EL-03-FP: 老人在旁边慢慢做饭

虽然老人短暂离开了厨房，但5分钟后回来检查，不是忘了关火

Global temperature sensor calibration failure causing invalid readings (2000-2500°C) that mimic a catastrophic fire but are physically impossible for domestic environments.

Explanation: Temperature values across all rooms consistently exceed 2000 degrees Celsius throughout the timeline, which is physically impossible for any residential scenario and indicates a unit mismatch or raw data reporting error rather than real heat.

Explanation: The anomaly is global and stable; if it were a real fire, temperatures would likely be concentrated in specific zones (e.g., kitchen), whereas here living rooms, bedrooms, and kitchens all report identical erroneous high values simultaneously.

Explanation: Despite the sensor failure, other systems function normally: occupants entered the home, lights turned on/off, the cook surface operated correctly, and the door lock was manually engaged without any smoke detector alarms or CO sensor triggers being recorded.

Timestamp 2026-06-10T07:05:00 shows Living Room at 2518°C while occupancy sensors confirmed human presence inside, ruling out external environmental causes.

Kitchen cook_surface state changed from On to Off as expected (05:50:33 to 06:36:00), and subsequent sensor logs show 'None' or erratic values instead of realistic thermal decay, confirming sensor blindness or corruption.

Immediately inspect and recalibrate/replace all temperature sensors in the home.

Verify no physical damage exists despite the false readings before considering evacuation.

This hypothesis assumes the hardware is functioning correctly but misconfigured. If the unit is actually Celsius, a reading of 2300°C would indicate catastrophic equipment failure or fire, not just calibration.

Does not explain why `kitchen_temp_sensor` returns `None` at specific times (05:51, 06:37) if it were simply a constant offset failure.

Delayed Occupancy Reporting

Occupancy sensors show '0' for all rooms from 00:00 to 05:30, despite high ambient heat suggesting activity or residual warmth from previous days.

Occupancy events spike only after 05:30 when lights turn on and temperatures continue to rise.

Structured signals show `occupancy_events`: 946 vs `lock_state_flips`: 4, suggesting the system registered many presence changes but perhaps lagged in room-level attribution.

A delay of 5+ hours for occupancy detection is highly irregular for standard PIR/RFID systems.

Cannot explain the initial massive temperature spike if no one was present to generate it, unless the house was pre-heated by an external event (fire/equipment).

Catastrophic Thermal Event (Fire or Equipment Failure)

Temperature values exceeding 2000°C (e.g., Living Room: 2518 at 07:05) are physically impossible for domestic environments and indicate either extreme real-world heat or total sensor data corruption.

If interpreted as real-world Celsius, this indicates a massive uncontained fire starting around 00:00 and intensifying through morning hours.

Correlation between rising temps and eventual human arrival suggests occupants entered a hazardous environment.

Kitchen cook_surface activates at 05:50 while temps are already >2400, indicating potential ignition source or post-ignition thermal runaway.

Could be a software bug where the sensor reports raw ADC counts instead of converted degrees (e.g., 2300 counts != 2300 degrees).

No smoke detector alarms or door lock breach attempts recorded prior to manual locking at 06:58, which might be expected in a rapid evacuation scenario.

Sensor Data Corruption / Firmware Glitch

Sudden `None` values in `kitchen_temp_sensor` logs at 05:51:03 and 06:37:00, breaking the continuous stream of high-value readings.

The absolute magnitude (>2000) is statistically anomalous for any known residential heating appliance.

Consistency of the error across multiple zones suggests a central processing issue rather than individual sensor failure.

Does not account for the *trend* of the numbers rising logically over time; a glitch usually results in static errors or random noise, not a coherent ramp-up curve.

Fails to explain why the system continued to log other valid state changes (locks, lights, window covers) during the same corrupted period.

The specific timestamp 2026-06-10T07:05:00 showing `living_room_temp_sensor` at 2518 and `bedroom_temp_sensor` at 2414 strongly points towards a physical anomaly (fire) rather than a simple unit mismatch, as such temperatures would cause structural damage regardless of units used.

The sequence `kitchen_cook_surface | OnOff.OnOff = True` (05:50:33) followed immediately by `kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = None` (05:51:03) indicates the sensor may have been destroyed or blinded by the event it was measuring.

Manual door lock operation at 06:58:05 (LockState=2 then 1) occurring after temperatures peaked suggests an intentional security measure taken in response to the perceived threat, distinguishing this from passive system failure.

Smoke detector status logs and alarm activation timestamps.

Video feed snapshots or motion blur analysis from entrance cameras to confirm occupant behavior upon entry.

Historical baseline temperature data for this specific home to confirm if 2000+ readings are a known persistent bug or a new anomaly.

Delayed Occupancy Reporting

The current investigation is on-topic, correctly identifying the critical thermal anomaly and potential fire risk.

Evidence sufficiency is low because the Investigator explicitly requested 'Smoke detector status logs' and 'Carbon monoxide (CO) sensor readings', which are absent from the currently selected chunks (C00-C05, C16).

The sequence of events suggests an active emergency (high heat, cook surface usage followed by sensor failure); therefore, the evidence collection must expand immediately into the post-incident timeline (Chunks C06-C09) to capture any subsequent safety system triggers (smoke alarms, evacuation attempts) or further state changes that occurred after the initial spike at 07:05.

Without data on smoke/CO sensors, the assessment of 'Life Safety' threat remains speculative rather than confirmed.

## Query
以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。

## Layout
Layout: 独居老人 (Elderly Living Alone)
- 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>, 床头灯<onoff_light>
- 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>, 厨房运动传感器<occupancy_sensor>
- living_room: 客厅温度传感器<temperature_sensor>, 客厅灯<dimmable_light>, 客厅烟雾报警器<smoke_co_alarm>, 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": 498,
    "bedroom": 529,
    "kitchen": 539,
    "bathroom": 59,
    "entrance": 230
  },
  "attribute_frequency": {
    "Occupancy": 946,
    "MeasuredValue": 870,
    "OnOff": 22,
    "CurrentPositionLiftPercent100ths": 4,
    "LockState": 4,
    "StateValue": 4,
    "CurrentLevel": 1
  },
  "lock_state_flips": 4,
  "occupancy_events": 946,
  "temperature_patterns": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-10T00:00:00",
    "end_ts": "2026-06-10T01:35:00",
    "event_count": 80,
    "rooms": {
      "living_room": 24,
      "bedroom": 24,
      "kitchen": 24,
      "bathroom": 4,
      "entrance": 4
    },
    "top_devices": [
      "living_room_temp_sensor",
      "bedroom_temp_sensor",
      "kitchen_temp_sensor",
      "living_room_occupancy",
      "bedroom_occupancy",
      "kitchen_occupancy"
    ],
    "alarmish_count": 20,
    "preview_lines": [
      "[2026-06-10T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2276",
      "[2026-06-10T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2165",
      "[2026-06-10T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2262",
      "[2026-06-10T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-10T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-10T00:00:00] kitchen_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-10T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-10T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-10T00:05:00] li

## Query
以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。

## Triage
{
  "latent_task_profile": "composite-safety | behavior-sequence",
  "focus_rooms": [
    "kitchen",
    "bedroom",
    "living_room"
  ],
  "focus_devices": [
    "temperature_sensor",
    "occupancy_sensor",
    "cook_surface",
    "door_lock",
    "contact_sensor"
  ],
  "focus_chunk_ids": [
    "C00",
    "C01",
    "C02",
    "C03",
    "C04",
    "C05",
    "C16"
  ],
  "suspected_patterns": [
    "Extreme temperature anomalies (values ~2100-2500 vs normal ~20-30) indicating sensor calibration failure or unit mismatch.",
    "Prolonged absence of occupants in living/bedrooms during early morning hours (C00-C03) while kitchen sensors report high activity or temperature.",
    "High frequency of 'alarmish' events correlating with temperature spikes.",
    "Potential fire risk due to unattended cooking indicated by cook_surface state changes in C16 after long periods of occupancy."
  ],
  "why_these_chunks": [
    "C00-C03: Show the initial period of total house vacancy combined with bizarrely high temperature readings, suggesting a system baseline issue or environmental hazard before arrival.",
    "C04-C05: Capture the transition where occupants return (high entrance/bathroom occupancy) coinciding with peak temperature values, critical for determining if the heat is human-generated (cooking/heating) or equipment failure.",
    "C16: Contains specific state change data for the cook_surface ('OnOff.OnOff = False'), which is essential for assessing immediate fire safety risks post-cooking.",
    "All chunks containing temperature_sensor data are required to analyze the magnitude and duration of the thermal anomaly."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "System Sensor Calibration Offset / Unit Mismatch",
      "evidence": [
        "All temperature readings across all rooms (Living: ~2276, Bedroom: ~2165, Kitchen: ~2262) are consistently in the 2000-2500 range throughout the entire timeline.",
        "The values remain relatively stable and correlate with expected diurnal heating patterns (slight rise as occupancy increases), suggesting a systematic error rather than random noise.",
        "No single sensor is reporting wildly different values compared to others; the offset appears global."
      ],
      "weaknesses": [
        "This hypothesis assumes the hardware is functioning correctly but misconfigured. If the unit is actual


温度异常上升但无合理热源（空调关闭/制冷模式，灶具关闭） 上升速度超过正常烹饪或日照导致的范围

火灾风险警报，建议住户检查该区域电器

An unauthorized intruder entered the residence via the front door between 07:29 and 07:30, activated kitchen appliances while occupants were in the master bedroom, and remained inside with sustained high occupancy readings.

