- 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>
Add viz.html as the main entry point that loads Three.js from CDN and
orchestrates all visualization components (scene, body model, signal
viz, environment, HUD). Add data-processor.js that transforms API
WebSocket messages into geometry updates and provides demo mode with
pre-recorded pose cycling when the server is unavailable.
https://claude.ai/code/session_01Ki7pvEZtJDvqJkmyn6B714
Add prominent hardware requirements table at top of README documenting
the three paths to real CSI data (ESP32, research NIC, commodity WiFi).
Include remaining Three.js visualization components for dashboard.
https://claude.ai/code/session_01Ki7pvEZtJDvqJkmyn6B714
- .github/workflows/verify-pipeline.yml: CI that verifies pipeline
determinism and checks for np.random in production code
- ui/components/body-model.js: Three.js 3D human body model with
24 DensePose body parts mapped to 3D geometry
- v1/requirements-lock.txt: Minimal pinned dependencies for verification
- v1/src/api/dependencies.py: Fix mock auth returns with proper errors
- v1/src/core/router_interface.py: Additional mock mode cleanup
- v1/src/services/pose_service.py: Further mock elimination in service
https://claude.ai/code/session_01Ki7pvEZtJDvqJkmyn6B714
Commodity Sensing Module (ADR-013):
- sensing/rssi_collector.py: Real Linux WiFi RSSI collection from
/proc/net/wireless and iw commands, with SimulatedCollector for testing
- sensing/feature_extractor.py: FFT-based spectral analysis, CUSUM
change-point detection, breathing/motion band power extraction
- sensing/classifier.py: Rule-based presence/motion classification
with confidence scoring and multi-receiver agreement
- sensing/backend.py: Common SensingBackend protocol with honest
capability reporting (PRESENCE + MOTION only for commodity)
Proof of Reality Bundle (ADR-011):
- data/proof/generate_reference_signal.py: Deterministic synthetic CSI
with known breathing (0.3 Hz) and walking (1.2 Hz) signals
- data/proof/sample_csi_data.json: Generated reference signal
- data/proof/verify.py: One-command pipeline verification with SHA-256
- data/proof/expected_features.sha256: Expected output hash
Three.js Visualization:
- ui/components/scene.js: 3D scene setup with OrbitControls
Mock Isolation:
- testing/mock_pose_generator.py: Mock pose generation moved out of
production pose_service.py
- services/pose_service.py: Cleaned mock paths
https://claude.ai/code/session_01Ki7pvEZtJDvqJkmyn6B714
- 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.
