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Add environment-tuned activity classification that learns from labeled ESP32 CSI recordings, replacing brittle static thresholds. - Adaptive classifier: 15-feature logistic regression trained from JSONL recordings (variance, motion band, subcarrier stats: skew, kurtosis, entropy, IQR). Trains in <1s, persists as JSON, auto-loads on restart. - Three-stage signal smoothing: adaptive baseline subtraction (α=0.003), EMA + trimmed-mean median filter (21-frame window), hysteresis debounce (4 frames). Motion classification now stable across seconds, not frames. - Vital signs stabilization: outlier rejection (±8 BPM HR, ±2 BPM BR), trimmed mean, dead-band (±2 BPM HR), EMA α=0.02. HR holds steady for 10+ seconds instead of jumping 50 BPM every frame. - Observatory auto-detect: always probes /health on startup, connects WebSocket to live ESP32 data automatically. - New API endpoints: POST /api/v1/adaptive/train, GET /adaptive/status, POST /adaptive/unload for runtime model management. - Updated user guide with Observatory, adaptive classifier tutorial, signal smoothing docs, and new troubleshooting entries. |
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| adr | ||
| ddd | ||
| edge-modules | ||
| research | ||
| build-guide.md | ||
| security-audit-wasm-edge-vendor.md | ||
| user-guide.md | ||
| wifi-mat-user-guide.md | ||
| WITNESS-LOG-028.md | ||