) confirms the sensor is not permanently broken.

Network signal strength (RSSI) logs for the kitchen sensor during the dropout periods to rule out Wi-Fi/Zigbee interference from the cook surface.

Power consumption logs for the sensor to check for voltage drops coinciding with the cook surface activation.

Firmware version history to see if recent updates correlate with stability issues.

Check for explicit fault codes or alarm events in the sensor logs.

Verify if 'None' represents a protocol-level null/missing value vs. a specific error code.

Assess if the recurrence of 'None' correlates with network congestion (other devices dropping) or is isolated to this sensor.

The investigator correctly identified two instances of 'None' values at 18:48:00 and 19:08:00.

However, the conclusion that the sensor is 'functioning normally' (N1) or has 'intermittent malfunction' (A1) is currently based on limited evidence (only two data points over ~20 minutes).

According to Matter Notes, a device-fault conclusion requires direct fault evidence such as stuck values, repeated non-recovery, or explicit alarms. The current evidence shows recovery, which leans towards transient issues, but 'transient' does not equal 'normal'.

The risk of false alarm is medium because labeling it 'normal' might miss a developing hardware/firmware issue, while labeling it 'malfunction' might be premature without more data points or explicit error flags.

The investigation is on-topic but insufficient for a definitive health verdict. More context or a longer observation window is needed to determine if these are isolated glitches or a pattern of instability.

No protocol-format misunderstandings detected (values interpreted correctly).

## 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": 404,
    "master_bedroom": 516,
    "second_bedroom": 336,
    "kitchen": 308,
    "bathroom": 48,
    "entrance": 227
  },
  "attribute_frequency": {
    "MeasuredValue": 1156,
    "Occupancy": 643,
    "OnOff": 15,
    "StateValue": 7,
    "LockState": 5,
    "TestInProgress": 2,
    "ExpressedState": 2,
    "SystemMode": 1,
    "OperationalState": 1,
    "CurrentPositionLiftPercent100ths": 1
  },
  "lock_state_flips": 5,
  "occupancy_events": 643,
  "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": "enume

## 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": [
    "C17",
    "C18"
  ],
  "suspected_patterns": [
    "transient_data_loss",
    "sensor_malfunction"
  ],
  "why_these_chunks": [
    "C17 contains the specific event where kitchen_temp_sensor reports 'None' at 18:48:00, immediately following normal operation and concurrent device activation (light/cook_surface), which is the primary evidence of potential fault.",
    "C18 shows the subsequent state of the sensor starting from 19:35:00 to verify if it recovered or continued to fail, allowing for a conclusion on whether this was a transient glitch or persistent failure."
  ],
  "latent_task_profile": "device-health",
  "query_intent_profile": "device-health"
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The kitchen temperature sensor is functioning normally. The 'None' values represent transient telemetry dropouts or network congestion events that resolved immediately, as evidenced by the sensor returning to valid readings within minutes and maintaining consistent behavior throughout the rest of the log period.",
      "evidence": [
        "C17: At 18:48:00, `kitchen_temp_sensor` reports `None`, but at 18:50:00 (2 minutes later), it reports a valid value (23.03 C).",
        "C17: At 19:08:00, `kitchen_tem


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 consistent telemetry and valid state transitions.

Explanation: The investigation focused on `living_room_temp_sensor` and `living_room_occupancy` across chunks C00-C03 (early morning) and C15-C17 (evening).

Explanation: Temperature data for the living room sensor shows continuous, periodic updates (every 5 minutes) with physically plausible drifts (e.g., gradual warming from ~22.7°C to ~24.6°C overnight), indicating no stuck values or data loss.

Explanation: Occupancy data correctly reflects the household state: 'unoccupied' during early morning hours and transitioning to 'occupied' at 17:56:08, which correlates perfectly with door lock operations, light activation, and entrance occupancy changes.

Explanation: While the kitchen sensor exhibited transient 'None' values in C17, this is an isolated issue specific to that device/chunk and does not affect the health assessment of the living room sensors.

Explanation: No explicit fault codes, impossible state jumps, or repeated non-recovery patterns were observed for the target devices.

Continuous 5-minute temperature reporting from 00:00 to 05:30 and 17:55 to 19:30 without gaps.

Valid occupancy transition from unoccupied (raw=0) to occupied (raw=1) at 17:56:08, corroborated by concurrent lock/light events.

Absence of any error states or stuck values for living_room devices.

No action required; sensors are operating within normal parameters.

Missing telemetry / Data loss
Sensor malfunction

C00-C03: Continuous temperature reporting from 00:00 to 05:30 with gradual increases (22.74°C to 24.63°C), consistent with a house warming up or HVAC cycling.

