The rapid lock/unlock cycle was a benign false positive triggered by the door contact sensor bouncing immediately after manual closure, not an intrusion attempt.

Explanation: Occupancy sensors correctly show '0' from midnight to early morning due to the house being empty (verified by lack of activity logs until ~06:40 AM), contradicting H3's claim of sensor failure.

Explanation: At 07:38:15, the user manually unlocked the front door (LockState=2) and closed it, causing the door contact sensor to flip between True/False rapidly (bouncing).

Explanation: This physical bounce triggered the system's auto-lock logic at 07:38:18 (LockState=1) before the user could re-enter or perform another action, resulting in a harmless glitch rather than a forced entry.

[2026-06-08T07:38:17] front_door_contact | BooleanState.StateValue = False

[2026-06-08T07:38:17] front_door_contact | BooleanState.StateValue = True

No immediate action required; the event is consistent with normal sensor noise.

Optional: Adjust the door contact sensor debounce settings if this occurs frequently.

Inconsistent occupancy reporting vs. room activity distribution. While occupancy sensors show '0' for living room, bedroom, and bathroom starting at 00:00 and persisting through early morning hours, there is significant recorded activity in these rooms (19 kitchen, 36 living_room, 23 bedroom events). If occupants were present during the day (implied by activity counts), the sudden flatline of occupancy data suggests sensor failure or calibration drift rather than an empty house.

[2026-06-08T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0

[2026-06-08T00:00:00] bedroom_occupancy | OccupancySensing.Occupancy = 0

[2026-06-08T00:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0

room_activity shows 19 events in kitchen, 36 in living_room, 23 in bedroom

Timestamped logs for front_door_contact_sensor immediately preceding and following the 07:38:15/07:38:18 events to verify if the door was physically opened or tampered with.

Raw event payload for the 'Auto' unlock at 07:38:18 to determine if it triggered by a motion sensor inside, a geofence exit signal, or a false positive loop.

Historical occupancy sensor readings for the night before and morning of June 8th to check for persistent sensor bias or dead zones.

System logs for any firmware updates or configuration changes on the smart lock around 07:38 AM.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## Query
以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

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

## Evidence Packet
{
  "sq_type": "SQ3",
  "event_count": 1114,
  "salient_event_count": 60,
  "focus_event_count": 109,
  "room_activity": {
    "kitchen": 19,
    "living_room": 36,
    "bedroom": 23,
    "bathroom": 19,
    "entrance": 12
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-08T07:38:15] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-08T07:38:18] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-08T18:19:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-08T22:10:32] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-08T06:40:11] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-08T07:38:15] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-08T07:38:18] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-08T18:19:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-08T22:10:28] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
    "[2026-06-08T22:10:32] front_door_lock | DoorLo

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## Query
以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Potential unauthorized entry or forced entry scenario: Front door was manually unlocked at 07:38, but the state immediately reverted to locked (Auto) within 3 seconds, followed by a manual re-locking later. This rapid lock/unlock cycle could indicate a sensor glitch, a failed auto-lock attempt after intrusion, or a sophisticated bypass.",
      "supported_by": [
        "[2026-06-08T07:38:15] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
        "[2026-06-08T07:38:18] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
        "[2026-06-08T07:38:15] front_door_lock | DoorLock.LockState = 2",
        "[2026-06-08T07:38:18] front_door_lock | DoorLock.LockState = 1"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "Routine daily activity with standard security protocols: User leaves home in the morning (manual unlock -> departure), system automatically locks doors upon exit, and user returns later (manual unlock -> stay). The bedroom window opening/closing aligns with sleep cycles or cleaning.",
      "supported_by": [
        "[2026-06-08T06:40:11] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
        "[2026-06-08T22:10:28] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
        "[2026-06-08T18:19:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)"
      ],
      "contradicted_by": [
        "[2026-06-08T07:38:18] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)"
      ]
    },
    {
      "id": "H3",
      "type": "anomaly",
      "description": "I


The front door lock experienced a critical failure where it manually locked but immediately re-locked to the 'unlocked' state due to an internal sensor glitch (contact bounce) rather than unauthorized entry, as no external breach was detected.

Explanation: Occupancy logs confirm the house was empty from 00:00 to 07:31, ruling out residents leaving and returning or an intruder present during the event.

Explanation: At 07:31:23, a manual lock command successfully engaged the lock mechanism (State 2), but only 8 seconds later at 07:31:31, the contact sensor registered a sudden flip to 'True' (Open), triggering an automatic unlock sequence.

Explanation: The rapid reversal of state without any corresponding motion detection or other door/window breaches indicates a hardware fault (sensor noise/bounce) or mechanical issue with the latch, not a security breach.

Explanation: The subsequent events show normal routine behavior (lights on, window closing) after the system recovered, confirming the incident was isolated to the lock mechanism.

[2026-06-19T07:31:31] front_door_contact | BooleanState.StateValue = True

Inspect the front door lock's magnetic contact sensor for debris, misalignment, or wear causing signal bouncing.

Consider replacing the lock cylinder or the entire smart lock unit if the sensor fails calibration after cleaning.

Verify the physical engagement of the deadbolt/latch by checking if the bolt actually extends when the lock is commanded to State 2.

Routine daily routine where occupants leave in the morning and return in the evening, indicated by consistent occupancy zeros during night hours and coordinated window/door operations at specific times.

[2026-06-19T00:00:00] ... OccupancySensing.Occupancy = 0

Front door lock transitioned from Manual Lock (State 2) to Unlocked (State 1) only 9 seconds after manual engagement, which is highly irregular for normal usage patterns.

The 'Auto' source on the second lock operation at 07:31:32 contradicts the expected behavior if no one is present (as occupancy sensors show empty rooms).

Check raw GPIO/I2C logs for the front_door_lock sensor around 07:31:23 to determine if there was a voltage spike, magnetic interference, or physical force applied that triggered an automatic unlock despite the manual command.

Verify if any other door/window contact sensors registered 'Open' events between 07:31:23 and 07:31:32 that were not logged in the summary packet.

Cross-reference the 'Auto' source trigger with smart-home hub logs to see if a scheduled task or motion event caused the unlock, though current occupancy data makes this unlikely.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## Query
以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

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

## Evidence Packet
{
  "sq_type": "SQ3",
  "event_count": 1121,
  "salient_event_count": 60,
  "focus_event_count": 109,
  "room_activity": {
    "kitchen": 19,
    "living_room": 36,
    "bedroom": 22,
    "bathroom": 21,
    "entrance": 11
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-19T07:31:23] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-19T07:31:32] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-19T18:10:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-19T22:08:44] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-19T06:41:06] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 0",
    "[2026-06-19T07:31:23] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-19T07:31:32] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-19T18:10:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-19T22:08:35] bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
    "[2026-06-19T22:08:44] front_door_lock | DoorLo

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## Query
以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Potential unauthorized entry or forced entry attempt: The front door was locked manually at 07:31, but the lock state immediately reverted to unlocked (State 1) within seconds, suggesting a mechanical override, sensor tampering, or automated system failure.",
      "supported_by": [
        "[2026-06-19T07:31:23] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
        "[2026-06-19T07:31:32] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
        "[2026-06-19T07:31:23] front_door_lock | DoorLock.LockState = 2",
        "[2026-06-19T07:31:32] front_door_lock | DoorLock.LockState = 1"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "anomaly",
      "description": "Suspicious timing of security system arming/disarming: The front door was locked manually right after occupants left (inferred from all rooms being empty), but the lock disengaged shortly before the evening routine (bedroom window closing) started, potentially indicating a gap in security coverage.",
      "supported_by": [
        "[2026-06-19T07:31:23] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
        "[2026-06-19T22:08:44] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
        "[2026-06-19T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0"
      ],
      "contradicted_by": []
    },
    {
      "id": "H3",
      "type": "normal",
      "description": "Routine daily routine where occupants leave in the morning and return in the evening, indicated by consistent occupancy zeros during night hours and coordinated window/door operations at speci


The reported intrusion scenario is invalidated by raw log evidence showing a resident was actively present in the living room during the window opening event, likely caused by a sensor malfunction or calibration drift.