Explanation: The front door contact state flipped to 'False' (open) at 07:29:20, immediately followed by the entrance occupancy sensor triggering at 07:29:21, confirming physical entry.

Explanation: Kitchen devices (light and cook surface) were activated sequentially at 06:39 and 06:39:40 while the house was reported empty until that moment, suggesting pre-entry preparation or immediate action upon entry.

Explanation: Entrance occupancy remained persistently high ('1') from 07:29 onwards, coinciding with a resident remaining in the master bedroom, indicating an intruder moving through the home rather than a transient event.

Explanation: The temperature spikes observed in later chunks (e.g., reaching ~25.4°C scaled values) correlate with appliance usage and potential environmental changes caused by the presence of multiple people or equipment failure, but the primary threat is the confirmed breach.

Front door contact opened (False) at 07:29:20, 1 second before entrance occupancy spiked to True at 07:29:21.

Sequential activation of kitchen light and cook surface at 06:39 despite zero occupancy prior to 06:35.

Continuous entrance occupancy signal starting at 07:29:21 and persisting throughout the log duration.

Master bedroom occupancy started at 06:35 and persisted, while the intruder accessed other areas including the kitchen.

Immediately call local law enforcement to report a break-in.

Do not enter the premises until authorities have secured the scene.

Preserve all digital logs, camera footage, and device states for investigation.

Check for signs of forced entry at the front door and any damage to kitchen appliances.

{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The house is empty with sensors reporting baseline ambient temperatures (scaled by x10) and no human activity.",
      "evidence": ["Occupancy sensors reported '0' for all rooms between 03:00 and 06:35.", "Temperature values in the 2300-2400 range are consistent with a stable indoor environment if scaled Celsius (~23-24°C)."],
      "weaknesses": ["Fails to account for the sudden spike in occupancy at 06:35 in the master bedroom.", "Cannot explain the rapid temperature increase observed after 06:40 coinciding with cooking events."]
    }
  ],
  "anomaly_hypotheses": [
    {
      "id": "A1",
      "description": "Unauthorized intrusion followed by a fire or extreme heat generation event inside the residence.",
      "threat_type": "Fire/Explosion/Intrusion",
      "evidence": ["At 07:29, the front door contact flipped to False (open) immediately before entrance occupancy spiked to 1. The lock state flipped twice within seconds, suggesting forced entry or tampering rather than normal manual locking/unlocking patterns.", "Starting at 06:39, kitchen devices activated (lights and cook surface), but the system was already in a high-temperature state (~25°C real-world equivalent).", "Between 06:40 and 08:44, temperatures rose from ~2500 to >2540 (real-world ~25-25.4°C? Or potentially higher if scaling changes or sensor drift occurs due to heat). *Correction based on data context*: If 2341 = 23.41C, then 2540 = 25.40C. This is not a fire temperature. Re-evaluating A1.",
      "revised_evidence_for_A1": ["At 07:29, the front door contact flipped to False (open) immediately before entrance occupancy spiked to 1. The lock state flipped twice within seconds (Manual Unlock -> Auto Lock), indicating an intruder entered via the front door.", "Simultaneous activation of kitchen lights and cook surface at 06:39 while the house was supposedly empty suggests either automated scheduling failure or manual activation by an intruder.", "Persistent high occupancy readings in the entrance (starting 07:29) and master bedroom (starting 06:35) despite no other room activity indicates someone moving through the house to a specific location."]
    },
    {
      "id": "A2",
      "description": "Sensor Malfunction causing false positives for both occupancy and temperature.",
      "threat_type": "False Positive/Data Integrity",
      "evidence": ["All temperature sensors show nearly identical values across different rooms simultaneously, which is physically unlikely without perfect thermal equilibrium (suggesting a shared data feed error or calibration offset).", "Occupancy sensors trigger sporadically ('flips') without corresponding motion logic in other zones.", "The 'MeasuredValue' attribute frequency is extremely high compared to discrete states like 'LockState' or 'SmokeState', suggesting a data stream flooding issue."],
      "weaknesses": ["Does not explain the precise temporal correlation between the front door opening (07:29:20) and the entrance occupancy signal (07:29:21). Physical causality is strong here.", "The sequential activation of kitchen appliances (light -> stove) follows a logical human pattern that random noise would not typically replicate."]
    }
  ],
  "most_discriminative_evidence": [
    "Temporal Sequence at 07:29: Front Door Contact -> False (Open) occurred 2 seconds BEFORE Entrance Occupancy -> True. This confirms physical entry.",
    "Device Activation Cluster: Kitchen Light and Cook Surface turned ON at 06:39 while the house was unoccupied until 06:35. This suggests pre-entry preparation or immediate post-entry action.",
    "Sustained Master Bedroom Occupancy: Once occupied at 06:35, the master bedroom remained occupied continuously until the end of the log, while other rooms cycled or stayed empty."
  ],
  "missing_information": [
    "Video footage or audio logs from the time of the intrusion (06:35 - 07:30) to confirm identity and actions.",
    "Historical temperature data prior to 02:40 to determine if the 'high' baseline (2341) was actually abnormal or the new normal.",
    "Confirmation of whether the 'Cook Surface' being ON resulted in smoke detection (SmokeState count is only 1 in structured signals, likely unrelated to this event)."
  ]
}

Verify if kitchen temperature spiked significantly during the appliance activation (C06-C10) to confirm heat source vs. sensor drift.

Cross-reference SmokeState logs with the specific time of stove activation and any subsequent temperature anomalies.

The current evidence collection is insufficient because it focuses heavily on the intrusion event (C02-C06, C17) and late-night activity (C20-C22), but completely ignores the critical window immediately following the intrusion (approx. 07:30 - 08:44).

The Investigator identified a temperature rise from ~2500 to >2540 between 06:40 and 08:44 as potentially significant (or needing re-evaluation of scaling). Chunks C07, C08, C09, and C10 cover this exact timeframe and are essential to determine if the kitchen fire hypothesis (A1) was validated by actual thermal spikes or if the 'high' temperature was merely a sensor anomaly.

Without these chunks, we cannot rule out that the stove activation led to a fire or excessive heat generation, which contradicts the initial assumption that 25°C is safe based solely on the raw integer values seen earlier.

## Query
以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。

## 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": 403,
    "master_bedroom": 515,
    "second_bedroom": 336,
    "kitchen": 304,
    "bathroom": 48,
    "entrance": 228
  },
  "attribute_frequency": {
    "MeasuredValue": 1158,
    "Occupancy": 640,
    "OnOff": 15,
    "StateValue": 7,
    "LockState": 5,
    "SmokeState": 1,
    "SystemMode": 1,
    "OperationalState": 1,
    "CurrentPositionLiftPercent100ths": 1
  },
  "lock_state_flips": 5,
  "occupancy_events": 640,
  "temperature_patterns": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-26T00:00:00",
    "end_ts": "2026-06-26T01:20:00",
    "event_count": 80,
    "rooms": {
      "living_room": 20,
      "master_bedroom": 19,
      "second_bedroom": 19,
      "kitchen": 16,
      "bathroom": 3,
      "entrance": 3
    },
    "top_devices": [
      "living_room_temp_sensor",
      "master_bedroom_temp_sensor",
      "second_bedroom_temp_sensor",
      "kitchen_temp_sensor",
      "living_room_occupancy",
      "master_bedroom_occupancy"
    ],
    "alarmish_count": 15,
    "preview_lines": [
      "[2026-06-26T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2275",
      "[2026-06-26T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2261",
      "[2026-06-26T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2274",
      "[2026-06-26T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2273",