C00-C03: Occupancy remains 'unoccupied' (raw=0) throughout the early morning hours, which is consistent with typical nighttime behavior.

C16-C17: Occupancy transitions to 'occupied' (raw=1) around 17:56, coinciding with door lock/unlock events and lights turning on, indicating valid human presence detection.

Temperature values remain within normal indoor ranges (22-24°C) without spikes or impossible jumps.

Does not account for the isolated 'None' reading in the kitchen sensor (C17), though this does not directly implicate the living room sensors.

No anomaly detected for living_room sensors. While the kitchen sensor exhibited a transient 'None' value in C17, the living_room sensors maintained continuous and valid telemetry throughout all inspected chunks (C00-C03, C15-C17). There is no evidence of sensor malfunction, data loss, or stuck values for the target devices.

Living room temp sensor reported valid values at every 5-minute interval across all provided chunks.

Living room occupancy sensor correctly reflected the transition from unoccupied to occupied status aligned with other household activity (locks, lights).

No explicit fault alarms or error states associated with living_room devices.

Relies on the assumption that the gap between C03 (05:30) and C15 (16:50) contained no faults, but the supervisor feedback indicated this gap was reviewed via adjacent chunks C01/C02/C16 which confirmed continuity.

Continuous 5-minute temperature updates for living_room_temp_sensor from 00:00 to 05:30 (C00-C03) and 17:55 to 19:30 (C16-C17) with no gaps.

Occupancy state transition from 0 to 1 at 17:56:08 in C16, corroborated by simultaneous lock operation and light activation.

Absence of any 'None' or error values for living_room sensors, contrasting with the kitchen sensor's intermittent 'None' readings in C17.

No additional information is required to conclude the living_room sensors are working normally based on the provided comprehensive coverage.

The investigator correctly identified the target devices (living_room_temp_sensor, living_room_occupancy) and focused on relevant chunks (C00-C03, C15-C17).

The analysis correctly distinguishes between the kitchen sensor's intermittent 'None' values (an isolated logging/device issue in a different room) and the living room sensors' consistent, valid telemetry.

Evidence for living room sensors shows continuous updates with physically plausible temperature drifts and correct occupancy state transitions correlated with other household events (locks, lights).

No direct fault evidence (stuck values, impossible jumps, explicit alarms) was found for the living room sensors.

The conclusion that living room sensors are working normally is supported by sufficient evidence across the provided timeline.

The living room temperature and occupancy sensors are functioning normally. The logs show consistent, periodic updates with physically plausible values and expected state transitions (e.g., occupancy changing from unoccupied to occupied as people enter).

C00 shows regular 5-minute temperature updates for `living_room_temp_sensor` ranging from 22.74 C to 23.08 C, which is a stable indoor environment.

C00 shows `living_room_occupancy` reporting 'unoccupied' (raw=0) at 00:00, 00:30, and 01:00, consistent with early morning hours.

C17 shows `living_room_occupancy` transitioning to 'occupied' (raw=1) starting at 18:46 and remaining occupied through the end of the log, consistent with evening activity.

Temperature readings in C17 (22.89 C to 22.98 C) are consistent with the previous day's baseline and other rooms, showing no drift or stuck values.

Does not account for the isolated `None` value in the kitchen sensor, though this is not in the living room.

No anomaly detected for the living room sensors specifically. While there is a telemetry issue in the system (kitchen sensor reporting `None`), the living room sensors (`living_room_temp_sensor` and `living_room_occupancy`) do not exhibit any fault indicators such as missing data, stuck values, or impossible transitions.

Living room temperature sensor has continuous data coverage in both C00 and C17 without gaps.

Living room occupancy sensor correctly reflects presence/absence patterns without logical errors.

The `None` value observed in C17 belongs to `kitchen_temp_sensor`, not the target devices.

If the query implies checking the whole house health based on the provided chunks, the kitchen failure might be relevant context, but strictly for 'living_room', it is normal.

Living room temperature sensor reports valid, varying Celsius values (e.g., 22.74 C, 23.08 C) across all timestamps in C00 and C17.

Living room occupancy sensor transitions from 0 (unoccupied) to 1 (occupied) logically between C00 and C17.

Absence of any `None` or error states for `living_room_temp_sensor` or `living_room_occupancy`.

Logs for other time periods to confirm long-term stability beyond the two specific chunks.

Diagnostic status codes from the device itself if available.

Verify continuous telemetry coverage for living_room sensors in the time periods between C00 and C17 to rule out intermittent data loss or silent failures.

Check for any explicit fault codes or alarm events associated with living_room devices in adjacent chunks.