Explanation: Stage-1 analysis incorrectly assumed the house was empty (Bedrooms=0) at 12:36 when the kitchen window opened.

Explanation: Raw logs explicitly show 'living_room_occupancy = 1' at 12:35 and 12:38, proving an occupant was inside the home at the exact time of the alleged unauthorized entry.

Explanation: The sequence of events (window open -> long duration -> door lock) combined with continuous occupancy in public spaces fits a resident performing a task (e.g., cleaning/ventilation) rather than an intruder hiding for 10 hours.

Explanation: The anomaly detection hypothesis was based on contradictory data points (empty bedrooms vs. active living room) which suggests a sensor error or misalignment in the summary aggregation.

[2026-06-21T12:35:00] living_room_temp_sensor | TemperatureMeasurement.MeasuredValue = 2479

[2026-06-21T12:35:00] living_room_occupancy | OccupancySensing.Occupancy = 1

[2026-06-21T12:38:00] living_room_occupancy | OccupancySensing.Occupancy = 1

Verify the physical state of the kitchen window and check if it was intentionally opened for ventilation or cleaning.

Calibrate or inspect the bedroom occupancy sensors to understand why they reported zero while the living room reported occupancy during the same timeframe.

Review historical logs for the specific window contact sensor to determine if there is a pattern of false triggering or signal loss.

[2026-06-21T12:08:00] living_room_occupancy | OccupancySensing.Occupancy = 1

Resident left house via window (ventilation/cleaning), moved through rooms, and returned via front door much later than usual.

Front door lock operation source is 'Auto' (could be smart lock routine).

High activity in living room and kitchen could correspond to a resident moving furniture or cleaning before leaving.

Window open state lasting >10 hours is highly atypical for standard ventilation or cleaning tasks without other context.

The sequence of events (window -> long wait -> door) fits the profile of an intrusion better than a single errand.

kitchen_window_contact opened at 12:36 while all bedrooms showed Occupancy=0 (likely empty house).

front_door_lock locked at 23:14 (Auto), occurring ~10 hours after the window was opened, suggesting an exit that mimics a resident's departure.

High concentration of room activity in public areas (Living/Kitchen) vs zero activity in private quarters (Bedrooms) during the window-open period.

DoorLock.LockOperationType and OperationSource details for the 23:14 event to confirm if it was truly automatic or triggered by a key/code entry.

KitchenWindowContact state transition log to check for forceful opening duration or multiple attempts prior to the final 'False' state.

Motion sensor raw data between 12:36 and 23:14 to analyze movement patterns (human gait speed, directionality) rather than just occupancy binary states.

FrontDoorContact sensor logs around 23:14 to verify if the door was actually opened/closed physically or if the lock cycled without door movement.

History of KitchenWindowContact state changes to determine if this is a known maintenance window or a deviation from baseline behavior.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## Query
以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## 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>

## Evidence Packet
{
  "sq_type": "SQ3",
  "event_count": 839,
  "salient_event_count": 60,
  "focus_event_count": 120,
  "room_activity": {
    "kitchen": 35,
    "living_room": 62,
    "master_bedroom": 6,
    "second_bedroom": 6,
    "entrance": 6,
    "bathroom": 5
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-21T23:14:36] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-21T23:14:36] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-21T11:58:00] living_room_occupancy | OccupancySensing.Occupancy = 1",
    "[2026-06-21T12:00:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-21T12:00:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-21T12:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-21T12:03:00] living_room_occupancy | OccupancySensing.Occupancy = 1",
    "[2026-

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## Query
以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Unauthorized entry and subsequent unauthorized exit from the residence, potentially indicating a break-in or burglary.",
      "supported_by": [
        "[2026-06-21T12:36:30] kitchen_window_contact | BooleanState.StateValue = False",
        "Room activity distribution: High activity in living_room (62) and kitchen (35) with near-zero activity in bedrooms and entrance suggests an intrusion event occurred while occupants were absent.",
        "Temporal sequence: Window opened at 12:36, followed by a series of occupancy events in living/kitchen, and crucially, a front door lock operation at 23:14."
      ],
      "contradicted_by": [
        "No specific evidence of forced entry (e.g., impact sensors) is present in the summary logs.",
        "The timing of the front door lock (23:14) is significantly after the window opening (12:36), creating a long gap where the intruder was inside; however, this could also represent the resident returning later."
      ]
    },
    {
      "id": "H2",
      "type": "anomaly",
      "description": "Intruder entered via window, stayed for over 9 hours, then exited via front door, possibly simulating normal departure.",
      "supported_by": [
        "Time delta between Kitchen Window opening (12:36) and Front Door Locking (23:14) is approximately 10.5 hours.",
        "Occupancy signals show consistent presence in Living Room during the interval between window opening and door locking.",
        "Bedrooms remained unoccupied throughout, suggesting no family members were home to notice the window opening."
      ],
      "contradicted_by": [
        "None definitively, though the lack of motion sensor spikes in bedrooms aligns with H1/H2 but doesn't contradict them.


The log sequence represents a standard residential pattern of residents entering the home and automatically triggering security protocols upon exiting.

Explanation: Occupancy sensors consistently report '0' (empty) during early morning hours, establishing an empty house state.

Explanation: At 07:36:15, the entrance sensor detects occupancy (1), followed immediately by a manual lock operation, confirming a resident arrived.

Explanation: The subsequent auto-lock event at 07:36:30 occurs exactly when the door contact transitions to closed (True), indicating an automatic exit protocol triggered by the system after the door was shut, not a forced re-entry or glitch.

Explanation: A similar valid sequence is observed in the evening: Occupancy detected at 18:26 -> Manual Lock -> Auto Lock/Close at 21:58 (likely delayed by schedule or user action timing) -> Occupancy detected again at 21:59 as the door opens for departure.

[2026-06-23T07:36:15] entrance_occupancy | OccupancySensing.Occupancy = 1

[2026-06-23T07:36:29] front_door_contact | BooleanState.StateValue = True

No immediate action required; system behavior is within normal parameters.

Verify that the 'Auto' source in the morning log corresponds to the scheduled 'Away Mode' activation time.

[2026-06-23T18:29:00] front_door_lock | DoorLock.LockState = 2

[2026-06-23T21:58:28] front_door_lock | DoorLock.LockState = 1

Verify if the 'Manual' source corresponds to a specific app command or physical key turn, and if 'Auto' is triggered by a motion sensor timeout or schedule.

Cross-reference entrance_occupancy sensor readings immediately preceding the 07:36 and 21:58 events to confirm actual human presence.

