- Fix TestAnalyticsHandler_ErrorHandling to use proper in-memory database
instead of nil database which caused nil pointer dereference
- Update handleGetCorridors to return corridors wrapped in {corridors: [...]}
for consistency with frontend expectations from crowdflow.js
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Fix Viz3D exports to include flow visualization functions
- Export setFlowLayerVisible, setDwellLayerVisible, setCorridorLayerVisible
- Export setFlowTimeFilter, setFlowData, setDwellData, setCorridorData
- Remove duplicate setDwellLayerVisible function definition
This completes the crowd flow visualization feature that was
already implemented in the backend (flow.go) and frontend
(crowdflow.js, viz3d.js) but had missing exports in the Viz3D module.
Implements comprehensive anomaly detection system that learns normal household
patterns over 7+ days and alerts on deviations. Transforms spaxel into a basic
home security system.
Core features:
- Normal behaviour model: statistical tracking of occupancy patterns per
(hour_of_week, zone_id) slot with expected occupancy, typical person count,
and typical BLE devices
- Four anomaly types: unusual hour presence, unknown BLE device, motion during
away mode, unusual dwell duration
- Security mode: lowered thresholds, immediate alerts, bypasses quiet hours
- Auto-away/disarm: automatic security mode activation based on BLE device
presence (15min absence, auto-disarm on device return)
- Alert chain: staged notifications (dashboard → push → webhook → escalation)
- WebSocket integration: real-time anomaly broadcasts to dashboard
API endpoints:
- GET/POST /api/mode: system mode control (home/away/sleep)
- GET /api/security/status: current security state
Tests cover all anomaly types, alert chain timing, security mode thresholds,
auto-away/disarm, acknowledgement flow, and cooldown deduplication.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Added tests for:
- Auto-away activation when all registered BLE devices absent for 15+ minutes
- Auto-disarm triggering when registered BLE device returns with strong RSSI
- Manual override pausing auto-away detection
- System mode GET/PUT REST API endpoints
- Edge cases: no registered devices, weak BLE signals, unregistered devices
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add anomaly.css and sleep.css to dashboard includes
- Add sleep.js for sleep quality monitoring
- Implement analytics API handler (flow, dwell, corridors)
- Add tracks API and tests for time-based data queries
- Add sleep monitor tests
- AnomalyDetector initialized and running in main()
- Anomaly events broadcast via WebSocket to dashboard
- Security mode arm/disarm persists across restarts (learning_state table)
- Learning progress tracking and display
- Alert banner with acknowledge functionality
- All API endpoints wired: /api/anomalies, /api/security/*, /api/analytics/*
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Confirm AnomalyDetector initialization in main(), wire anomaly event
broadcasts to dashboard WS as alert messages, and verify all security
mode endpoints (arm/disarm/status) return correct JSON with persistent
state across restarts.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- AnomalyDetector initialized and running in main() with periodic updates
- Anomaly events pushed to dashboard WS feed as 'alert' messages
- GET /api/anomalies?since=24h lists recent anomaly events
- POST /api/security/arm + /api/security/disarm endpoints
- GET /api/security/status returns armed, learning_until, anomaly_count_24h
- Arm/disarm state persists via learning_state SQLite table
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add missing CountAnomaliesSince method to mockDetectorProvider
in security_test.go to satisfy the DetectorProvider interface
- Fix variable shadowing bug in anomaly.go QueryAnomalyEvents
where incomplete rename from 'events' to 'result' caused
append(events, &e) to reference the package instead of the slice
All security mode endpoints verified:
- GET /api/anomalies?since=24h — lists recent anomaly events
- POST /api/security/arm + /api/security/disarm — arm/disarm
- GET /api/security/status — {armed, learning_until, anomaly_count_24h}
- Anomaly events push to dashboard WS as 'alert' messages
- Arm/disarm state persists across restarts via learning_state table