## Query
以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。

## Triage
{
  "latent_task_profile": "composite-safety",
  "focus_rooms": [
    "kitchen",
    "living_room",
    "entrance"
  ],
  "focus_devices": [
    "kitchen_temp_sensor",
    "living_room_temp_sensor",
    "master_bedroom_temp_sensor",
    "second_bedroom_temp_sensor",
    "entrance_occupancy",
    "living_room_occupancy"
  ],
  "focus_chunk_ids": [
    "C02",
    "C03",
    "C04",
    "C05",
    "C06",
    "C17"
  ],
  "suspected_patterns": [
    "Anomalous temperature scaling: Sensor values range from ~2200 to ~2560, likely representing scaled Celsius (e.g., x10 or raw integer encoding), indicating a potential heating event rather than ambient cooling.",
    "Occupancy-Heat Correlation: High occupancy in living room and master bedroom coincides with peak temperature readings (Chunks C05-C10).",
    "Nighttime Activity Anomaly: Occupancy sensors trigger repeatedly after 21:00 (Chunks C20-C22) when typical residential activity subsides.",
    "Device State Transition: Living room AC switched OFF at 22:21 while occupancy remains high, suggesting manual override or system failure."
  ],
  "why_these_chunks": [
    "C02-C04: Show the initial rapid rise in temperature values across all rooms, establishing the baseline of the anomaly.",
    "C05-C06: Capture the peak temperature period and correlate it with specific occupancy events in the bedrooms.",
    "C17: Contains critical device state changes (AC turning off) amidst continued high temperatures and occupancy, indicating a potential safety hazard escalation.",
    "C20-C22: Highlight unusual late-night human presence which could imply unauthorized entry or abnormal household behavior."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The house is empty with sensors reporting baseline ambient temperatures (scaled by x10) and no human activity.",
      "evidence": ["Occupancy sensors reported '0' for all rooms between 03:00 and 06:35.", "Temperature values in the 2300-2400 range are consistent with a stable indoor environment if scaled Celsius (~23-24°C)."],
      "weaknesses": ["Fails to account for the sudden spike in occupancy at 06:35 in the master bedroom.", "Cannot explain the rapid temperature increase observed after 06:40 coinciding with cooking events."]
    }
  ],
  "anomaly_hypotheses": [
    {
      "id": "A1",
      "description": "Unauthorized intrusion followed by a fire or extreme he


凌晨2:30-2:40短时间内多房间连续活动 活动轨迹：客厅→厨房→玄关（像在搜索什么） 卧室全程无活动（住户在睡觉），这些活动不是住户产生的 注意区分：如果卧室先有活动再到其他房间，则可能是住户起夜

All temperature sensors are reporting physically impossible values (2261-2499) due to a critical calibration failure or unit scaling error, rendering thermal safety data invalid.

Explanation: The reported temperature readings range from approximately 2261 to 2500, which is physically impossible for ambient air temperature in standard units (Celsius max ~35, Kelvin max ~373).

Explanation: Data analysis reveals a linear drift pattern over time (e.g., living room sensor increasing from 2261 to 2498 over 6 hours), characteristic of a raw counter overflow, ADC fault, or missing decimal point scaling rather than actual thermal changes.

Explanation: Despite occupancy events and lighting activation (which should cause minor thermal fluctuations), the sensor values continue their erratic upward trend without stabilizing at realistic levels, confirming a hardware or firmware logic failure.

Timestamped logs show consistent integer values >2200 across all sensors (living_room, master_bedroom, second_bedroom, kitchen) throughout the monitoring period.

The values exhibit a smooth, linear increase (drift) inconsistent with real-world thermal physics, suggesting a software conversion bug or sensor stuck state.

Immediately flag the entire temperature monitoring system as 'UNRELIABLE' and disable any automation rules dependent on these values.

Contact hardware vendor or IT support to verify firmware version and check for recent updates that may have introduced a scaling regression.

Perform physical verification using independent manual thermometers to confirm environmental conditions before re-enabling automated alerts.

Values remain relatively stable and correlated across different rooms over time, indicating a systematic sensor or software issue rather than chaotic noise.

Occupancy events (lights turning on in living room/kitchen/bathroom) coincide with slight local temperature spikes, suggesting real thermal generation if the unit were correct.

A safety-critical system should not output raw integers that look like '2500' degrees without immediate normalization logic. If downstream alarms use these raw values, they would trigger false positives indefinitely.

No log entries explicitly mention a 'unit conversion' event or a reboot that might have triggered this default behavior.

Critical Sensor Failure / Calibration Loss: The temperature sensors have lost their calibration or unit configuration, reporting absolute millikelvin or arbitrary integer counts instead of Celsius. This renders all thermal safety data invalid.

Readings consistently exceed 2400-2500, which is physically impossible for ambient air temperature in Kelvin (absolute zero is 0K, boiling point is ~373K) or Celsius.

The magnitude of values (2500) suggests a loss of decimal scaling or an overflow from a different measurement type (e.g., mV converted incorrectly).

Despite high occupancy and light usage (C02-C04), temperatures do not stabilize at expected levels (e.g., >20°C); instead, they drift upwards linearly, indicating the sensor is no longer measuring heat but perhaps counting cycles or drifting voltage without offset correction.

Could be mitigated if the smart home hub has a fallback heuristic based on occupancy history, though none is visible in the logs.

If the sensors are actually measuring something else (like a proprietary heat index algorithm), the logic is undocumented and risky.

Environmental Hazard: The house is genuinely overheating to lethal levels (>2400°C), implying a catastrophic fire or industrial accident has occurred inside the walls, undetected by humans until structural failure.

Raw values reach 2500+ (if interpreted literally).

Continuous upward trend even during low-occupancy periods (00:00 - 06:00) suggests an external heat source rather than internal human activity.

Highly implausible given the stability of the reading pattern; fires cause erratic spikes, not smooth linear drifts.

If it were a fire, smoke detectors or other emergency systems would likely be triggered or logged, which are absent.

The linear progression of values (e.g., Living Room going from 2261 to 2491 over 6 hours) perfectly matches the mathematical slope of a counter or a faulty ADC reading, whereas a real thermal event would show exponential decay/growth or step changes.

The correlation between 'OnOff' events (lights) and minor value shifts suggests the device is reacting to environmental changes, proving it is 'on', but the scale is wrong.

Absence of any 'SystemMode' change or 'Alarm' state flip in the structured signals despite the temperature crossing any reasonable threshold.

The specific protocol used (MQTT payload schema) to determine if the value is raw integer, float, or encoded.

Historical baseline: What were the last known good values before June 22?

Firmware version and recent update logs to rule out a regression bug introduced recently.

Status of Smoke/Carbon Monoxide detectors, as thermal anomalies often correlate with combustion hazards.

Verify Smoke/CO detector status logs (explicitly requested in missing information).

Check historical baseline data prior to June 22 to confirm if values were previously normal.

Retrieve Firmware version and update changelogs to investigate scaling regression bugs.

Cross-reference 'alarmish_count' spikes with specific appliance power logs to rule out false positives from cooking activities.

The investigation has correctly identified the primary anomaly: temperature sensor calibration/scaling issues leading to impossible readings (~2500).

However, the current evidence is insufficient to fully assess 'safety status' as requested by the query. The analysis focuses heavily on thermal sensors but ignores critical safety systems mentioned in the triage (Smoke/CO detectors).

We must verify if the system failed silently regarding other hazards or if the thermal anomaly is the only issue.

Historical context (baseline) and firmware history are explicitly missing and necessary to determine if this is a new failure mode or a long-standing bug.

No additional chunk IDs need to be retrieved since all 21 chunks (C00-C20) have already been processed by the investigator.

## Query
以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。

## 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": 336,
    "second_bedroom": 336,
    "kitchen": 299,
    "bathroom": 58,
    "entrance": 232
  },
  "attribute_frequency": {
    "MeasuredValue": 1154,
    "Occupancy": 480,
    "OnOff": 16,
    "StateValue": 5,
    "LockState": 4,
    "SystemMode": 1,
    "OperationalState": 1
  },
  "lock_state_flips": 4,
  "occupancy_events": 480,
  "temperature_patterns": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-22T00:00:00",
    "end_ts": "2026-06-22T01:20:00",
    "event_count": 80,
    "rooms": {
      "living_room": 20,
      "master_bedroom": 19,
      "second_bedroom": 19,
      "kitchen": 16,
      "bathroom": 3,
      "entrance": 3
    },
    "top_devices": [
      "living_room_temp_sensor",
      "master_bedroom_temp_sensor",
      "second_bedroom_temp_sensor",
      "kitchen_temp_sensor",
      "living_room_occupancy",
      "master_bedroom_occupancy"
    ],
    "alarmish_count": 15,
    "preview_lines": [
      "[2026-06-22T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2261",
      "[2026-06-22T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2264",
      "[2026-06-22T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2280",
      "[2026-06-22T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2270",
      "[2026-06-22T00:00:00] living_room_occupancy | OccupancySensing.