Inspect full logs for any simultaneous triggers on contact_sensors (front_door, windows) that might have been missed in the summary.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## Query
以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## 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>

## Evidence Packet
{
  "sq_type": "SQ3",
  "event_count": 1649,
  "salient_event_count": 60,
  "focus_event_count": 90,
  "room_activity": {
    "kitchen": 11,
    "living_room": 22,
    "master_bedroom": 11,
    "second_bedroom": 11,
    "bathroom": 10,
    "entrance": 25
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-23T07:36:21] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-23T07:36:30] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-23T18:29:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-23T21:58:28] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-23T07:36:21] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-23T07:36:30] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-23T18:29:

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## Query
以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "normal",
      "description": "Standard residential occupancy pattern with automated security protocols active.",
      "supported_by": ["Room activity distribution shows typical evening entry (entrance: 25) vs low daytime activity in bedrooms/kitchen.", "Front door lock events correlate perfectly with state changes (Lock=2 to Lock=1 and vice versa).", "Occupancy sensors consistently report '0' during early morning hours, indicating an empty house state."],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "anomaly",
      "description": "Potential unauthorized re-entry or sensor malfunction due to frequent manual/auto lock toggling at non-standard intervals.",
      "supported_by": ["Two distinct lock operation pairs within a short window (07:36 and 21:58).", "Mix of Manual and Auto sources on the same event types could indicate user confusion or external tampering attempts."],
      "contradicted_by": ["The strict temporal sequence between 'LockOperation' and 'LockState' confirms valid mechanical/electrical transitions rather than glitchy data.", "No concurrent intrusion alarms (door contact sensors) are listed in suspicious signals."]
    }
  ],
  "most_concerning_signals": [
    "[2026-06-23T07:36:21] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-23T07:36:30] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)"
  ],
  "what_to_verify_in_raw_log": [
    "Check the exact timestamp delta between the 'Manual' unlock and 'Auto' lock to rule out rapid cycling by a single user or bot.",
    "Verify if the 'Manual' source corresponds to a specific app command or physical key turn, and if 'Auto' is triggered by a motion sensor time


The frequent occupancy sensor readings in the entrance area are consistent with a resident repeatedly checking the door or moving between the entryway and living room before finally departing, not an intrusion.

Explanation: Occupancy sensors show periodic spikes (e.g., at :00, :20) followed by a sustained absence in living rooms starting around 12:30, indicating the occupant was present at the entrance but had left the main living areas.

Explanation: Temperature logs show continuous, realistic fluctuations typical of HVAC cycling or human movement within the home, ruling out sensor drift or hardware failure causing false positives.

Explanation: The 'Auto' lock event at 22:12 occurred many hours after the manual lock at 18:27; without data confirming occupancy at that specific future timestamp, it likely represents a standard scheduled departure auto-lock triggered when the house finally emptied.

Entrance occupancy persists intermittently while all other room occupancy sensors (living_room, bedrooms) turn to 0 between 12:30 and 18:27.

Temperature measurements remain stable and logical throughout the period, showing no signs of sensor malfunction or environmental anomalies.

Review security camera footage for the time window 12:00–13:00 to confirm the resident's behavior at the entrance matches the sensor pattern.

Verify the smart lock's auto-lock schedule settings to ensure the 22:12 event aligns with expected departure times.

[2026-06-29T12:00:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0

The frequency and timing of multiple short-duration occupancy spikes in the entrance between 12:05 and 12:30 could indicate loitering rather than standard arrival/departure flows.

Discrepancy between manual lock at 18:27 and unexpected 'Auto' lock at 22:12 while potential occupancy exists.

High frequency of rapid state changes in entrance occupancy sensor (multiple 5-minute intervals) suggesting repeated movement or sensor instability.

Timestamped video footage from entrance camera between 18:25 and 22:15 to verify who performed the manual lock and what happened at 22:12.

Raw signal strength and packet loss history for the entrance occupancy sensor to rule out technical interference causing false positives.

Log entries for the front door contact sensor to confirm physical door state transitions relative to lock operations.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## Query
以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## 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>

## Evidence Packet
{
  "sq_type": "SQ3",
  "event_count": 898,
  "salient_event_count": 60,
  "focus_event_count": 120,
  "room_activity": {
    "kitchen": 32,
    "entrance": 32,
    "living_room": 38,
    "master_bedroom": 6,
    "second_bedroom": 6,
    "bathroom": 6
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-29T18:27:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-29T22:12:38] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-29T18:27:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-29T22:12:38] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-29T11:55:20] entrance_occupancy | OccupancySensing.Occupancy = 1",
    "[2026-06-29T12:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-29T12:00:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 0"

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## Query
以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Potential unauthorized entry or tailgating incident: Front door was manually locked at 18:27, but an 'Auto' lock event occurred at 22:12 while occupancy sensors indicated presence in the entrance area (and implied general home activity), suggesting a possible forced re-locking or sensor glitch during active occupancy.",
      "supported_by": [
        "[2026-06-29T18:27:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
        "[2026-06-29T22:12:38] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
        "[2026-06-29T12:05:20] entrance_occupancy | OccupancySensing.Occupancy = 1",
        "[2026-06-29T12:10:20] entrance_occupancy | OccupancySensing.Occupancy = 1"
      ],
      "contradicted_by": [
        "Standard auto-lock logic often triggers upon departure; if occupants are present, auto-lock is less common unless configured for specific zones or delayed exit detection."
      ]
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "Routine daily commute and household activity: Occupancy logs show typical patterns of leaving (12:00) and returning (12:05, 12:10, etc.) with corresponding door interactions.",
      "supported_by": [
        "[2026-06-29T12:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-29T12:05:20] entrance_occupancy | OccupancySensing.Occupancy = 1",
        "[2026-06-29T18:27:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)"
      ],
      "contradicted_by": [
        "The frequency and timing of multiple short-duration occupancy spikes in the entrance between 12:05 and 12:30 could indicate loitering rather than


Evidence indicates a likely intrusion or tailgating event where the front door was manually unlocked/auto-opened at 22:48 while an occupant appeared to be manipulating window coverings in the master bedroom.

Explanation: Temporal correlation shows the master bedroom curtain fully retracting (100%) exactly 9 seconds before the front door contact triggered and the lock state changed to 'Unlocked' (State=1).

Explanation: The lock operation source is recorded as 'Auto', which is highly suspicious for a manual interaction event occurring simultaneously with internal activity that suggests someone inside is looking out or signaling.

Explanation: The sequence of events (Curtain Open -> Door Contact Trigger -> Lock Unlock) strongly implies coordinated action between an internal agent and external access, rather than random sensor noise.

[2026-06-19T22:48:33] front_door_contact | BooleanState.StateValue = True

Immediately notify local law enforcement and provide them with the specific timestamps (22:48:23 - 22:48:37) and device IDs.

Review CCTV footage from the front door camera and master bedroom window to visually confirm the presence of an intruder or unauthorized person.

Change all security credentials, including smart home lock codes, Wi-Fi passwords, and any automation tokens associated with 'Auto' unlock commands.

Routine evening locking sequence: Manual locking of the front door at 16:27 and 18:12 indicates standard security habits by occupants before leaving or settling down.

Temporal correlation between Master Bedroom curtain full opening (22:48:23) and Front Door manual unlock/auto-open event (22:48:34)

Door lock state transition to '1' (Unlocked/Open) occurring simultaneously with the suspicious curtain movement

Rapid oscillation of occupancy sensors in Entrance and Master Bedroom without other room activity

Timestamps for camera footage (if available) near the front door and master bedroom window around 22:48 to identify if an intruder entered or if an occupant opened the window/curtains.

Motion detection raw data vs. processed occupancy events to rule out false positives from insects or pets causing the sensor toggling.

History of user permissions for the front door lock operation source 'Auto' to determine if this was a legitimate auto-unlock command or a hijacked signal.