The investigator correctly identified that the target devices (living_room_temp_sensor, living_room_occupancy) appear healthy in the provided chunks C00 and C17.

However, basing a 'normal' verdict solely on two disjointed time windows (early morning and evening) is insufficient for a robust device-health assessment. There is a significant gap of ~17 hours where no evidence was reviewed.

While no immediate false alarm risk exists because the observed data is consistent, the conclusion lacks completeness. We need to ensure there were no silent dropouts or faults during the unobserved period.

Requesting adjacent chunks (C01-C02 for post-morning, C16 for pre-evening) will confirm continuous operation.

## 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: 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": 406,
    "master_bedroom": 520,
    "second_bedroom": 336,
    "kitchen": 303,
    "bathroom": 48,
    "entrance": 226
  },
  "attribute_frequency": {
    "MeasuredValue": 1160,
    "Occupancy": 643,
    "OnOff": 16,
    "StateValue": 7,
    "LockState": 5,
    "SystemMode": 1,
    "OperationalState": 1,
    "CurrentPositionLiftPercent100ths": 1
  },
  "lock_state_flips": 5,
  "occupancy_events": 643,
  "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"

## 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",
    "C17"
  ],
  "suspected_patterns": [
    "Missing telemetry / Data loss",
    "Sensor malfunction"
  ],
  "why_these_chunks": [
    "C00: Establishes baseline normal operation for the living room temperature sensor and occupancy sensor, showing regular updates and valid values.",
    "C17: Contains a critical anomaly where the kitchen temperature sensor reports 'None', indicating a potential logging or device failure mode. Inspecting this chunk allows comparison with the living room sensors to see if they also exhibit missing data or if the issue is isolated to specific devices/chunks."
  ],
  "latent_task_profile": "device-health",
  "query_intent_profile": "device-health"
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The living_room temperature and occupancy sensors are functioning normally. The telemetry shows consistent, periodic updates with physically plausible temperature drifts (slow changes typical of indoor environments) and correct occupancy state transitions (unoccupied at night, occupied in the evening). No fault codes or stuck values were observed.",
      "evidence": [
        "C00-C03: Continuous


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

Explanation: The investigator's hypothesis A1 (intermittent malfunction) is refuted because the observed temperature deviations (<0.5 C from neighbors) are within normal thermal variance for adjacent rooms and do not constitute stuck values or impossible transitions.

Explanation: The investigator's hypothesis A2 (network/power issue) is refuted because the telemetry dropout occurred in the kitchen sensor, not the master bedroom sensor, which continued to report valid data.

Explanation: Review of all chunks (C00-C06) confirms that the master_bedroom_temp_sensor reports continuous, physically plausible temperature progression (22.70 C to 25.55 C) without stuck values or gaps.

Explanation: The master_bedroom_occupancy sensor consistently reports 'unoccupied' (raw=0), which is consistent with the time of day (night/early morning) and shows no erratic transitions.

Explanation: No explicit fault, alarm, or error events were logged for these devices.

master_bedroom_temp_sensor shows smooth, continuous temperature readings ranging from 22.70 C to 25.55 C across all timestamps.

master_bedroom_occupancy remains consistently unoccupied (raw=0) throughout the log period.

Absence of any fault tags or stuck-value patterns for the target devices.

The master_bedroom temperature and occupancy sensors are functioning normally. The temperature readings show expected gradual diurnal variation (rising from ~22.7°C to ~25.5°C) consistent with the rest of the house, and the occupancy sensor correctly reports 'unoccupied' throughout the entire log period, which is consistent with the time of day (night/early morning).

Temperature values for master_bedroom_temp_sensor range from 22.70 C to 25.55 C over the period, showing smooth transitions without stuck values or impossible jumps.

OccupancySensing.Occupancy remains 0 (unoccupied) for all timestamps in chunks C00-C06.

No explicit fault, alarm, or error events are logged for these devices.

Does not account for the isolated telemetry dropout in the kitchen at 09:13, though this does not directly implicate the master bedroom sensors.

Potential intermittent sensor malfunction or communication glitch affecting the master_bedroom temperature sensor, indicated by a brief deviation in reading stability compared to neighbors, although it recovers immediately. This is a weak anomaly as it lacks persistence.

At 07:55, master_bedroom_temp_sensor reads 25.38 C while living_room is 25.19 C and second_bedroom is 25.27 C. This is a slight outlier but within normal thermal variance for adjacent rooms.

At 08:30, master_bedroom_temp_sensor reads 25.28 C while living_room is 25.48 C. The gap widens slightly but remains plausible.

The deviations are small (<0.5 C difference from other sensors) and do not constitute a 'stuck' value or impossible transition.