## Query
以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。

## Triage
{
  "latent_task_profile": "composite-safety",
  "focus_rooms": ["living_room", "kitchen", "master_bedroom", "second_bedroom"],
  "focus_devices": ["living_room_temp_sensor", "master_bedroom_temp_sensor", "second_bedroom_temp_sensor", "kitchen_temp_sensor", "entrance_occupancy", "living_room_occupancy", "bathroom_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"],
  "suspected_patterns": [
    "Anomalous temperature readings (e.g., 2261, 2578) likely representing raw sensor values or scaled data rather than Celsius/Kelvin, indicating a need for unit calibration or firmware review.",
    "Persistent occupancy in living areas and entrance throughout the day suggests active monitoring of routine movement patterns.",
    "Sudden spike in 'alarmish_count' during evening hours (C15-C18) coinciding with kitchen activity and high occupancy requires correlation with appliance logs.",
    "Discrepancy between high room event counts and specific device top-lists implies potential sensor polling loops or network latency issues."
  ],
  "why_these_chunks": [
    "All chunks are required to establish the full temporal baseline for temperature drift analysis across the 24-hour cycle.",
    "Early chunks (C00-C02) show initial system states and the first occurrences of anomalous temperature values.",
    "Mid-to-late chunks (C15-C18) exhibit the highest 'alarmish_count', suggesting potential safety triggers or sensor faults that must be correlated with occupancy events.",
    "The entire sequence is necessary to verify if the 'lock_state_flips' mentioned in deterministic signals correlate with entrance occupancy changes."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The system is experiencing a global firmware scaling error where temperature readings are multiplied by approximately 10 (e.g., 23°C stored as 2300). The values fluctuate realistically within a home environment range (-5 to +35 scaled) despite the raw numbers appearing extreme.",
      "evidence": ["All temperature sensors show consistent, plausible gradients (e.g., kitchen rising faster than bedrooms due to activity/lighting).", "Values remain relatively stable and correlated across different rooms over time, indicating a systematic sensor or software issue rather


1分钟内多次灯光开关 可能原因：智能家居系统被入侵/远程控制；设备自动化规则冲突；或电路问题 也可能是恐慌信号（住户通过反复开关灯试图引起注意）

通知住户检查是否有人误操作或系统异常

All temperature sensors are reporting physically impossible values (2300-2500+) indicative of a global calibration failure or data corruption rather than an actual fire, as the house structure would fail long before reaching such temperatures.

Explanation: Temperature readings across all rooms consistently exceed 2000°C (e.g., 2400-2559), which is physically impossible for indoor air; even steel melts around 1370°C, meaning the house would be destroyed if these were real measurements.

Explanation: Despite the 'extreme' heat readings, occupancy logs show residents moving normally between rooms (master_bedroom_occupancy = 1) and interacting with devices (lights on/off), which would not occur in a lethal environment.

Explanation: The kitchen cooking surface was turned ON at 06:59:36, and while this triggered the start of the anomalous readings, the subsequent rise to >2500 without any corresponding smoke detector triggers or sensor failures (until one specific kitchen sensor hit 'None') suggests the entire stream is corrupted or misinterpreted raw counts (likely Kelvin vs Celsius confusion or integer overflow).

Explanation: No other safety systems (smoke/CO) have been triggered, and the system has not entered a critical shutdown state until very late in the timeline, indicating the central logic does not recognize these numbers as fire events.

kitchen_temp_sensor reading dropped to 'None' at 07:00:06 while other sensors continued reporting high integers, suggesting localized component saturation or buffer overflow rather than uniform environmental destruction.

Occupancy flags remained active (1) in the master bedroom during periods where temperatures peaked above 2500, proving the environment was habitable.

Front door lock operations and light toggles occurred normally throughout the event, confirming human activity consistent with a non-emergency state.

Immediately reset all temperature sensors and check firmware for scaling errors (Kelvin vs. Celsius) or calibration drift.

Verify physical temperature using an independent handheld thermometer to confirm no actual fire exists.

Inspect the kitchen area visually for any signs of overheating or damage caused by the faulty sensor triggering unnecessary alarms or user panic.

Review network logs to rule out potential data injection attacks if the malfunction persists after hardware reset.

Occupancy events show logical human patterns: lights turn on/off, doors lock/unlock in sequence (C05-C06), and occupancy flags flip realistically (0 to 1).

No alarm triggers occurred during the period despite the 'alarmish_count' spike mentioned in the triage output, suggesting the logic layer filtered out the data corruption.

If the values were truly Kelvin, 2400K (~2127°C) is physically impossible for indoor air; the sensors would melt long before reporting this. Therefore, the unit is likely Celsius, making the absolute values physically impossible unless there is an active fire consuming the house structure itself, which contradicts the lack of visible smoke/damage logs.

Active Class A/B Fire Event: An uncontrolled fire is burning within the residence, causing extreme heat that exceeds standard sensor ranges, resulting in saturation or overflow values reported as high integers. The 'None' readings indicate sensor burnout.

Temperature readings escalate from ~2340 to >2500 over a 6-hour period. If these are raw counts proportional to temperature, they indicate rising thermal energy.

At 07:00:06 and 07:03:00, `kitchen_temp_sensor` returns `None`, indicating total sensor failure due to extreme heat or power loss.

Kitchen cooking surface was turned ON at 06:59:36. While late-night cooking is risky, the subsequent temperature escalation and sensor failure point beyond simple overheating.

Multiple `entrance_occupancy` spikes (07:28, 07:33, etc.) combined with door locking suggests residents are attempting to secure the perimeter or evacuate, though the timing relative to peak temps is ambiguous.

The timeline shows occupancy occurring *after* temperatures hit critical levels. Residents entering a room with 2000°C+ air would result in immediate detection via motion sensors failing due to heat haze or direct exposure, yet occupancy is logged clearly until the very end.

No other environmental signals (smoke detectors, CO sensors, window contact breaches indicating forced entry) are explicitly linked to the fire event in the provided chunks, only temperature and occupancy.

Data Corruption / Injection Attack: The temperature stream has been artificially manipulated or corrupted by a network intrusion, creating a false narrative of a fire to trigger panic or bypass security protocols.

The correlation between specific timestamps and the 'high' numbers is too perfect across disparate sensors without corresponding local heat source logs.

The `temperature_patterns` array in structured signals is empty, implying the system flagged the data series as invalid or anomalous internally.

Sensor failure (`None`) occurs exactly when the numeric value would be highest, consistent with a buffer overflow caused by injected data.

In a real attack, one might expect randomized noise or inconsistent patterns across sensors. Here, all sensors rise in unison, which mimics a physical phenomenon more closely than random injection.

The presence of legitimate device events (locks, lights, cooktops) interspersed with the bad data suggests the attacker has partial access, not total control, making a complete fabrication difficult.

The transition of `kitchen_temp_sensor` to `None` at 07:00:06 while other sensors still report high integer values suggests either a localized component failure (burnout) or a deliberate cutoff in a corrupted stream.

The specific timestamp `2026-06-23T06:59:36` for `kitchen_cook_surface` turning ON coincides with the start of the steep temperature ascent, creating a plausible causal link for a kitchen fire scenario if the values represent valid heat accumulation.

The complete absence of any 'SmokeDetected' or 'FireAlarmTriggered' events in the logs, despite temperatures exceeding realistic limits, implies the safety logic is either blind to the temperature anomaly or the anomaly is being misinterpreted as non-critical.

Actual temperature units (Celsius vs. Fahrenheit vs. Raw Counts) defined in the schema.

Logs from Smoke/CO detectors and Water Leak sensors to confirm or deny fire/water damage.

Camera footage or audio logs to verify if occupants are fleeing, hiding, or interacting normally with the environment.

Historical baseline temperature data to determine if the current 'baseline' of 2300 is already abnormal for this specific hardware setup.

Verify if high temperature readings correlate with specific fire events in C07-C10.

Check for smoke/CO alarm triggers or sensor failures in subsequent chunks.

Confirm occupancy patterns to determine if residents are evacuating or trapped.

The investigation has drifted slightly into speculative hypotheses (cyber attack vs. physical fire) without sufficient empirical data from the mid-to-late timeline (C07-C22).

Critical gaps exist: We need to see what happens after the 'None' reading at C06. Is there a total system shutdown? Do smoke alarms trigger later?

The current evidence relies heavily on extrapolating from the initial spike; we need concrete logs of evacuation attempts, fire suppression activation, or continued sensor degradation in the next set of chunks to validate Anomaly A1.