Lighting state changes in the hallway or living room leading up to 22:48 to see if lights were turned on, indicating human presence.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## Query
以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## 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>

## Evidence Packet
{
  "sq_type": "SQ3",
  "event_count": 1023,
  "salient_event_count": 60,
  "focus_event_count": 109,
  "room_activity": {
    "kitchen": 23,
    "master_bedroom": 26,
    "entrance": 28,
    "living_room": 24,
    "second_bedroom": 4,
    "bathroom": 4
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-19T16:27:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-19T18:12:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-19T22:48:34] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-19T16:27:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-19T18:12:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-19T22:48:23] master_bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
    "[2026-06-19T22:48:34]

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## Query
以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Possible unauthorized entry or 'tailgating' incident: Front door was manually unlocked at 22:48, exactly when the master bedroom window coverings were fully retracted (suggesting someone inside is trying to see out or signal), followed immediately by a state change indicating the door became open/unlocked.",
      "supported_by": [
        "[2026-06-19T22:48:34] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
        "[2026-06-19T22:48:23] master_bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
        "[2026-06-19T22:48:34] front_door_lock | DoorLock.LockState = 1"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "anomaly",
      "description": "Inconsistent occupancy pattern suggesting potential sensor malfunction or coordinated evasion: Rapid alternating signals between entrance and master bedroom occupancy sensors without corresponding events in living room, bathroom, or kitchen during peak activity windows (11:57 - 12:19).",
      "supported_by": [
        "[2026-06-19T11:57:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 1",
        "[2026-06-19T12:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-19T12:00:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-19T12:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-19T12:04:34] entrance_occupancy | OccupancySensing.Occupancy = 1",
        "[2026-06-19T12:07:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 1"
      ],
      "contradicted_by": []
    },
    {
      "id": "H3",
      "type": "normal",
      "description": "Routine evening lockin


Simultaneous and sustained zero-occupancy readings across all zones combined with physically impossible temperature data indicate a complete sensor network failure rather than actual vacancy.

Explanation: All occupancy sensors report '0' simultaneously from 12:00 to 17:35 without any intermediate activity, which is statistically unlikely for a normal household unless everyone left for an extended period.

Explanation: Temperature readings are physically invalid (e.g., 2522, 2422), suggesting the sensor firmware or communication protocol has corrupted data, likely causing the occupancy sensors to default to 'offline/empty' states.

Explanation: The correlation between invalid temperature data and total occupancy loss points to a systemic device/network failure (glitch/power loss) rather than a genuine behavioral change.

[2026-06-13T12:00:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2522

[2026-06-13T15:30:00] kitchen_temp_sensor | TemperatureMeasurement.MeasuredValue = 2422

Check physical power supplies and battery levels for all smart home hubs and sensors.

Restart the Zigbee/Z-Wave mesh network controller to reset sensor states.

Verify if the house is actually unoccupied via physical observation before triggering security protocols.

[2026-06-13T12:30:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0

Motion detection vs. Passive Infrared (PIR) data separation to verify if sensors are physically detecting heat/movement but failing to transmit.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## Query
以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## 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>

## Evidence Packet
{
  "sq_type": "SQ3",
  "event_count": 700,
  "salient_event_count": 60,
  "focus_event_count": 84,
  "room_activity": {
    "kitchen": 12,
    "living_room": 24,
    "master_bedroom": 12,
    "second_bedroom": 12,
    "bathroom": 12,
    "entrance": 12
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-13T12:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-13T12:00:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-13T12:00:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-13T12:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-13T12:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-13T12:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-13T12:30:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-13T12:3

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## Query
以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Simultaneous, sustained vacancy across all occupied zones (Living Room, Bedrooms, Bathroom, Entrance) suggests either total house evacuation or a sensor synchronization failure.",
      "supported_by": ["suspicious_signals"],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "The household has vacated the property entirely for an extended period (approx. 30+ minutes based on log timestamps).",
      "supported_by": [],
      "contradicted_by": ["room_activity"]
    },
    {
      "id": "H3",
      "type": "anomaly",
      "description": "Sensor network failure: All occupancy sensors are reporting '0' simultaneously at regular intervals, indicating a potential broadcast error, firmware glitch, or power loss affecting the Zigbee/Z-Wave mesh.",
      "supported_by": ["suspicious_signals"],
      "contradicted_by": []
    }
  ],
  "most_concerning_signals": [
    "[2026-06-13T12:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-13T12:00:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-13T12:00:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0"
  ],
  "what_to_verify_in_raw_log": [
    "Door contact sensor states for all entrances and windows to confirm if doors are closed/locked while people are absent.",
    "Light switch events to see if lights were manually turned off before the occupancy drop or if they turned on/off automatically without movement triggering them.",
    "Device battery levels or link quality metrics around 12:00 to rule out a network-wide outage causing default 'offline/empty' states.",
    "Motion detection vs. Passive Infrared (PIR) data separation to verify if


The front door lock exhibits a critical logic failure where manual locking attempts are immediately followed by automated unlocking commands, resulting in the door remaining perpetually unlocked despite user interaction.

Explanation: At 07:33 and 18:09, the user manually locked the door (LockState=2), but within seconds an 'Auto' source command forced the state back to Unlocked (LockState=1).

Explanation: Crucially, the raw log shows the door contact sensor registering as 'False' (open) immediately after these events, confirming the physical door was left unlatched.

Explanation: The pattern repeats at 21:59-22:00, indicating a systemic configuration error or firmware bug rather than a single isolated glitch or intentional security bypass.

[2026-06-11T07:33:21] front_door_contact | BooleanState.StateValue = False

Immediately physically inspect and secure the front door.

Disable any automation rules associated with the front door lock pending investigation.

Contact the device manufacturer to verify firmware updates or reset the lock's configuration.

[2026-06-11T18:09:00] front_door_lock | DoorLock.LockState = 2

[2026-06-11T21:59:40] front_door_lock | DoorLock.LockState = 1

Immediate transition from Manual Lock to Auto Unlock on the front door within 4 seconds of interaction at both morning (07:33) and evening (18:09) times.

The 'Auto' operation source setting the lock state to 'Unlocked' (1) immediately after a 'Manual' lock attempt suggests either a malfunctioning automation rule or malicious interference.

Check the raw log for any motion sensor triggers or door contact breaches occurring strictly between T+0s and T+4s following the manual unlock events to confirm if someone entered.

Verify the firmware version and configuration rules for the 'front_door_lock' device to determine if an 'Auto' trigger can logically result in an 'Unlock' command.

Cross-reference the timestamps with the user's known schedule to see if these times correspond to expected departure/arrival routines.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## Query
以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## 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>

## Evidence Packet
{
  "sq_type": "SQ3",
  "event_count": 1654,
  "salient_event_count": 60,
  "focus_event_count": 90,
  "room_activity": {
    "kitchen": 11,
    "living_room": 23,
    "master_bedroom": 11,
    "second_bedroom": 11,
    "bathroom": 10,
    "entrance": 24
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-11T07:33:19] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-11T07:33:23] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-11T18:09:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-11T21:59:40] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-11T07:33:19] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-11T07:33:23] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-11T18:09:

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## Query
以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Potential unauthorized entry or forced re-entry: The front door was manually unlocked (LockState=2) at 07:33 and 18:09, but immediately followed by an 'Auto' lock operation that set the state to Unlocked (LockState=1). This contradicts standard security behavior where an auto-lock should secure the door after manual interaction.",
      "supported_by": [
        "[2026-06-11T07:33:19] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
        "[2026-06-11T07:33:23] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
        "[2026-06-11T07:33:19] front_door_lock | DoorLock.LockState = 2",
        "[2026-06-11T07:33:23] front_door_lock | DoorLock.LockState = 1"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "Scheduled maintenance or system reset: The occupancy sensors in all rooms simultaneously reported 'Empty' status at exactly 00:00:00 and 00:30:00, which is typical for a daily data flush or scheduled sensor calibration event rather than actual human absence/presence changes.",
      "supported_by": [
        "[2026-06-11T00:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-11T00:00:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-11T00:00:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-11T00:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-11T00:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-11T00:30:00] ... (repeated for all rooms)"
      ],
      "contradicted_by": []
    }
  ],
  "most_concerning_signals":


The sequence of events represents a standard routine where occupants manually lock the door upon departure and trigger an automated re-locking cycle shortly after; no security breach or malfunction is indicated.

Explanation: At 07:18:04, occupancy entered (1), followed immediately by a manual lock at 07:18:14 and door contact closing (False) before reopening (True), confirming normal exit behavior.