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add complete health check implementation for Docker HEALTHCHECK and
Traefik health routing with:
Response fields:
- status: "ok" or "degraded"
- uptime_s: seconds since mothership boot
- version: mothership version string
- nodes_online: count of connected nodes
- db: "ok" or "failing" (SELECT 1 with 100ms timeout)
- load_level: 0-3 from load shedding state
- reason: human-readable explanation (only when degraded)
HTTP status codes:
- 200 for healthy (status="ok")
- 503 for degraded (status="degraded")
Degraded conditions:
- Database unreachable
- Load level 3 sustained for >60 seconds
- No nodes connected after 5 minutes uptime
Docker HEALTHCHECK updated to verify status="ok" response.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add GetArmedAt() method to persist armed timestamp across restarts
- Add blob appear/disappear callbacks to tracker for security events
- Add security handler for arm/disarm API endpoints
- Update /api/security endpoint to return armed_at timestamp
- Add tracker tests for blob lifecycle callbacks
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
All 5 new message types (event, alert, ble_scan, trigger_state,
system_health) were already implemented in hub.go with broadcast methods,
called from main.go/ingestion/volume_triggers/events, and handled in
app.js. Also includes security mode persistence from anomaly DB and
OpenAPI docs for triggers endpoints.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Change testAlertHandler.mu from sync.Mutex to sync.RWMutex to match
RLock/RUnlock calls in alertCount/webhookCount/escalationCount
- Add proper mutex locking in SendAlert/SendWebhook/SendEscalation
- Fix TestAnomaly_UnknownBLEDevice: use security mode so score (0.8)
exceeds security threshold (0.4) instead of normal threshold (0.6)
- Fix TestAnomaly_UnusualDwell: use security mode for threshold check
- Fix TestAnomaly_SecurityModeThreshold: remove normal mode call that
creates cooldown and prevents security mode detection
- Fix TestAnomaly_AlertChainNormalMode/SecurityMode: add waitForGoroutines()
before checking alerts sent via goroutines
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Implement a complete self-improving localization system that uses BLE
RSSI triangulation as ground truth to learn per-link, per-zone weights
for the Fresnel zone fusion engine.
Key components:
- Ground truth sample collection with confidence > 0.7 and distance < 0.5m gates
- Spatial weight learner using online SGD with L2 regularization
- Validation gate that rejects updates without 5% improvement on holdout set
- Bilinear interpolation for smooth weight transitions between zones
- SQLite persistence for weights with 10,000 sample cap per person
- Position accuracy trend visualization in dashboard Accuracy panel
Backend (mothership/internal/localization/):
- groundtruth.go: BLE trilateration provider with Gauss-Newton optimization
- groundtruth_store.go: SQLite storage with weekly accuracy rollups
- spatial_weights.go: SpatialWeightLearner with SGD, validation, interpolation
- weightlearner.go: WeightLearner with error history tracking
- weightstore.go: Weight persistence to SQLite
Frontend (dashboard/js/accuracy.js):
- fetchPositionAccuracy/fetchPositionHistory functions
- drawPositionSparkline for weekly median error trend
- Position accuracy section with median error, trend indicator, sample count
Tests cover:
- Sample collection gates (confidence/distance thresholds)
- SGD weight updates after 100 samples
- Validation gate rejection of adversarial samples
- Bilinear interpolation smoothness
- SQLite sample cap enforcement
- Weight persistence across restarts
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add trajectory accumulation, directional flow maps, and dwell time
hotspot visualization for occupancy pattern analysis.
Backend:
- FlowAccumulator records trajectory segments and dwell time in SQLite
- REST endpoints for flow map, dwell heatmap, and detected corridors
- Bresenham rasterization for flow vector aggregation
- Connected component analysis for corridor detection
Frontend:
- Pattern controls in dashboard sidebar (flow, dwell, corridors toggles)
- Time filter dropdown (7d, 30d, all time)
- 3D visualization with ArrowHelper for flow, PlaneGeometry for heatmaps
- Pulsating animation on flow arrows
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