## Query
以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。

## 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": 407,
    "master_bedroom": 517,
    "second_bedroom": 336,
    "kitchen": 303,
    "bathroom": 48,
    "entrance": 229
  },
  "attribute_frequency": {
    "MeasuredValue": 1156,
    "Occupancy": 642,
    "OnOff": 22,
    "StateValue": 7,
    "LockState": 5,
    "SystemMode": 1,
    "OperationalState": 1,
    "CurrentPositionLiftPercent100ths": 1
  },
  "lock_state_flips": 5,
  "occupancy_events": 642,
  "temperature_patterns": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-23T00:00:00",
    "end_ts": "2026-06-23T01:20:00",
    "event_count": 80,
    "rooms": {
      "living_room": 20,
      "master_bedroom": 19,
      "second_bedroom": 19,
      "kitchen": 16,
      "bathroom": 3,
      "entrance": 3
    },
    "top_devices": [
      "living_room_temp_sensor",
      "master_bedroom_temp_sensor",
      "second_bedroom_temp_sensor",
      "kitchen_temp_sensor",
      "living_room_occupancy",
      "master_bedroom_occupancy"
    ],
    "alarmish_count": 15,
    "preview_lines": [
      "[2026-06-23T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2273",
      "[2026-06-23T00:00:00] master_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2281",
      "[2026-06-23T00:00:00] second_bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2277",
      "[2026-06-23T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2262",
      "[2026-06-23T00:00:00

## Query
以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。

## Triage
{
  "latent_task_profile": "composite-safety",
  "focus_rooms": ["kitchen", "living_room", "master_bedroom"],
  "focus_devices": ["kitchen_temp_sensor", "living_room_temp_sensor", "master_bedroom_temp_sensor", "kitchen_cook_surface", "entrance_occupancy", "master_bedroom_occupancy"],
  "focus_chunk_ids": ["C02", "C03", "C04", "C05", "C06", "C17", "C18"],
  "suspected_patterns": [
    "Temperature values (e.g., 2273, 2559) are in Kelvin scale (~20°C - 228°C), not Celsius. If interpreted as °C, this indicates a critical sensor failure or data corruption.",
    "High frequency of occupancy events ('flip-flop' pattern) at the entrance and living room suggests potential sensor instability or repeated short visits by individuals/animals.",
    "Late-night activity detected in the master bedroom while other sensors show low activity."
  ],
  "why_these_chunks": [
    "C02-C04: Show the steepest rise in temperature readings across all rooms, which is suspicious if the unit is Celsius; otherwise, it's normal diurnal heating but requires validation against expected ranges.",
    "C05-C06: Critical period where high temperatures coincide with the first confirmed human occupancy events in the master bedroom after a long absence.",
    "C17-C18: The only chunks showing active cooking surface usage ('OnOff = True') late at night (18:46, 19:30), which combined with the elevated temperature readings creates a potential fire safety risk scenario.",
    "Throughout C00-C01: Baseline establishment showing 'alarmish_count' spikes without corresponding physical event logs, hinting at system noise or calibration drift that needs correlation with the later active events."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The entire house is experiencing a severe sensor calibration failure or firmware bug where all temperature readings are erroneously multiplied by a factor of ~10 (reporting Kelvin values like 2400K instead of Celsius). The system has no actual fire hazard.",
      "evidence": ["All temperature values across all rooms consistently fall between 2340 and 2547, which corresponds to physical temperatures of ~2000°C to ~2270°C if interpreted as Celsius, but ~20°C to ~2300K (physical ~1700°C) if interpreted as Kelvin. However, the *relative* stability and gradual drift suggest a scaling error rather than chaotic noise.", "Occupancy events show logical human


工作日上午学校时段
家长已出门（LockOperation 记录）
仅儿童房有活动信号，其他房间无人
活动模式像小孩（仅在一个房间）

通知家长确认孩子是否生病在家/逃学

The home monitoring system is reporting physically impossible temperature readings (>2000°C) across all sensors due to a critical firmware or data corruption error, posing no immediate environmental fire risk but causing system integrity failure.

Explanation: All temperature sensors (kitchen, living_room, bedrooms) report values consistently between ~2260 and ~2550, which are physically impossible for any standard indoor residential environment (normal range: -10°C to 50°C).

Explanation: The anomaly is global and simultaneous, affecting every sensor in the house from the very first timestamp (2026-06-21T00:00:00), indicating a central processing unit, broadcast command, or calibration issue rather than localized heat sources like a fire.

Explanation: Occupancy sensors confirm the house has been empty (all zeros) throughout the entire incident period, ruling out human activity (cooking, heating) as the cause of the extreme readings.

Explanation: No other safety systems (smoke alarms, locks, water leaks) show correlated anomalies or state changes, isolating the fault strictly to the temperature measurement logic.

MeasuredValues range from 2262 to 2551 over an 8.5-hour period, far exceeding any known physical limit for indoor air temperature.

Consistency of Invalidity: Every single temperature reading across 8 different rooms contains the same impossible characteristic simultaneously.

Contradictory State: The house is reported as fully unoccupied during the anomalous period, eliminating human activity as the source.

Immediately reboot the central home automation hub or gateway to reset sensor communication protocols.

Check device logs for firmware errors, buffer overflows, or recent configuration changes that may have triggered the data corruption.

Perform a manual physical inspection of one sensor to verify actual ambient temperature if possible, or replace suspected faulty hardware after reboot.

Occupancy sensors consistently report 0 (empty house) while temperature sensors generate this chaotic stream, ruling out occupancy-based heating as a cause.

No lock_state_flips occurred, suggesting doors/windows are sealed, yet 'temperature' logic fails completely.

We cannot definitively prove it isn't an external industrial furnace operating in the basement if the house layout is non-standard, though the values are too high even for that.

Potential Data Transmission Protocol Error (Overflow/Corruption).

The timestamps are precise to the second, but the payload values (2278, 2294, etc.) show no correlation with time or known environmental cycles.

The specific chunk IDs C00-C04 cover the entire anomaly duration, showing a sustained failure mode rather than a transient glitch.

Could be misinterpreted as a real hazard by downstream safety systems if not filtered correctly.

The absolute value magnitude: Indoor temperatures > 2200 are physically impossible under any standard domestic scenario, immediately classifying this as a hardware/software fault rather than an environmental event.

Consistency of Invalidity: Every single temperature reading across 8 different rooms contains the same impossible characteristic, pointing to a central processing unit issue or broadcast command failure rather than individual sensor failures.

Contradictory State: The house is reported as fully unoccupied (all Occupancy = 0) during the entire anomalous period, eliminating human activity (cooking, heating) as the source of the extreme readings.

Historical baseline data: What were the normal readings before 2026-06-21T00:00:00?

Sensor hardware logs: Did the sensors reboot, reset, or enter an error state at the start of the log?

Network topology: Is there a centralized controller sending a 'setpoint' or 'override' command that could have triggered this?

Verify sensor reboot logs or error states at the start of the anomaly.

Check for centralized controller 'override' commands in historical data prior to C00.

Review network topology to rule out broadcast command failures.

The analysis correctly identifies the temperature readings (>2000) as physically impossible and indicative of a system integrity issue rather than an environmental hazard.

However, the current evidence only covers chunks C00-C07 (the initial onset). To fully diagnose the root cause, we need earlier context (C08-C10) to establish a baseline and check for preceding commands or hardware resets that triggered this global failure mode.

The hypothesis regarding a 'firmware bug' vs. 'data corruption' cannot be distinguished without seeing the state immediately before the anomaly began.

## Query
以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。

## 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": 336,
    "master_bedroom": 336,
    "kids_room": 338,
    "kitchen": 288,
    "dining_room": 48,
    "second_bedroom": 48,
    "master_bathroom": 48,
    "entrance": 50
  },
  "attribute_frequency": {
    "MeasuredValue": 1152,
    "Occupancy": 337,
    "OnOff": 1
  },
  "lock_state_flips": 0,
  "occupancy_events": 337,
  "temperature_patterns": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-21T00:00:00",
    "end_ts": "2026-06-21T01:10:00",
    "event_count": 80,
    "rooms": {
      "living_room": 18,
      "master_bedroom": 18,
      "kids_room": 18,
      "kitchen": 14,
      "dining_room": 3,
      "second_bedroom": 3,
      "master_bathroom": 3,
      "entrance": 3
    },
    "top_devices": [
      "living_room_temp_sensor",
      "master_bedroom_temp_sensor",
      "kids_room_temp_sensor",
      "kitchen_temp_sensor",
      "living_room_occupancy",
      "dining_room_occupancy"
    ],
    "alarmish_count": 21,
    "preview_lines": [
      "[2026-06-21T00:00:00] living_room_temp_sensor | TemperatureMeasurement.

## Query
以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。

## Triage
{
  "latent_task_profile": "composite-safety",
  "focus_rooms": ["kitchen", "living_room"],
  "focus_devices": ["temperature_sensor", "smoke_co_alarm", "water_leak_detector", "cook_surface"],
  "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04", "C05", "C06", "C07"],
  "suspected_patterns": [
    "Abnormal temperature readings (values > 2000) across all rooms indicating sensor calibration failure or data corruption.",
    "High frequency of 'alarmish' events correlating with temperature spikes, suggesting a potential false alarm cascade due to the faulty sensor data."
  ],
  "why_these_chunks": [
    "Chunks C00-C07 contain the initial and most severe temperature anomalies (ranging from ~2278 to ~2553), which are physically impossible for standard indoor environments and indicate a critical system health issue rather than an environmental hazard. These chunks require inspection to determine if this is a firmware bug, hardware failure, or data transmission error before any safety protocols are triggered."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "System-wide sensor calibration drift or firmware bug causing uniform offset.",
      "evidence": ["All temperature sensors report values between 2260-2495, which are physically impossible for indoor environments (likely intended to be ~20-30).", "The magnitude of the error is consistent across all room types (living_room, kitchen, bedrooms) suggesting a global configuration error rather than localized heat sources."],
      "weaknesses": ["If this were a simple offset, one would expect some variation based on actual room conditions, but the values remain stubbornly high and fluctuate erratically without a clear physical cause like a fire."]
    }
  ],
  "anomaly_hypotheses": [
    {
      "id": "A1",
      "description": "Critical Data Corruption / Sensor Firmware Failure.",
      "threat_type": "System Integrity / False Positive Cascade Risk",
      "evidence": ["MeasuredValues range from 2262 to 2495 over a 6-hour period. Standard indoor temperatures rarely exceed 35°C (89°F), making these readings (>2200 units) physically impossible.", "The 'attribute_frequency' shows 'MeasuredValue': 1152 events, indicating the system is actively generating massive amounts of invalid data points rather than just failing once.", "Occupancy sensors consistently report 0 (empty house) while temperature sensor


灶具开着 + 厨房无人 + 老人在其他房间
跟 FG-01 类似但在老人场景下更危险（认知衰退风险更高）

The kitchen temperature sensor is critically malfunctioning by returning 'None' values immediately after the cook surface is activated or deactivated, creating a dangerous blind spot for fire monitoring.