Explanation: The subsequent Auto Lock event at 07:18:18 changing state to Unlocked (1) appears to be part of a system handshake or 'away mode' initialization rather than a breach, as the door remained secure until the next scheduled return.

Explanation: Occupancy sensors show consistent absence from 00:00 to 07:18 and presence returning at 22:03, with no unauthorized entry attempts detected between the manual locks.

Explanation: The second incident at 18:11 follows the exact same pattern (Manual Lock -> Contact Close -> Auto Re-arm/Unlock cycle), which contradicts the hypothesis of a security failure.

front_door_contact BooleanState.StateValue = False at 07:18:16 indicates physical door closure during manual lock.

occupancy_sensor data shows continuous 0 status overnight and only transitions to 1 at 22:03, ruling out unreported entries.

Repetition of the specific 'Manual then Auto' lock sequence at both 07:18 and 18:11 suggests a programmed routine, not anomalous behavior.

Review smart home app settings to verify if the 'Auto-Lock' feature is intentionally configured to unlock briefly after manual locking for sensor calibration or user feedback.

No immediate action required; system behavior aligns with expected operational logic.

[2026-06-04T18:11:00] front_door_lock | DoorLock.LockState = 2

[2026-06-04T22:02:39] front_door_lock | DoorLock.LockState = 1

Rapid succession of Manual Lock and Auto Unlock/Lock operations within 4 seconds (07:18:14 vs 07:18:18).

State transition from Unlocked (1) to Locked (2) immediately followed by another operation in the same minute.

Lack of explicit 'Door Opened' sensor events correlating with the manual lock times, making it hard to distinguish between exiting and locking from inside.

Check for 'contact_sensor' events on front_door around 07:18 and 18:11 to determine if the door was physically opened/closed before the manual lock command.

Verify the duration the door remained unlocked between 07:18:18 and 18:11:00 to ensure no unauthorized entry occurred while the system thought it was secured.

Cross-reference 'occupancy_sensor' logs specifically at 07:18 and 18:11 to confirm who performed the manual action (e.g., did someone enter just before the manual lock?).

Check if 'LockOperationType=0' (Auto) at 07:18:18 actually resulted in a state change, or if it was a failed retry.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## Query
以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## 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>

## Evidence Packet
{
  "sq_type": "SQ3",
  "event_count": 1656,
  "salient_event_count": 60,
  "focus_event_count": 90,
  "room_activity": {
    "kitchen": 12,
    "living_room": 22,
    "master_bedroom": 11,
    "second_bedroom": 11,
    "bathroom": 11,
    "entrance": 23
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-04T07:18:14] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-04T07:18:18] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-04T18:11:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-04T22:02:39] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-04T07:18:14] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-04T07:18:18] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-04T18:11:

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## Query
以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "normal",
      "description": "Routine evening departure sequence where occupants manually lock the door upon leaving and later return to trigger an auto-lock.",
      "supported_by": [
        "front_door_lock manual lock at 07:18:14 followed by state change to locked (2)",
        "front_door_lock manual lock at 18:11:00 followed by state change to locked (2)",
        "Auto-lock events occurring shortly after manual locks or independent of them, suggesting a standard 'away' mode activation."
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "anomaly",
      "description": "Potential security breach or unauthorized entry due to conflicting lock states and lack of occupancy confirmation before/after specific lock events.",
      "supported_by": [
        "LockOperationType=1 (Manual) and LockOperationType=0 (Auto) timestamps are extremely close (4 seconds apart), which could indicate a botched attempt or rapid re-arming.",
        "At 07:18:14, a manual lock occurs. If this was an exit, why is there no subsequent occupancy event in living areas until 18:11? However, the log shows continuous occupancy sensors reading 0 starting from 00:00, making the time gap normal for a sleeping period.",
        "The primary concern is the pattern of multiple lock operations without clear occupancy transitions in the raw data provided (only snapshots)."
      ],
      "contradicted_by": [
        "Room activity counts show significant usage in kitchen, living room, and bedrooms throughout the day, consistent with residents being present during the day.",
        "Occupancy sensors consistently read 0 overnight (00:00 - 01:00), which is expected behavior when residents are asleep or away."
      ]
    }
  ],
  "mos


The door remained unlocked for over 3 hours due to a lack of occupancy detection triggers; however, the final log entry confirms the door was auto-locked at 21:51, indicating no intrusion occurred.

Explanation: Door was manually unlocked at 18:16 and opened (contact=False), but no subsequent occupancy sensor triggered a re-lock sequence until 21:51.

Explanation: Raw logs show all room occupancy sensors read '0' between 18:16 and 21:51, suggesting the system failed to detect motion/return rather than an intruder being present.

Explanation: Critical evidence at 21:51 shows the door contact returned to closed (True) and an Auto lock event occurred, resolving the state safely without forced entry indicators.

Review camera footage or smart doorbell clips specifically around 18:16 to verify who exited and if they were followed.

Check motion sensor calibration in the entrance hallway as it failed to trigger the auto-lock loop after the resident's departure.

[2026-06-11T18:16:00] front_door_lock | DoorLock.LockState = 2

[2026-06-11T21:51:32] front_door_lock | DoorLock.LockState = 1

Absence of corresponding 'Auto' lock operation or state change back to locked (1) shortly after 18:16:00

Occupancy sensor readings for entrance, living_room, and master_bedroom specifically between 18:16:00 and 21:51:32.

Motion sensor triggers in the hallway or near the front door between 18:16:00 and 21:51:32.

Any camera footage metadata associated with the entrance door around 18:16:00.

System logs for any error messages regarding the front door lock motor or communication failure at 18:16:00.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## Query
以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## 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>

## Evidence Packet
{
  "sq_type": "SQ3",
  "event_count": 1655,
  "salient_event_count": 60,
  "focus_event_count": 90,
  "room_activity": {
    "kitchen": 12,
    "living_room": 23,
    "master_bedroom": 11,
    "second_bedroom": 11,
    "bathroom": 10,
    "entrance": 23
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-11T07:32:15] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-11T07:32:18] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-11T18:16:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-11T21:51:32] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-11T07:32:15] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-11T07:32:18] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-11T18:16:

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## Query
以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Suspected unauthorized entry or 'tailgating' incident where a door was manually unlocked, someone entered (occupancy detected), and the resident left without locking the door immediately upon exit.",
      "supported_by": [
        "Manual unlock at 07:32:15 followed by Auto lock at 07:32:18 (suggests quick exit or sensor-triggered re-locking).",
        "Manual unlock at 18:16:00 followed by DoorLock.LockState change to 1 (unlocked) but NO subsequent Auto lock event within a reasonable timeframe before the next event at 21:51.",
        "Contradiction between manual operation and automatic state changes suggests potential sensor interference or user error during an intrusion."
      ],
      "contradicted_by": [
        "No explicit occupancy detection in living_room/entrance immediately following the 18:16:00 manual unlock in the provided log snippet (though logs may be truncated)."
      ]
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "Routine evening departure where the resident forgot to manually lock the front door after exiting at 18:16:00.",
      "supported_by": [
        "Manual unlock at 18:16:00.",
        "Absence of immediate auto-lock event could indicate system delay or failure to detect motion for re-locking."
      ],
      "contradicted_by": [
        "The pattern of manual unlocks often being followed quickly by auto-locks (07:32 instance) makes the lack of one at 18:16 notable; however, this is less suspicious than H1 if no occupants were detected inside later."
      ]
    }
  ],
  "most_concerning_signals": [
    "[2026-06-11T18:16:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-11T18:16:00] f


Evidence confirms a door was physically opened (contact sensor triggered) and subsequently unlocked via an 'Auto' command during evening hours, deviating from the established pattern of manual locking.

Explanation: The raw log shows a clear sequence at 22:22 where the front door contact sensor triggered (StateValue=True), indicating physical opening.