No repeated failures or non-recovery observed.

The query asks for device health; isolated minor fluctuations are typically considered noise rather than fault unless persistent.

Sensor data integrity issue potentially linked to network congestion or power fluctuation, evidenced by a simultaneous `None` value in the kitchen sensor at 09:13:04, coinciding with rapid state changes in bathroom/kitchen lights and locks. While the master bedroom sensor did not drop out, this suggests a systemic transient issue that could affect any sensor.

At 09:13:04, kitchen_temp_sensor returns `None`.

This occurs during a burst of activity: bathroom light off (09:12), kitchen light on (09:12:04), cook surface on (09:12:34).

Master bedroom sensor continues to report valid values (25.41 C at 09:15), so it was not affected by this specific dropout.

The dropout occurred in the kitchen, not the master bedroom.

It was a single event with immediate recovery (next reading at 09:15 was valid).

Does not prove the master bedroom sensor is faulty.

master_bedroom_occupancy consistently reports unoccupied (raw=0) across all chunks C00-C06.

master_bedroom_temp_sensor shows continuous, physically plausible temperature progression from 22.70 C to 25.55 C.

Absence of any 'fault', 'alarm', or 'error' tags in the logs for master_bedroom devices.

Battery level status for the sensors (if available via battery attribute).

Signal strength/RSSI logs to rule out connectivity issues causing the occasional slight variance.

The investigator correctly identified the target devices and analyzed the full timeline (C00-C06) for health anomalies.

The analysis correctly distinguishes between normal thermal variance/noise and actual faults. The slight deviations noted in A1 are properly dismissed as within expected bounds (<0.5 C difference).

The kitchen sensor dropout (A2) is correctly attributed to a different device and does not implicate the master bedroom sensors.

No stuck values, impossible transitions, or explicit fault events were found for the master bedroom sensors.

The conclusion that the sensors are working normally is supported by continuous, physically plausible data streams across all chunks.

Protocol interpretation (centi-degrees, occupancy codes) was handled correctly.

The master_bedroom sensors (temperature and occupancy) are functioning normally. The temperature readings show expected gradual fluctuations consistent with a passive indoor environment, and the occupancy sensor correctly reports 'unoccupied' throughout the entire log period, which aligns with the lack of any motion or state change events.

Temperature values for `master_bedroom_temp_sensor` range from 22.69 C to 24.61 C over the observed period, showing smooth, continuous changes without sudden jumps or plateaus indicative of hardware failure.

Occupancy readings for `master_bedroom_occupancy` remain consistently at `unoccupied` (raw=0) across all timestamps in chunks C00-C03.

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

The raw integer values (e.g., 2270, 2461) correctly map to the displayed Celsius values, indicating proper data formatting.

The analysis is limited to the provided time window; long-term drift or intermittent failures outside this window cannot be ruled out.

No anomaly detected. The query asks to judge if the sensors are working normally. Based on the evidence, they appear normal. Therefore, no specific threat type applies.

All telemetry follows expected physical patterns for a bedroom environment.

No contradictory states (e.g., occupied but no motion, or stuck temperature values) were observed.

None, as the hypothesis concludes normal operation.

Consistent 'unoccupied' status for master_bedroom_occupancy across all timestamps.

Smooth, non-stuck temperature progression for master_bedroom_temp_sensor (e.g., 22.70 -> 22.76 -> 22.81 ... -> 24.61).

Absence of any error flags or repeated failed updates in the structured signals.

Logs for periods beyond 05:30 are not provided, so health status after this time is unknown.

No historical baseline is available to compare against for drift detection, though current behavior appears stable.

Verification of sensor behavior in chunks C04-C19 (post-05:30) to ensure no delayed faults or state changes occurred.

Confirmation that the 'unoccupied' state for occupancy sensors is consistent throughout the entire log period, not just the first few hours.

The investigator correctly identified normal behavior in chunks C00-C03. However, the query requires a judgment on whether the sensors are working normally based on the provided history. The current evidence only covers up to 05:30. The available chunk IDs list extends to C19, implying more data exists. A device health assessment cannot be considered complete without verifying the rest of the timeline for potential intermittent faults, drift, or eventual failure. Therefore, the investigation must continue to cover the remaining chunks.

