- Docker default changed from --source simulated to --source auto
(auto-detects ESP32 on UDP 5005, falls back to simulation)
- Pose derivation now driven by real sensing features: motion_band_power,
breathing_band_power, variance, dominant_freq_hz, change_points
- Temporal feature extraction: 100-frame circular buffer, Goertzel
breathing rate estimation (0.1-0.5 Hz), frame-to-frame L2 motion
detection, SNR-based signal quality metric
- Signal field driven by subcarrier variance spatial mapping instead
of fixed animation circle
- UI data source indicators: LIVE/RECONNECTING/SIMULATED banner on
sensing tab, estimation mode badge on live demo tab
- Setup guide panel explaining ESP32 count requirements for each
capability level (1x: presence, 3x: localization, 4x+: full pose)
- Tick rate improved from 500ms to 100ms (2fps to 10fps)
- Fixed Option<f64> division bug from PR #83
- ADR-035 documents all decisions
Closes#86
Co-Authored-By: claude-flow <ruv@ruv.net>
- Add Python WebSocket sensing server (ws_server.py) with ESP32 UDP CSI
and Windows RSSI auto-detect collectors on port 8765
- Add Three.js Gaussian splat renderer with custom GLSL shaders for
real-time WiFi signal field visualization (blue→green→red gradient)
- Add SensingTab component with RSSI sparkline, feature meters, and
motion classification badge
- Add sensing.service.js WebSocket client with reconnect and simulation fallback
- Implement sensing-only mode: suppress all DensePose API calls when
FastAPI backend (port 8000) is not running, clean console output
- ADR-019: Document sensing-only UI architecture and data flow
- ADR-020: Migrate AI/model inference to Rust with RuVector ONNX Runtime,
replacing ~2.7GB Python stack with ~50MB static binary
- Add ruvnet/ruvector as upstream remote for RuVector crate ecosystem
Co-Authored-By: claude-flow <ruv@ruv.net>
- Created comprehensive API reference documentation covering authentication, request/response formats, error handling, and various API endpoints for pose estimation, system management, health checks, and WebSocket interactions.
- Developed a detailed deployment guide outlining prerequisites, Docker and Kubernetes deployment steps, cloud deployment options for AWS, GCP, and Azure, and configuration for production environments.
ruv