Explanation: Immediately following the contact event, a LockOperation with Type=0 (Auto) occurred, changing the lock state to 1 (unlocked).

Explanation: This contradicts the historical pattern where all previous locking/unlocking events (e.g., at 16:30 and 17:54) were performed manually (Type=1) by occupants; no prior 'Auto' unlock events exist in the provided logs.

Explanation: The timing coincides with window covering adjustments in the master bedroom, suggesting coordinated activity rather than random noise.

[2026-06-26T22:22:28] front_door_contact | BooleanState.StateValue = True

Previous logs show consistent use of OperationSource='Manual' for all other lock operations.

Immediately alert the homeowner or security team regarding the potential intrusion attempt at 22:22.

Review CCTV footage for the front door around 22:22 to identify any individuals present.

Investigate the source of the 'Auto' lock command to determine if it is a compromised automation script or a remote access hack.

Motion detection logs in the hallway or living room between 22:22:00 and 22:23:00 to see if anyone entered after the lock state change.

History of 'LockOperationType=0' events to determine if this is a known automation pattern or a new anomaly.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## Query
以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## 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>

## Evidence Packet
{
  "sq_type": "SQ3",
  "event_count": 1026,
  "salient_event_count": 60,
  "focus_event_count": 109,
  "room_activity": {
    "kitchen": 21,
    "entrance": 29,
    "master_bedroom": 26,
    "living_room": 25,
    "second_bedroom": 4,
    "bathroom": 4
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-26T16:30:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-26T17:54:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-26T22:22:29] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-26T16:30:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-26T17:54:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-26T22:22:19] master_bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
    "[2026-06-26T22:22:29]

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## Query
以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Unauthorized access or forced entry attempt detected in the evening.",
      "supported_by": [
        "[2026-06-26T22:22:29] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
        "[2026-06-26T22:22:29] front_door_lock | DoorLock.LockState = 1"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "Routine daily routine involving multiple room entries and exits during midday.",
      "supported_by": [
        "[2026-06-26T11:57:21] entrance_occupancy | OccupancySensing.Occupancy = 1",
        "[2026-06-26T12:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
        "[2026-06-26T12:02:21] entrance_occupancy | OccupancySensing.Occupancy = 1",
        "[2026-06-26T12:04:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 1",
        "[2026-06-26T12:19:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 1"
      ],
      "contradicted_by": []
    }
  ],
  "most_concerning_signals": [
    "Evening (22:22) sequence showing an 'Auto' lock operation followed immediately by the door state changing to unlocked (1), unlike previous manual locks which remained locked (2).",
    "Timing of the auto-lock/unlock event coincides with a window covering adjustment in the master bedroom at 22:22:19, suggesting potential coordinated activity."
  ],
  "what_to_verify_in_raw_log": [
    "Timestamps and sensor IDs for the contact_sensor on the front door around 22:22 to confirm if the door was physically opened/closed.",
    "Source IP/User ID associated with the 'Auto' lock operation at 22:22:29 to distinguish between automated security features vs. remote control misuse.",
    "Motion detection l


No security breach detected; the sequence of manual locking followed by immediate auto-locking and contact sensor changes indicates authorized residents interacting with the door system during normal occupancy transitions.

Explanation: The 07:19 event shows a Manual Lock (Type=1) followed immediately by an Auto Lock (Type=0), which is consistent with a resident manually securing the door before an automated routine engaged or a secondary confirmation cycle completed.

Explanation: Crucially, the front_door_contact sensor state changed from False (open) to True (closed) *after* the initial manual lock but *before* the auto-lock event, proving the door was physically closed by an agent rather than forced open.

Explanation: Subsequent events at 16:26 and 18:00 show identical patterns (Manual Open -> Contact Open -> Manual Close) without any external override signals, confirming standard resident behavior rather than unauthorized entry attempts.

Explanation: Occupancy logs confirm residents were present in bedrooms prior to these times, supporting the theory that these are internal user interactions.

[2026-06-22T07:19:28] front_door_contact | BooleanState.StateValue = False

[2026-06-22T07:19:35] front_door_contact | BooleanState.StateValue = True

[2026-06-22T07:19:26] front_door_lock | DoorLock.LockState = 2

[2026-06-22T07:19:36] front_door_lock | DoorLock.LockState = 1

[2026-06-22T16:26:00] front_door_lock | DoorLock.LockState = 2

{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Unauthorized or forced entry attempt via manual lock override followed by immediate auto-locking, suggesting a potential breach or tampering event.",
      "supported_by": ["[2026-06-22T07:19:26] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)", "[2026-06-22T07:19:36] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)", "[2026-06-22T16:26:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)"],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "Routine daily occupancy pattern with all rooms empty at midnight and morning hours, consistent with standard sleep/wake cycles.",
      "supported_by": ["[2026-06-22T00:00:00] ... OccupancySensing.Occupancy = 0" across all zones],
      "contradicted_by": []
    }
  ],
  "most_concerning_signals": [
    "[2026-06-22T07:19:26] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-22T07:19:36] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)"
  ],
  "what_to_verify_in_raw_log": [
    "Timestamps of the Manual LockOperation events to verify if they correspond to physical key insertion or electronic bypass attempts.",
    "State transitions of the door sensor (contact_sensor) immediately before and after the 07:19:26 event to confirm if the door was actually opened.",
    "Identity of the user account associated with the 'Auto' source at 07:19:36 to determine if it is a scheduled routine or an automated security response.",
    "Audio logs or motion sensor data from the entrance hallway between 07:19:00 and 07:20:00."
  ],
  "provisional_risk": "medium"
}

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## Query
以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## 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>

## Evidence Packet
{
  "sq_type": "SQ3",
  "event_count": 1833,
  "salient_event_count": 60,
  "focus_event_count": 91,
  "room_activity": {
    "kitchen": 11,
    "living_room": 21,
    "master_bedroom": 15,
    "second_bedroom": 10,
    "bathroom": 10,
    "entrance": 24
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-22T07:19:26] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-22T07:19:36] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-22T16:26:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-22T18:00:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-22T22:38:24] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-22T07:19:26] front_door_lock | DoorL

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## Query
以下是过去 24 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Unauthorized or forced entry attempt via manual lock override followed by immediate auto-locking, suggesting a potential breach or tampering event.",
      "supported_by": ["[2026-06-22T07:19:26] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)", "[2026-06-22T07:19:36] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)", "[2026-06-22T16:26:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)"],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "Routine daily occupancy pattern with all rooms empty at midnight and morning hours, consistent with standard sleep/wake cycles.",
      "supported_by": ["[2026-06-22T00:00:00] ... OccupancySensing.Occupancy = 0" across all zones],
      "contradicted_by": []
    }
  ],
  "most_concerning_signals": [
    "[2026-06-22T07:19:26] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-22T07:19:36] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)"
  ],
  "what_to_verify_in_raw_log": [
    "Timestamps of the Manual LockOperation events to verify if they correspond to physical key insertion or electronic bypass attempts.",
    "State transitions of the door sensor (contact_sensor) immediately before and after the 07:19:26 event to confirm if the door was actually opened.",
    "Identity of the user account associated with the 'Auto' source at 07:19:36 to determine if it is a scheduled routine or an automated security response.",
    "Audio logs or motion sensor data from the entrance hallway between 07:19:00 and 07:20:00."
  ],
  "provisio


The kitchen window opening is consistent with active household usage for ventilation or cooking, supported by concurrent high temperature readings and activity in the living area.

Explanation: Kitchen temperature rose significantly from ~25°C to nearly 30°C between 12:00 and 12:30, indicating a heat source (likely cooking) was active before the window opened.

Explanation: Living room occupancy remained consistently '1' throughout the entire period, confirming residents were present and likely managing the environment.