Explanation: Analysis of chunk C03 reveals a cooking event starting at 06:10:39 where the `kitchen_cook_surface` turns ON, but the `kitchen_temp_sensor` immediately returns 'None' at 06:11:09, preventing heat verification during active use.

Explanation: A repeat failure occurs in chunk C04 at 06:33:00 when the cook surface turns OFF, followed instantly by a 'None' reading from the temperature sensor at 06:34:00, confirming a systematic hardware or communication fault rather than random noise.

Explanation: Similar anomalies are observed in chunks C09 and C16, where every instance of appliance state change (ON/OFF) triggers immediate data loss from the thermal sensor, rendering the kitchen effectively unmonitored for overheating or fire hazards.

[2026-06-12T06:10:39] kitchen_cook_surface | OnOff.OnOff = True followed by [2026-06-12T06:11:09] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = None

[2026-06-12T06:33:00] kitchen_cook_surface | OnOff.OnOff = False followed by [2026-06-12T06:34:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = None

Immediately inspect and replace the kitchen temperature sensor to restore continuous thermal monitoring.

Conduct a manual safety check of the kitchen area to ensure no lingering heat sources or smoke detectors have been compromised due to the lack of automated alerts.

Temperature values are unphysically high (22-25°C range represented as 2200-2500), suggesting a sensor calibration offset rather than actual thermal readings.

Kitchen temperature sensor returns 'None' immediately after cook surface activation, indicating a potential hardware fault or communication drop.

Critical failure of the kitchen temperature monitoring system creates a blind spot for fire safety, allowing the cook surface to operate without valid thermal feedback.

At 06:10:39, kitchen_cook_surface turns ON.

Immediately at 06:11:09, kitchen_temp_sensor reports 'None'.

This pattern repeats at 11:07:30 (Cook ON) -> 11:08:00 (Temp None) and 11:26:00 (Cook OFF) -> 11:27:00 (Temp None).

The sensor fails specifically during active appliance states, not just when idle.

No evidence of smoke detection triggering an alarm yet.

Severe HVAC failure leading to dangerous overheating, indicated by sustained and rising indoor temperatures that exceed safe human comfort levels significantly.

Living room temperature rises steadily from ~22°C (2200) at 00:00 to ~25°C (2500) by 11:00 and remains elevated.

Peak reading at 11:10 shows 2552 (25.5°C equivalent if scaled correctly, or simply anomalously high raw data), while bedroom is also high at 2439.

Despite occupancy starting at 05:30, there is no corresponding drop in temperature or activation of cooling systems; instead, temperatures continue to climb into the mid-20s range.

Raw temperature units are ambiguous; could be millidegrees Celsius (which would make these normal) unless the system interprets them as standard degrees.

The temporal correlation between `kitchen_cook_surface.OnOff = True` and `kitchen_temp_sensor.MeasuredValue = None` occurring repeatedly across different time blocks (C03, C09, C16) strongly indicates a systematic sensor failure rather than random noise.

The continuous upward trend in temperature readings across all rooms (C00 to C03) despite the start of occupancy suggests a lack of environmental control (AC/Heater malfunction).

Actual unit of measurement for the TemperatureMeasurement values (e.g., are they °C, m°C, or relative index?).

Status of the HVAC system (On/Off) and thermostat setpoints.

Presence of any smoke detector alerts or carbon monoxide sensor readings.

Verify HVAC system status (On/Off) and thermostat setpoints to confirm A2 hypothesis.

Check for smoke detector alerts or carbon monoxide sensor readings as requested in 'missing_information'.

Clarify the unit of measurement for TemperatureMeasurement values (°C vs m°C) to validate the thermal anomaly severity.

The analysis is on-topic but relies heavily on hypotheses regarding sensor calibration errors (N1/A2) without confirming the data units. Chunk C02/C04 are needed to see if temperature trends persist or reset early in the timeline before the suspected anomalies.

Critical safety checks for smoke/CO sensors and HVAC status are missing from the current evidence scope. Chunks C17/C18 likely contain late-night event logs which are necessary to verify the 'activity spike' and potential wandering behavior mentioned in the triage profile.

Without explicit confirmation of the temperature unit scale (millidegrees vs degrees), the 'dangerous overheating' conclusion (A2) remains speculative and potentially misleading.

## Query
以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。

## Layout
Layout: 独居老人 (Elderly Living Alone)
- 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>, 床头灯<onoff_light>
- 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>, 厨房运动传感器<occupancy_sensor>
- living_room: 客厅温度传感器<temperature_sensor>, 客厅灯<dimmable_light>, 客厅烟雾报警器<smoke_co_alarm>, 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": 498,
    "bedroom": 530,
    "kitchen": 536,
    "bathroom": 63,
    "entrance": 231
  },
  "attribute_frequency": {
    "Occupancy": 947,
    "MeasuredValue": 871,
    "OnOff": 23,
    "CurrentPositionLiftPercent100ths": 4,
    "LockState": 4,
    "StateValue": 4,
    "CurrentLevel": 1
  },
  "lock_state_flips": 4,
  "occupancy_events": 947,
  "temperature_patterns": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-12T00:00:00",
    "end_ts": "2026-06-12T01:35:00",
    "event_count": 80,
    "rooms": {
      "living_room": 24,
      "bedroom": 24,
      "kitchen": 24,
      "bathroom": 4,
      "entrance": 4
    },
    "top_devices": [
      "living_room_temp_sensor",
      "bedroom_temp_sensor",
      "kitchen_temp_sensor",
      "living_room_occupancy",
      "bedroom_occupancy",
      "kitchen_occupancy"
    ],
    "alarmish_count": 20,
    "preview_lines": [
      "[2026-06-12T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2280",
      "[2026-06-12T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2170",
      "[2026-06-12T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2277",
      "[2026-06-12T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-12T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-12T00:00:00] kitchen_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-12T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-12T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-12T00:05:00] li

## Query
以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。

## Triage
{
  "latent_task_profile": "composite-safety",
  "focus_rooms": ["kitchen", "bedroom", "living_room"],
  "focus_devices": ["kitchen_cook_surface", "temperature_sensor", "occupancy_sensor", "front_door_contact"],
  "focus_chunk_ids": ["C00", "C01", "C03", "C09", "C16"],
  "suspected_patterns": [
    "Sustained high indoor temperatures (24-25°C range) potentially indicating HVAC failure or overheating in a home with an elderly resident.",
    "Intermittent loss of sensor data ('None' values) on critical kitchen temperature sensors, suggesting hardware malfunction or signal interference during active cooking.",
    "Activity spike at night/late evening (high entrance occupancy and motion) which may indicate wandering behavior, fatigue, or unauthorized access for a lone senior.",
    "Cooking activity detected late in the sequence without immediate subsequent cooling events, raising burn/fire risk."
  ],
  "why_these_chunks": [
    "C00/C01: Establish the baseline of abnormally high ambient temperatures across all rooms early in the timeline.",
    "C03: Shows peak temperature readings (>24°C), confirming the thermal anomaly persists.",
    "C09: Critical safety event where the cook surface turns ON while the temperature sensor returns 'None', creating a blind spot for heat monitoring.",
    "C16: Another instance of sensor data loss ('None') coinciding with the cook surface turning OFF, indicating unreliable telemetry during appliance state changes.",
    "C00-C23: Longitudinal analysis required to track the progression from empty house to active living patterns late at night."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The house is currently occupied by a single resident who has been active throughout the day, engaging in normal cooking activities and moving between rooms. The high ambient temperatures are due to external weather (June) and lack of HVAC cooling.",
      "evidence": [
        "Occupancy sensors show consistent presence in bedroom, kitchen, living room, bathroom, and entrance from 05:30 onwards.",
        "Cook surface was activated at 06:10 and 11:54, typical for meal preparation.",
        "Window covering was closed at 05:32, which is normal behavior to retain heat during cooler morning hours or block sun."
      ],
      "weaknesses": [
        "Temperature values are unphysically high (22-25°C range represented as 2200-2


居家意外（任意位置跌倒/晕倒）

最后一次运动在非卧室房间（如客厅、厨房） 随后异常长时间无任何活动 不在正常午睡时段（比如上午10点或下午4点）

紧急联系老人，如无应答联系紧急联系人或120

The system data indicates a critical sensor scaling error causing unreliable temperature readings and masking potential environmental hazards, as no cooling or alarm systems were triggered despite rising values.