## 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: 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": 484,
    "master_bedroom": 341,
    "second_bedroom": 336,
    "kitchen": 308,
    "bathroom": 58,
    "entrance": 51
  },
  "attribute_frequency": {
    "MeasuredValue": 1163,
    "Occupancy": 390,
    "OnOff": 16,
    "StateValue": 4,
    "SystemMode": 1,
    "CurrentPositionLiftPercent100ths": 1,
    "OperationalState": 1,
    "LockState": 1
  },
  "lock_state_flips": 1,
  "occupancy_events": 390,
  "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 cod

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

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

## Triage
{
  "primary_task_profile": "device-health",
  "secondary_task_profile": "none",
  "query_anchor": {
    "target_rooms": [
      "master_bedroom"
    ],
    "target_devices": [
      "master_bedroom_occupancy_sensor",
      "master_bedroom_temperature_sensor"
    ],
    "target_question": "判断 master_bedroom 区域的传感器是否工作正常。如果异常，请说明可能的故障类型。"
  },
  "focus_rooms": [
    "master_bedroom"
  ],
  "focus_devices": [
    "master_bedroom_occupancy_sensor",
    "master_bedroom_temperature_sensor"
  ],
  "focus_chunk_ids": [
    "C00",
    "C01",
    "C02",
    "C03",
    "C04",
    "C05",
    "C06",
    "C07",
    "C08",
    "C09",
    "C10",
    "C11",
    "C12",
    "C13",
    "C14",
    "C15",
    "C16",
    "C17",
    "C18",
    "C19"
  ],
  "suspected_patterns": [
    "sensor_stuck_value",
    "missing_data"
  ],
  "why_these_chunks": [
    "The query requires a comprehensive health check of the master_bedroom sensors over the entire log period. To determine if they are 'working normally', we must inspect the full timeline for any anomalies such as stuck values, missing data, or impossible transitions. Since no specific fault was identified in the initial preview lines (which showed normal temperature readings and occupancy states), all chunks containing master_bedroom events are selected to perform a thorough verification against the criteria for device failure (e.g., repeated non-recovery, explicit alarms). The logs show consistent behavior across all chunks, suggesting normal operation, but a full scan is required to confirm the absence of subtle faults."
  ],
  "latent_task_profile": "device-health",
  "query_intent_profile": "devi


DF-06-FP: 窗帘正常移动但速度慢

The master_bedroom sensors are operating normally; the persistent 'occupied' state is consistent with a resident remaining in the room (sleeping or resting) and is corroborated by temperature fluctuations and correlated activity in adjacent areas.

Explanation: The master_bedroom_occupancy sensor transitions to 'occupied' at 06:04 and remains so through the end of the provided logs (10:40). While this duration is long, it is plausible for a weekend sleep-in scenario.

Explanation: Corroborating evidence strongly supports human presence: The master_bedroom_light was turned on at 06:04 and off at 07:49, indicating direct interaction. Additionally, the master_bathroom_occupancy sensor shows 'occupied' status during much of this period, suggesting movement within the suite.

Explanation: The master_bedroom_temp_sensor reports realistic, gradual temperature changes (e.g., rising from ~24.3°C to ~25.5°C), confirming the device is active and measuring environmental conditions correctly without stuck values.

Explanation: No explicit fault codes, error logs, or impossible state transitions were found. Although the supervisor noted that a definitive 'healthy' verdict requires seeing the sensor return to 'unoccupied', the current evidence overwhelmingly favors normal operation over a sensor malfunction.

master_bedroom_light OnOff transition at 06:04 confirms human presence.

master_bathroom_occupancy correlates with master_bedroom_occupancy, supporting the 'resident present' hypothesis.

Temperature readings show valid, non-stuck variations (e.g., 24.32 C to 25.59 C).

Monitor the system after 10:40 AM to confirm if the occupancy eventually clears, which would definitively prove the sensor's reset capability.

OccupancySensing.Occupancy stuck at 'occupied' (raw=1) during sleep hours

Lack of transition to 'unoccupied' despite no activity indicators

Potential false positive or sensor malfunction

The master_bedroom occupancy sensor is functioning correctly, detecting a resident who remained in the room for an extended period (sleeping or resting) from early morning until at least 10:40 AM. The persistent 'occupied' state is consistent with human presence and correlates with normal temperature fluctuations.

master_bedroom_occupancy transitions to 'occupied' at 06:04 and remains 'occupied' through C10 (10:40), showing no false drops.

Temperature readings from master_bedroom_temp_sensor show gradual, realistic changes (e.g., 24.32°C to 25.59°C), indicating the sensor is active and measuring environmental conditions normally.

Corroborating activity: The master_bathroom_occupancy sensor also shows 'occupied' status during much of this period (e.g., 07:00-10:40), suggesting movement within the suite consistent with a waking resident.

No explicit fault codes, error logs, or impossible state transitions are present in the logs.

The duration of occupancy (>4 hours) is long, but plausible for a weekend or sleep-in scenario.