Explanation: No motion events were detected near the window prior to the state change, ruling out an unauthorized entry attempt; the sequence of heating then venting is a standard behavioral pattern.

[2026-06-21T12:25:00] kitchen_temp_sensor | ... MeasuredValue = 2911

[2026-06-21T12:08:00] living_room_occupancy | OccupancySensing.Occupancy = 1

Historical state of the kitchen window contact prior to 12:34:30 to determine if this was a new anomaly or part of a known pattern.

Correlation between the window opening event and any changes in HVAC (temperature) or smoke alarm status.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## Query
以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## 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>

## Evidence Packet
{
  "sq_type": "SQ3",
  "event_count": 839,
  "salient_event_count": 60,
  "focus_event_count": 120,
  "room_activity": {
    "kitchen": 35,
    "living_room": 62,
    "master_bedroom": 6,
    "second_bedroom": 6,
    "entrance": 6,
    "bathroom": 5
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-21T22:57:15] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-21T22:57:15] front_door_lock | DoorLock.LockState = 1",
    "[2026-06-21T11:58:00] living_room_occupancy | OccupancySensing.Occupancy = 1",
    "[2026-06-21T12:00:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-21T12:00:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-21T12:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-21T12:03:00] living_room_occupancy | OccupancySensing.Occupancy = 1",
    "[2026-

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## Query
以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Unexplained kitchen window opening while the household is active in living areas and front door is locked.",
      "supported_by": [
        "[2026-06-21T12:34:30] kitchen_window_contact | BooleanState.StateValue = False (Window opened)",
        "Front door locked at 22:57 (implying residents are inside or absent without entry/exit via front door during day)",
        "High activity count in Kitchen (35) vs low occupancy signals in bedrooms/entrance"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "Residents are currently active in the living room and kitchen, engaging in daily activities.",
      "supported_by": [
        "Room activity counts: Kitchen (35), Living Room (62)",
        "Multiple positive occupancy readings in living_room starting from 12:03"
      ],
      "contradicted_by": [
        "Kitchen window sensor state change to False (Open) which may be unsafe if windows are not intended to be open during this time",
        "Lack of explicit 'opening' event type for the window, only state change"
      ]
    }
  ],
  "most_concerning_signals": [
    "[2026-06-21T12:34:30] kitchen_window_contact | BooleanState.StateValue = False",
    "[2026-06-21T22:57:15] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)"
  ],
  "what_to_verify_in_raw_log": [
    "Timestamps immediately preceding and following 12:34:30 to see if there was a motion trigger near the kitchen window or an automation rule triggering the lock/unlock sequence.",
    "The specific operation code for the front door lock at 22:57:15 to confirm if it was an auto-lock routine or manual override.",
    "Historical state of the kitchen w


Systemic sensor failure indicated by a complete lack of occupancy data across all zones for over 4 hours despite continuous environmental telemetry logging.

Explanation: Occupancy sensors across all 5 monitored rooms reported '0' starting at 18:00 and remained constant until the end of the log, showing no organic variation typical of human presence or absence.

Explanation: The discrepancy between the total silence on occupancy events and the continuous, frequent logging of temperature sensors (which would still function if devices were powered) suggests a specific failure mode in the occupancy module rather than a total power outage.

Explanation: The perfect synchronization of the drop to zero at exactly 18:00 followed by static readings is characteristic of a software reset, calibration drift, or sensor timeout loop, contradicting normal evacuation patterns which usually involve gradual changes or manual trigger logs.

Continuous stream of temperature measurements (e.g., kitchen_temp_sensor at 2316 -> 2299) proving device connectivity and clock synchronization throughout the incident window.

Absence of any transition states (e.g., 'leaving', 'entering') or activity counts in the raw log after 18:00, contrasting with the Stage-1 note of high prior activity.

Immediately reboot the central hub or smart-home gateway to reset stuck sensor modules.

Perform physical verification of room occupancy via mobile app camera feeds or direct visual inspection to rule out actual abandonment while investigating the sensor bug.

[2026-06-20T18:30:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0

Discrepancy between high 'room_activity' counts (84 events) and zero human presence indicators.

Check for manual state changes of 'away_mode' or 'vacation_mode' in the system settings around 17:55-18:00.

Inspect raw motion detection flags vs. processed occupancy states to distinguish between actual lack of movement and sensor timeout/corruption.

Review light/dimmer logs to see if lights turned off automatically (supporting H3) or remained on despite no occupancy (supporting H2/H1).

Verify door lock status at 18:00 to confirm if the home was secured before becoming vacant.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## Query
以下是过去 6 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## 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>

## Evidence Packet
{
  "sq_type": "SQ3",
  "event_count": 352,
  "salient_event_count": 60,
  "focus_event_count": 84,
  "room_activity": {
    "kitchen": 12,
    "living_room": 24,
    "master_bedroom": 12,
    "second_bedroom": 12,
    "bathroom": 12,
    "entrance": 12
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-20T18:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-20T18:00:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-20T18:00:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-20T18:00:00] bathroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-20T18:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-20T18:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-20T18:30:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-20T18:30

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## Query
以下是过去 6 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Total Household Vacancy (Potential Abandonment or System Failure)",
      "supported_by": ["suspicious_signals shows occupancy=0 for all rooms (living_room, master_bedroom, second_bedroom, bathroom, entrance) at multiple timestamps between 18:00 and 19:30"],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "anomaly",
      "description": "Occupancy Sensor Malfunction or Calibration Drift",
      "supported_by": ["The 'room_activity' count is significantly high (total 84 events across 5 rooms), suggesting active device interaction, yet every single occupancy sensor reports empty simultaneously. If people were present to generate activity, sensors should detect them.", "The uniformity of the failure (all sensors reporting 0 exactly on the hour) suggests a systematic issue rather than organic movement patterns."],
      "contradicted_by": []
    },
    {
      "id": "H3",
      "type": "normal",
      "description": "Scheduled Home Evacuation / Away Mode Activation",
      "supported_by": ["All occupancy sensors dropping to 0 indicates no one is physically inside.", "High room_activity could be attributed to automated smart-home routines running while the house is empty (e.g., cleaning robots, scheduled lighting changes, thermostat adjustments)."],
      "contradicted_by": ["The suddenness and perfect synchronization of the drop to 0 at 18:00 without a preceding 'Away Mode' trigger event in the provided snippet makes this less likely as the sole explanation compared to H1/H2."]
    }
  ],
  "most_concerning_signals": [
    "Simultaneous occupancy=0 across ALL monitored zones (Living Room, Bedrooms, Bathroom, Entrance) starting at 18:00.",
    "Discrepancy between high 'room_activi


The front door was unlocked by an automated process while the system registered occupancy inside the master bedroom just prior, suggesting an unauthorized individual entered after a resident or via a compromised auto-unlock sequence.

Explanation: At 22:30:15, the master bedroom window coverings were fully raised (100%), indicating someone was present and interacting with that room immediately before the incident.

Explanation: At 22:30:21, the front door lock state changed to '1' (unlocked) with the operation source explicitly logged as 'Auto', which is highly unusual for a standard entry event without user interaction.

Explanation: The timestamp of the door unlock (22:30:21) occurs exactly 6 seconds after the window covering adjustment, creating a tight temporal sequence inconsistent with normal casual entry or exit patterns.

Immediately contact security personnel or law enforcement to report a potential intrusion.

Review video surveillance footage for the time window 22:30:00 - 22:31:00 to identify the individual at the entrance and in the master bedroom.

Audit smart-home credentials and disable any active 'auto-unlock' features pending investigation.

[2026-06-19T11:56:25] entrance_occupancy | OccupancySensing.Occupancy = 1

High frequency of entrance/occupancy toggles between 12:00 and 12:18 without corresponding mass movement events in other rooms could indicate loitering or repeated failed entry attempts, though less severe than H1.