Explanation: Analysis of raw log values (e.g., 2269, 2381) reveals they are statistically improbable for direct Celsius measurements, indicating a firmware bug where values are multiplied by 10 but not scaled down internally.

Explanation: Despite the apparent steady rise in 'temperature' from ~22°C to ~25°C, no HVAC activation, window opening, or safety alarms occurred, suggesting thresholds are misconfigured relative to the erroneous raw data.

Explanation: The combination of unverified thermal data and lack of automated mitigation creates a false sense of security, rendering the current safety monitoring ineffective.

Temperature readings show integer patterns consistent with `value * 10` truncation errors (e.g., 2269 instead of 22.69).

No actuator responses (HVAC, windows) or alarm states were logged during the period of increasing numerical temperature values.

Triage logic explicitly identified 'persistent_high_temperature_anomaly' linked to this scaling issue.

Immediately verify physical room temperatures with independent manual thermometers.

Contact the smart home service provider to correct the sensor scaling factor in the configuration.

Temporarily disable automatic threshold triggers until the sensor data is validated to prevent future false negatives or positives.

Pattern of values ending in single digits (e.g., 2269, 2315) consistent with integer truncation of a scaled float.

Triage output explicitly notes 'sensor scaling error'.

Despite rising temps, no active cooling alarms trigger until potentially too late or never, due to threshold miscalculation based on raw values.

Cannot confirm if the system has internal logic to handle this scale; perhaps thresholds are also scaled internally.

Could be a unit conversion issue (e.g., Kelvin vs Celsius) though 25K is impossible.

Elderly/Sole Occupant Thermal Hazard: An occupant (likely elderly given the slow movement patterns and focus on kitchen/bedroom) is exposed to rising heat levels (>25°C) without effective ventilation, indicated by closed windows and delayed light activation.

Environmental Safety Hazard / Heat Stress

Bedroom occupancy starts at 05:28; lights turn on shortly after (05:28:07).

Window covering remains fully closed (Position=0) throughout the heating period.

Kitchen cook surface turns ON at 05:56:32, adding heat source.

Temperatures continue to climb steadily (23°C -> 25°C) over several hours without significant mitigation.

Front door lock flips frequently (4 times), suggesting entry/exit attempts but no clear departure pattern before the end of the log.

Absence of explicit age data for occupants.

Potential for automated HVAC systems to override manual window settings if connected.

The mathematical improbability of random sensor readings ending in odd/even sequences like '2269', '2315', '2478' which strongly implies a `value * 10` integer cast error.

The temporal correlation between the start of cooking (05:56) and the sustained rise in kitchen temperature despite the absence of reported ventilation changes (window position stays 0).

The Triage Output's explicit identification of 'persistent_high_temperature_anomaly' correlating with the raw data spikes.

The actual configured temperature thresholds for alarms (are they set to raw 2500 or scaled 25.0?).

HVAC system status and automatic response logs (did the AC kick in?).

Demographic profile of the household members to assess vulnerability to heat stress.

Historical baseline data to determine if 25°C is an abnormal spike for this location/time of day.

Verify HVAC status and automatic cooling responses in subsequent chunks to confirm lack of mitigation.

Check for alarm trigger states or notifications in later logs once temperatures exceed typical thresholds (if scaled).

Correlate door lock events with occupancy data to confirm if the occupant is trapped or attempting to leave but failing.

The analysis has correctly identified a potential sensor scaling error (values like 2269 implying ~22.7°C) and a heat hazard scenario involving an elderly occupant in the kitchen.

However, the evidence collection is currently insufficient because it stops at C04. The Investigator Output explicitly lists 'HVAC system status' and 'Historical baseline data' as missing information.

Chunks C05 and C06 are required to observe whether the temperature continues to rise unchecked (confirming the hazard) or if any automated systems eventually intervene, which would alter the risk assessment.

Additionally, checking further chunks is necessary to see if the 'front door lock' activity correlates with an actual exit attempt that might have been blocked or failed.

## Query
以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。

## Layout
Layout: 独居老人 (Elderly Living Alone)
- 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>, 床头灯<onoff_light>
- 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>, 厨房运动传感器<occupancy_sensor>
- living_room: 客厅温度传感器<temperature_sensor>, 客厅灯<dimmable_light>, 客厅烟雾报警器<smoke_co_alarm>, 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": 497,
    "bedroom": 529,
    "kitchen": 536,
    "bathroom": 57,
    "entrance": 232
  },
  "attribute_frequency": {
    "Occupancy": 943,
    "MeasuredValue": 870,
    "OnOff": 21,
    "CurrentPositionLiftPercent100ths": 4,
    "LockState": 4,
    "StateValue": 4,
    "CurrentLevel": 1
  },
  "lock_state_flips": 4,
  "occupancy_events": 943,
  "temperature_patterns": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-11T00:00:00",
    "end_ts": "2026-06-11T01:35:00",
    "event_count": 80,
    "rooms": {
      "living_room": 24,
      "bedroom": 24,
      "kitchen": 24,
      "bathroom": 4,
      "entrance": 4
    },
    "top_devices": [
      "living_room_temp_sensor",
      "bedroom_temp_sensor",
      "kitchen_temp_sensor",
      "living_room_occupancy",
      "bedroom_occupancy",
      "kitchen_occupancy"
    ],
    "alarmish_count": 20,
    "preview_lines": [
      "[2026-06-11T00:00:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2269",
      "[2026-06-11T00:00:00] bedroom_temp_sensor | TemperatureMeasurement.MeasuredValue = 2163",
      "[2026-06-11T00:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2266",
      "[2026-06-11T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-11T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-11T00:00:00] kitchen_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-11T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-11T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0",
      "[2026-06-11T00:05:00] li

## Query
以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。

## Triage
{
  "latent_task_profile": "composite-safety",
  "focus_rooms": ["kitchen", "living_room"],
  "focus_devices": ["temperature_sensor", "occupancy_sensor", "cook_surface"],
  "focus_chunk_ids": ["C00", "C01", "C02", "C03", "C04"],
  "suspected_patterns": [
    "persistent_high_temperature_anomaly",
    "occupancy_without_ventilation_correlation"
  ],
  "why_these_chunks": [
    "C00-C03 show continuous temperature readings starting at ~22.6°C (x10) and rising steadily to >25°C, indicating a sensor scaling error or extreme heating event.",
    "C04 marks the first appearance of 'Occupancy=1' in the kitchen while temperatures peak above 25°C, creating a high-risk scenario for an elderly person cooking without adequate cooling or ventilation.",
    "The sustained high 'alarmish_count' across these chunks correlates with the thermal anomaly, suggesting system flags related to environmental safety."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "The temperature sensors are functioning correctly, reporting ambient room temperatures in the 22-25°C range, while 'Occupancy' events represent discrete user interactions or sensor noise rather than continuous presence.",
      "evidence": ["All room temperatures fluctuate between ~2100 and ~2500 units across all chunks.", "Occupancy events for specific rooms (e.g., kitchen, bedroom) appear intermittently after initial periods of zero.", "No explicit error codes or alarm states are present in the raw logs."],
      "weaknesses": ["Temperature values are integers ending in even numbers (e.g., 2269, 2315) which is statistically improbable for analog thermal sensors without rounding logic, suggesting a scaling factor error.", "Continuous high-frequency updates of similar magnitude suggest a stuck loop or misconfiguration rather than natural environmental variance."]
    }
  ],
  "anomaly_hypotheses": [
    {
      "id": "A1",
      "description": "Critical Sensor Scaling Error: Temperature readings are multiplied by a factor of 10 (or similar), displaying values like 2381 instead of ~23.8°C. This indicates a firmware bug or configuration drift that renders thermal data unreliable for safety monitoring.",
      "threat_type": "Data Integrity Failure / False Negative Risk",
      "evidence": ["Initial reading at C00: 2269 (likely 22.69°C).", "Progressive rise to C04: 2520 (likely 25.20°C).", "Pattern of values en


玄关运动 + 门锁解锁失败

密码错误（小孩可能记不准密码）

跟 INS-02 的区别：这里不是暴力破解，只有1-2次尝试，且家中有其他房间的活动（说明有人在家）

The entire home environment is reporting physically impossible temperature readings (2300-2540 scale) that indicate a critical sensor calibration failure or system overflow, rather than a real environmental hazard.

Explanation: Analysis of temperature data from C01 to C08 shows consistent values ranging between 2298 and 2542 across all rooms over an 8-hour period. If interpreted as Celsius or Fahrenheit, these represent temperatures far exceeding the melting point of metals and the boiling point of lead, which would result in immediate house destruction and loss of life, contradicting the presence of occupants.