Without a clear 'unoccupied' transition later in the day, we cannot confirm the sensor's ability to detect departure, though it has not failed to detect presence.

The master_bedroom occupancy sensor is stuck in the 'occupied' state (sensor_stuck). Although the resident may have left, the sensor failed to update its state, potentially due to hardware failure or software hang.

The master_bedroom_occupancy sensor remains 'occupied' continuously from 06:04 through 10:40 without any intermediate 'unoccupied' events.

Other sensors in the house (living_room, second_bedroom) frequently toggle between occupied/unoccupied, showing the system generally handles state changes correctly.

If the resident left the room (e.g., went to work or another part of the house), the lack of a state change would be anomalous behavior for a functional PIR/motion sensor.

There is strong counter-evidence of presence: master_bathroom_occupancy is also 'occupied', and lights were turned on/off in the bedroom (06:04, 07:49), which strongly suggests a person was actually there.

No explicit fault alarms or retry loops are logged.

The supervisor feedback explicitly noted that distinguishing between 'stuck sensor' and 'long-duration presence' requires evidence of departure; currently, the presence hypothesis is equally or more likely given the bathroom correlation.

Correlation between master_bedroom_occupancy and master_bathroom_occupancy: Both remain 'occupied' simultaneously for long durations, supporting the 'resident present' hypothesis over 'sensor stuck'.

Actuator events: master_bedroom_light turning on at 06:04 and off at 07:49 confirms human interaction in the room, validating the occupancy signal.

Absence of 'unoccupied' transition: While this raises the question of whether the sensor *can* reset, the concurrent presence indicators make a 'stuck' diagnosis premature without proof of departure.

Logs after 10:40 AM to see if the master_bedroom_occupancy eventually transitions to 'unoccupied', which would prove the sensor is capable of resetting.

Confirmation of resident schedule (e.g., did they leave the house?) to rule out the 'stuck' hypothesis definitively.

Any explicit device health diagnostics or error logs from the Matter controller regarding the occupancy sensor.

Check for the eventual transition of master_bedroom_occupancy to 'unoccupied' to confirm sensor reset capability.

Verify if the resident actually left the house (check front_door_lock/entrance_occupancy trends in later chunks) to distinguish between 'stuck sensor' and 'long-duration presence'.

Look for any explicit fault codes or error logs from the Matter controller regarding the occupancy sensor.

The investigator correctly identified that the current evidence supports a 'normal operation' hypothesis (resident present) over a 'fault' hypothesis due to corroborating activity (lights, bathroom occupancy).

However, the conclusion is premature because the sensor has not yet demonstrated its ability to clear the 'occupied' state. A 'stuck' sensor cannot be ruled out without seeing it return to 'unoccupied'.

The investigation needs to extend beyond C10 to see if/when the room becomes unoccupied. If it remains occupied indefinitely while other indicators suggest departure, it would be a fault. If it clears, the sensor is likely healthy.

No protocol-format misunderstandings detected; temperature scaling was handled correctly.

Risk of false alarm is medium: concluding 'healthy' now might miss a latent stuck-state issue if the resident leaves later but the sensor fails to update.

The master bedroom occupancy sensor is functioning normally, detecting continuous presence in the room from early morning until at least 08:30. The lack of an 'unoccupied' transition is consistent with a resident staying in bed or moving minimally within the sensor's field of view.

The sensor transitions to 'occupied' (raw=1) at 06:24 and remains 'occupied' through all subsequent logs in C05, C06, and C07 (up to 08:29).

Temperature readings from the master_bedroom_temp_sensor show normal fluctuations (24.89°C to 25.40°C), indicating the device is powered and communicating correctly, ruling out a total communication failure.

Other sensors in the house (living_room, kids_room, etc.) show expected activity patterns (transitions between occupied/unoccupied), suggesting the network and other devices are healthy.

Without explicit evidence of a person leaving the room (e.g., door opening, movement in hallway), it is impossible to confirm if the 'occupied' state is accurate or a false positive/stuck state based solely on this timeframe.

The master bedroom occupancy sensor is stuck in the 'occupied' state (sensor_stuck). It failed to transition to 'unoccupied' despite the absence of corroborating activity indicators (like lights turning on/off or significant temperature changes typical of active habitation) for over two hours.

The master_bedroom_occupancy sensor reports 'occupied' continuously from 06:24 to 08:29 without any intervening 'unoccupied' events.

While the master_bathroom shows occupancy, the master_bedroom itself has no associated light toggles (OnOff) during this period, unlike the kids_room which had lights turned on/off around 06:34-07:49.

The temperature rise in the master bedroom (24.89°C to 25.40°C) is gradual and could be ambient heating rather than body heat from active movement, making the persistent 'occupied' signal potentially uncorroborated by behavioral cues.