Check if the 'master_bedroom_window' closing event is physically linked to the 'front_door_lock' unlock via user ID or geofence data.

Verify if the 'front_door_lock' unlock at 22:30:21 was authorized (e.g., key fob vs. keypad code vs. physical key).

Cross-reference camera feeds (if available) for the time window 22:30:10 - 22:30:30 to confirm who entered the house.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## Query
以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## 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>

## Evidence Packet
{
  "sq_type": "SQ3",
  "event_count": 1025,
  "salient_event_count": 60,
  "focus_event_count": 109,
  "room_activity": {
    "kitchen": 22,
    "entrance": 31,
    "master_bedroom": 24,
    "living_room": 24,
    "second_bedroom": 4,
    "bathroom": 4
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-19T16:16:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-19T17:57:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
    "[2026-06-19T22:30:21] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
    "[2026-06-19T16:16:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-19T17:57:00] front_door_lock | DoorLock.LockState = 2",
    "[2026-06-19T22:30:15] master_bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
    "[2026-06-19T22:30:21]

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## Query
以下是过去 12 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Potential unauthorized entry or 'tailgating' event: The front door was manually unlocked at 22:30:21, immediately followed by the master bedroom window being fully closed (100%) within 6 seconds. This sequence suggests someone entered via the door and immediately secured a window in the adjacent room, which is behaviorally inconsistent with normal residents leaving or entering casually.",
      "supported_by": [
        "[2026-06-19T22:30:21] front_door_lock | Event: LockOperation(LockOperationType=0, OperationSource=Auto)",
        "[2026-06-19T22:30:15] master_bedroom_window | WindowCovering.CurrentPositionLiftPercent100ths = 10000",
        "[2026-06-19T22:30:21] front_door_lock | DoorLock.LockState = 1"
      ],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "normal",
      "description": "Routine evening arrival home: Residents arrived home around 16:16 and again at 17:57, securing the door. The subsequent activity levels in living rooms and bedrooms suggest normal occupancy patterns later in the day.",
      "supported_by": [
        "[2026-06-19T16:16:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)",
        "[2026-06-19T17:57:00] front_door_lock | Event: LockOperation(LockOperationType=1, OperationSource=Manual)"
      ],
      "contradicted_by": []
    }
  ],
  "most_concerning_signals": [
    "Temporal proximity of Front Door Unlock (22:30:21) and Master Bedroom Window Closing (22:30:15) suggests rapid, purposeful action upon entry.",
    "High frequency of entrance/occupancy toggles between 12:00 and 12:18 without corresponding mass movement events in other rooms could indicate loitering or repeated failed entry attempts, th


The pattern of simultaneous zero occupancy is explained by normal household evacuation and scheduled cleaning mode, not sensor failure or intrusion.

Explanation: Occupancy sensors across all rooms consistently report '0' at precise intervals (every 30 mins) without any transition logs, which aligns with a house being completely empty rather than a sensor synchronization glitch.

Explanation: Temperature readings show a natural, gradual cooling trend over the 6-hour period (from 23°C to ~22.5°C), indicating the HVAC system is off and no heating/cooling events are occurring, consistent with an unoccupied home.

Explanation: The absence of any light, appliance, or door lock/unlock events during this window rules out active intrusions, cooking, or people moving through the house while sensors are stuck.

Continuous temperature decline from 23.21°C to 22.54°C over 6 hours indicates lack of human activity or climate control usage.

No timestamps exist for lights turning on, appliances running, or doors unlocking/locking between 17:00 and 22:00.

Verify that all occupants have safely exited the premises before midnight.

Confirm that the security system's 'Away Mode' was manually activated or triggered automatically at approximately 17:00.

[2026-06-13T18:00:00] master_bedroom_occupancy | OccupancySensing.Occupancy = 0

[2026-06-13T18:00:00] second_bedroom_occupancy | OccupancySensing.Occupancy = 0

[2026-06-13T18:00:00] kids_room_occupancy | OccupancySensing.Occupancy = 0

[2026-06-13T18:00:00] master_bathroom_occupancy | OccupancySensing.Occupancy = 0

[2026-06-13T18:00:00] entrance_occupancy | OccupancySensing.Occupancy = 0

[2026-06-13T18:30:00] living_room_occupancy | OccupancySensing.Occupancy = 0

high event count suggests some system activity might be occurring if this were true

Simultaneous zero occupancy across ALL rooms (Entrance through Master Bathroom) at t=18:00, 18:30, 19:00

Absence of any transition events (e.g., 'Occupancy changed from 1 to 0') indicating when people actually left

Perfect temporal correlation of negative states across independent devices

Door lock status history: Was the front door locked between 17:00 and 19:00?

Motion sensor debug flags: Check for 'battery_low', 'calibration_error', or 'signal_lost' flags on the sensor nodes.

Network connectivity logs: Verify MQTT/Wi-Fi packet loss rates for these specific devices during the 18:00-19:00 window.

Light/Appliance logs: Were any lights turned on or appliances started in any room during this period? (If yes, H1/H2 anomaly; If no, supports H3)

Sensor timestamp vs System clock: Check if device clocks drifted significantly before resetting to default values.

## Task
Analyze the following evidence packet for a smart-home anomaly query.

## Query
以下是过去 6 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## 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>

## Evidence Packet
{
  "sq_type": "SQ3",
  "event_count": 376,
  "salient_event_count": 60,
  "focus_event_count": 78,
  "room_activity": {
    "kitchen": 9,
    "living_room": 17,
    "dining_room": 9,
    "master_bedroom": 9,
    "second_bedroom": 9,
    "kids_room": 9,
    "master_bathroom": 8,
    "entrance": 8
  },
  "temperature_patterns": [],
  "suspicious_signals": [
    "[2026-06-13T18:00:00] living_room_occupancy | OccupancySensing.Occupancy = 0",
    "[2026-06-13T18:00:00] dining_room_occupancy | OccupancySensing.Occupancy = 0",
    "[20

## Task
Make the final anomaly decision from compressed evidence plus a focused raw-log excerpt.

## Query
以下是过去 6 小时的设备活动日志。请分析是否存在异常行为模式，并说明推理过程。

## Stage-1 Analysis
{
  "candidate_hypotheses": [
    {
      "id": "H1",
      "type": "anomaly",
      "description": "Simultaneous total house empty state (Ghost House) - All occupancy sensors across all rooms report '0' at the exact same minute intervals, suggesting either a complete evacuation or sensor synchronization failure.",
      "supported_by": ["suspicious_signals shows identical timestamps (18:00, 18:30, 19:00) with Occupancy=0 for every room listed (living_room, dining_room, bedrooms, bathrooms, entrance)", "event_count is high (376) while focus_event_count is relatively low (78), implying many events are mundane status reports rather than dynamic user interactions"],
      "contradicted_by": []
    },
    {
      "id": "H2",
      "type": "anomaly",
      "description": "Systematic Sensor Data Loss/Desynchronization - Sensors are reporting stale data or defaulting to 'empty' due to network issues, time drift, or firmware bugs, creating a false negative of an empty house.",
      "supported_by": ["The perfect alignment of zero readings across geographically dispersed sensors (kitchen vs master bedroom) at precise 30-minute intervals is statistically improbable for natural human movement patterns.", "Room activity counts are uniform (9-17 events) which often indicates periodic heartbeat pings rather than organic event bursts."],
      "contradicted_by": []
    },
    {
      "id": "H3",
      "type": "normal",
      "description": "Scheduled Full Evacuation and Cleaning Mode - The household has vacated the premises entirely for cleaning or work, and all doors/windows have been secured.",
      "supported_by": [],
      "contradicted_by": ["lack of specific door lock/unlock logs in the provided snippet to confirm exit sequence", "high event count suggests some system activity might be occurring if this were