Explanation: The uniformity of this anomaly across multiple sensors (kitchen, living room, bedrooms) and the steady nature of the reading (slowly drifting upwards by ~1 unit per hour) rules out localized equipment failures like a single broken appliance causing heat buildup.

Explanation: Given the physical impossibility of indoor temperatures reaching >2500°C/F, the only logical conclusion is that the sensor firmware is outputting raw integer values in an incorrect unit (e.g., millikelvin where 2500mK is near absolute zero, or a floating-point overflow representing a normal temperature like 25.00), rendering the safety status based on these numbers invalid.

Explanation: While the front door lock jamming (C06) was noted in the triage, the subsequent successful manual locking and auto-lock confirms the primary risk is the false positive regarding thermal conditions due to sensor malfunction.

Temperature readings consistently hover between 2300 and 2540 for 8 hours despite occupancy and lighting changes.

No corresponding physical damage events (fire, structural collapse) occurred during the reported high-temperature windows.

All room sensors report nearly identical magnitude values simultaneously, indicating a shared software/firmware baseline issue rather than individual sensor drift.

Immediately reset all temperature sensors via the smart home hub to clear potential cache errors.

Verify the actual ambient temperature using independent analog thermometers placed in key locations (kitchen, bedroom).

Check device firmware logs for 'overflow', 'unit mismatch', or 'calibration fail' error codes.

Update the IoT ecosystem firmware to patch known scaling bugs.

Door contact state flipped correctly (False then True) shortly after the error, suggesting the door was manipulated normally.

Multiple consecutive errors (OperationError=1) suggest a persistent mechanical issue rather than a one-time glitch.

Critical HVAC Failure or Sensor Calibration Drift causing potentially lethal heat accumulation indoors.

Massive temperature divergence between time blocks: C06/C24 show values >2200 while C15 shows ~2400. If scale is linear Celsius, this implies indoor temps of 2500°C (impossible) or a catastrophic drift if the scale is offset. Assuming standard deviation logic fails, the variance suggests system collapse.

In C06, temperatures climb steadily from ~2500 to 2533 while kitchen window opens (State=False), exacerbating heat gain.

In C24, despite lights going off and window closing, temperatures remain elevated (~2250) compared to the 'cooler' C15 block (~2450), suggesting no cooling cycle engaged.

If the sensor unit is actually mK (millikelvin), 2500 mK = -272.95°C (near absolute zero), which would also be fatal but physically impossible for a living space unless frozen solid, contradicting 'occupancy'. The most likely scenario is a 'floating point' overflow or unit mismatch where 2500 represents a normal temp, making the *change* the anomaly, not the value itself. However, assuming the prompt implies these are raw readings that should be interpreted as dangerous anomalies per the triage output.

No humidity or CO2 data provided to confirm suffocation risk.

Security Compromise via Lock Jamming and Forced Entry Attempt.

C15 shows two consecutive 'LockOperationError' events at 14:12:05 and 14:12:15 before any successful lock event.

These errors coincide with high occupancy in the entrance/dining room, increasing vulnerability if entry failed.

The sequence suggests a struggle to secure the perimeter while occupants are present inside.

Successful auto-lock follows immediately, mitigating immediate breach risk.

No forced entry alarms (door contact held open) were triggered during the error window.

The stark contrast in temperature readings between Chunk C15 (~2400 range) and Chunks C06/C24 (~2200-2500 range) indicates a systemic shift in environmental control or sensor baseline that defies normal diurnal cycles.

The specific timestamp correlation in C15: Two rapid-fire 'LockOperationError' events occurring while the house is occupied, distinguishing it from random mechanical noise.

The unit of measurement for TemperatureMeasurement.MeasuredValue (e.g., Kelvin, Centi-Kelvin, or arbitrary units) is unknown; interpreting 2500 as 'hot' vs 'cold' depends entirely on this.

HVAC System Mode logs (Heating, Cooling, Auto, Off) to determine if the thermostat is actively failing or simply misreading.

Battery levels for the door lock motor to rule out power-induced operation errors.

HVAC System Mode logs to verify if cooling/heating is active or stuck.

Temperature unit definition (e.g., raw mK vs scaled Celsius) to validate the magnitude of readings.

Door lock battery status and error code specifics to distinguish mechanical jam from power failure.

Occupancy sensor data for all rooms during the temperature anomaly windows to confirm presence/absence correlation.

Historical baseline data for temperature sensors to determine if '2500' is a drift or normal baseline.

Security log details regarding forced entry attempts during the C15 lock errors.

The analysis is highly focused on the triage-selected chunks (C06, C15, C24), which is appropriate for initial anomaly detection. However, declaring the evidence 'sufficient' to judge the *current* safety status is premature.

Without broader context (chunks outside C06/C15/C24), we cannot establish if the high temperatures are a systemic household failure affecting all zones simultaneously or isolated incidents. The lack of surrounding data prevents verifying diurnal patterns or ruling out sensor calibration drift across the whole system.

The hypothesis about the temperature unit scale relies entirely on assumptions not present in the selected chunks. We need chunks containing metadata or historical readings to define the unit of measurement definitively.

To fully assess the security risk of the front door lock errors, we need to see the sequence before and after C15 to ensure no prior tampering or subsequent breach occurred.

Conclusion: The investigation has identified potential risks but lacks the temporal and spatial breadth required to confirm severity or root cause. More chunks are needed to move from 'suspected pattern' to 'confirmed safety status'.

## Query
以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。

## 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": 402,
    "master_bedroom": 516,
    "kids_room": 518,
    "kitchen": 303,
    "dining_room": 221,
    "second_bedroom": 48,
    "master_bathroom": 54,
    "entrance": 230,
    "second_bathroom": 1
  },
  "attribute_frequency": {
    "MeasuredValue": 1156,
    "Occupancy": 1087,
    "OnOff": 26,
    "StateValue": 7,
    "LockState": 5,
    "CurrentPositionLiftPercent100ths": 3,
    "SystemMode": 1,
    "OperationalState": 1
  },
  "lock_state_flips": 5,
  "occupancy_events": 1087,
  "temperature_patterns": []
}

## Chunk Index
[
  {
    "chunk_id": "C00",
    "start_ts": "2026-06-25T00:00:00",
    "end_ts": "2026-06-25T01:10:00",
    "event_count": 80,
    "rooms": {
      "living_room": 18,
      "master_bedroom": 18,
      "kids_room": 18,
      "kitchen": 14,
      "dining_room": 3,
      "second_bedroom": 3,
      "master_bathroom": 3,
      "entrance": 3
    },
    "top_devices": [
      "living_room_temp_sensor",
      "master_bedroom_temp_sensor",
      "kids_room_temp_sensor",
      "kitchen_temp_sensor",
      "living_room_occupancy",

## Query
以下是家庭设备的综合状态报告。请综合分析所有信息，判断家庭当前的安全状况，指出任何潜在风险。

## Triage
{
  "latent_task_profile": "composite-safety",
  "focus_rooms": ["kitchen", "entrance", "kids_room"],
  "focus_devices": ["kitchen_temp_sensor", "kitchen_window_contact", "front_door_lock", "kids_room_window_covering"],
  "focus_chunk_ids": ["C06", "C15", "C24"],
  "suspected_patterns": [
    "Sustained high temperature readings across all rooms (2300-2500+ scale) indicating potential HVAC failure or sensor calibration drift.",
    "Kitchen window contact state change to False while occupancy is present, suggesting an open window in a heated area.",
    "Front door lock operation errors followed by successful manual locking, indicating mechanical jamming or user struggle.",
    "Kids room window covering fully closed at night despite interior heat, potentially trapping hot air or preventing ventilation."
  ],
  "why_these_chunks": [
    "C06: Shows the kitchen window opening event during active hours and temperatures climbing above 2500.",
    "C15: Contains critical 'LockOperationError' events for the front door, signaling a security/functional hazard.",
    "C24: Captures the kids room window closing to 100% at night coinciding with peak indoor temperatures, creating a potential heat trap."
  ]
}

## Investigator
{
  "normal_hypotheses": [
    {
      "id": "N1",
      "description": "Sensors are reporting values in a valid but non-standard scale (likely millikelvin or a specific proprietary unit where 2500+ corresponds to ~23°C), indicating stable thermal conditions.",
      "evidence": ["Temperature readings remain consistent within narrow ranges across different rooms (e.g., Kitchen 2460-2533, Kids 2248-2527) without erratic spikes or drops typical of sensor failure.", "Occupancy patterns align with daily routines: high activity in mornings/afternoons, lights off at night (C24)."],
      "weaknesses": ["The absolute magnitude of the numbers (>2000) is counter-intuitive for standard Celsius/Fahrenheit sensors used in consumer devices, requiring external calibration data to verify."],
      "threat_type": null
    },
    {
      "id": "N2",
      "description": "Front door lock errors were caused by user distraction or mechanical friction unrelated to security compromise.",
      "evidence": ["Error occurred during an active occupancy period (C15) followed immediately by successful manual locking (LockState=1).", "Door contact state flipped correctly (False then True) shortly after the e