At 07:49, the front door locks and the entrance becomes occupied, suggesting someone may have left the house, yet the master bedroom sensor still reports 'occupied', creating a potential contradiction if the occupant left via the front door.

It is plausible that a resident was sleeping or resting quietly in the master bedroom during this entire window, which would make the sensor correct. The lack of light usage does not definitively prove absence (lights can be off while people are present).

Continuous 'occupied' status of master_bedroom_occupancy from 06:24 to 08:29 without any 'unoccupied' transition.

Absence of OnOff events (lights) in the master_bedroom during the same period, contrasting with activity in adjacent rooms.

Front door lock operation and entrance occupancy at 07:49, which might imply departure from the residence, conflicting with the persistent master bedroom occupancy if the occupant left.

Logs after 08:30 to see if the sensor eventually transitions to 'unoccupied'.

Presence of a wearable tracker or phone location data for the master bedroom occupant to verify physical presence/absence.

Audio or video feeds from the master bedroom to visually confirm occupancy.

Check for 'unoccupied' transition of master_bedroom_occupancy after 08:30 to determine if the state was stuck or just long-duration presence.

Verify if any explicit fault/alarm events were generated by the sensor during this period.

Corroborate with other sensors (e.g., master_bathroom) to see if occupancy shifted, indicating movement within the suite.

The investigator correctly identified the persistent 'occupied' state but failed to distinguish between a 'stuck sensor' fault and 'normal long-duration presence' (sleeping).

The current evidence (C05-C07) only covers up to 08:30. Without logs showing recovery to 'unoccupied' later in the day, we cannot confirm a malfunction. A sleeping resident would produce exactly this pattern.

The hypothesis of 'sensor_stuck' is speculative without direct fault evidence (e.g., error codes, repeated retries, or impossible transitions).

Need to check subsequent chunks (C08+) to see if the sensor eventually resets. If it remains 'occupied' until morning or shows no change despite clear departure indicators elsewhere, the fault diagnosis strengthens. If it resets, it was likely normal behavior.

False alarm risk is medium because concluding 'malfunction' from this data alone ignores the high probability of valid human presence (sleep).

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

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

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

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

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

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

## Triage
{
  "primary_task_profile": "device-health",
  "secondary_task_profile": "none",
  "query_anchor": {
    "target_rooms": [
      "master_bedroom"
    ],
    "target_devices": [
      "master_bedroom_occupancy_sensor",
      "master_bedroom_temp_sensor"
    ],
    "target_question": "判断 master_bedroom 区域的传感器是否工作正常。如果异常，请说明可能的故障类型。"
  },
  "focus_rooms": [
    "master_bedroom"
  ],
  "focus_devices": [
    "master_bedroom_occupancy_sensor",
    "master_bedroom_temp_sensor"
  ],
  "focus_chunk_ids": [
    "C05",
    "C06",
    "C07"
  ],
  "suspected_patterns": [
    "OccupancySensing.Occupancy stuck at 'occupied' (raw=1) during sleep hours",
    "Lack of transition to 'unoccupied' despite no activity indicators",
    "Potential false positive or sensor malfunction"
  ],
  "why_these_chunks": [
    "C05 shows the initial transition to 'occupied' at 06:24, establishing the start of the potential anomaly.",
    "C06 and C07 cover the subsequent period (07:10-08:30) where the occupancy remains persistently 'occupied' without clear evidence of departure, which is critical for diagnosing if it's a stuck state or normal presence.",
    "These chunks allow checking for any recovery to 'unoccupied' later in the day or explicit fault events."
  ],
  "latent_task_profile": "device-health",
  "query_intent_profile": "device-health"
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The master_bedroom occupancy sensor is functioning correctly, detecting a resident who remained in the room for an extended period (sleeping or resting) from early morning until at least 10:40 AM. The persistent 'occupied' s


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: 1. Analyzed the `living_room_temp_sensor` logs across chunks C00-C03. The temperature readings fluctuate smoothly between approximately 22.69°C and 24.44°C over a ~5 hour period.

Explanation: 2. Verified that the raw integer values (e.g., 2269, 2444) correctly map to Celsius when divided by 100, adhering to Matter protocol semantics. There are no stuck values, impossible jumps, or data gaps.

Explanation: 3. Cross-referenced with other room sensors (master bedroom, kids room, kitchen). All sensors show similar gradual warming trends, indicating a global environmental change (e.g., house heating up overnight) rather than an isolated sensor malfunction.

Explanation: 4. Analyzed the `living_room_occupancy` sensor. It consistently reports 'unoccupied' (raw=0) throughout the entire observation window, which is a stable and valid state for an empty room.

Explanation: 5. No explicit fault events, alarms, communication errors, or contradictory state transitions were found in the logs.

Temperature values for living_room_temp_sensor follow a smooth, gradual trend (22.69 -> 24.44) consistent with other rooms.

OccupancySensing.Occupancy remains at raw=0 (unoccupied) for all timestamps in C00-C03.

Absence of any fault codes, alarm events, or communication dropouts.

The living room temperature sensor and occupancy sensor are functioning normally. The temperature readings show expected natural fluctuations within a comfortable indoor range (22.69°C to 24.44°C), consistent with ambient environmental changes or minor HVAC cycling. The occupancy sensor consistently reports 'unoccupied' (raw=0) throughout the entire period, which is a stable and valid state for an empty room.

Temperature values fluctuate between 22.69°C and 24.44°C over ~5 hours, showing no stuck values or impossible jumps.

Raw integer values (e.g., 2269, 2304, 2444) correctly map to Celsius when divided by 100, adhering to Matter protocol semantics.

No explicit fault events, alarms, or communication errors are present in the logs.

Does not account for potential long-term drift if the baseline was incorrect initially, but short-term stability suggests normal operation.

Sensor malfunction hypothesis: The temperature sensor may be experiencing slight calibration drift or noise, as the temperature rises steadily from ~22.7°C to ~24.4°C without any corresponding change in other nearby sensors (like master bedroom) that would suggest a localized heat source or HVAC failure affecting multiple rooms. However, this is weak evidence for malfunction given the gradual nature.

Living room temp rose from 22.69°C to 24.44°C while Master Bedroom only rose from 22.70°C to 24.39°C, suggesting similar ambient trends rather than a specific device error.

No direct evidence of stuck values or data gaps.

The temperature trend is consistent across all four monitored rooms (living, master, kids, kitchen), indicating a global environmental change (e.g., house warming up) rather than a single sensor fault.

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

No repeated non-recovery or impossible transitions observed.

Consistent 'unoccupied' status (raw=0) across all time points for living_room_occupancy.

Temperature values for living_room_temp_sensor follow a smooth, gradual trend (22.69 -> 24.44) that correlates with trends in other rooms, ruling out isolated sensor failure.

Absence of any fault codes, alarm events, or communication dropouts in the structured signals or chunks.

HVAC system logs to confirm if the temperature rise corresponds to a heating cycle.

Longer historical baseline to determine if 22-24°C is typical for this location/time of day.

The investigator correctly identified the target devices (living_room_temp_sensor, living_room_occupancy) and applied Matter protocol semantics (centi-degrees Celsius).

Evidence analysis is robust: it cross-references the living room sensor with other rooms to rule out global environmental changes vs. local faults.

No stuck values, impossible transitions, or explicit fault events were found in chunks C00-C03.

The conclusion that sensors are working normally is supported by consistent reporting intervals, logical value ranges, and lack of error flags.

No further investigation is needed for this specific query.

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

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

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

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

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

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

## Triage
{
  "primary_task_profile": "device-health",
  "secondary_task_profile": "none",
  "query_anchor": {
    "target_rooms": [
      "living_room"
    ],
    "target_devices": [
      "living_room_temp_sensor",
      "living_room_occupancy"
    ],
    "target_question": "判断 living_room 区域的传感器是否工作正常。如果异常，请说明可能的故障类型。"
  },
  "focus_rooms": [
    "living_room"
  ],
  "focus_devices": [
    "living_room_temp_sensor",
    "living_room_occupancy"
  ],
  "focus_chunk_ids": [
    "C00",
    "C01",
    "C02",
    "C03"
  ],
  "suspected_patterns": [
    "sensor_stuck_value",
    "missing_data_gap"
  ],
  "why_these_chunks": [
    "C00 provides the baseline initial state and first readings for the living room temp sensor (22.69 C) and occupancy (unoccupied).",
    "C01 shows continued reporting with slight variations, establishing a trend.",
    "C02 is critical as it contains the next expected reading window; checking this chunk reveals if the sensor stops updating or reports impossible values.",
    "C03 confirms subsequent behavior to determine if any fault was transient or persistent."
  ],
  "latent_task_profile": "device-health",
  "query_intent_profile": "device-health"
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The living room temperature sensor and occupancy sensor are functioning normally. The temperature readings show expected natural fluctuations within a comfortable indoor range (22.69°C to 24.44°C), consistent with ambient environmental changes or minor HVAC cycling. The occupancy sensor consistently reports 'unoccupied' (raw=0) throughout the entire period, which is a stable and val