Three loose ends from the browser sign-in work. --- 1. The last mile: a button --- The server endpoints existed but nothing in ui/ linked to them, so the feature was unreachable. QuickSettings gains a "Cognitum Account" panel that renders from `GET /oauth/status` and offers Sign in / Sign out. `/oauth/status` is a new endpoint and is deliberately UNGATED — a signed-OUT browser cannot ask a gated API whether sign-in is available. It returns only capability flags and, when a session exists, who it belongs to. Never a credential. The panel distinguishes four states rather than showing a button that might 404: signed in; sign-in available; auth on but OAuth off (points at the existing static-token panel); no auth required. A 404 from /oauth/status means a server predating this work and says so plainly. Sign-in is a full-page navigation, not fetch(): the server replies 302 and the browser must follow it carrying the transaction cookie. An XHR would follow the redirect invisibly and land nowhere. --- 2. RUVIEW_SESSION_SECRET no longer required --- Previously `/oauth/start` returned 503 unless an operator invented a secret — a footgun, since they set RUVIEW_OAUTH_ISSUER, expect sign-in, and get a 503 naming an env var they have never heard of. Now resolved in order: env var, then `<data_dir>/session-secret`, then generate one and persist it 0600 (temp file, chmod before rename — the discipline used for the CLI's credentials). Persisted rather than in-memory so a restart does not silently sign everyone out. The env var still wins, which is what a multi-instance deployment needs: several servers must share a secret or a session issued by one is rejected by the next. If the file cannot be written we log the reason and continue with an in-memory secret rather than refusing sign-in outright. Verified with NO configuration at all: secret generated, file mode 0600, /oauth/start returns 302, /oauth/status reports browser_signin: true. --- 3. The JavaScript is now executed by tests --- `ui/services/ws-ticket.test.mjs`, 9 tests, node:test built-in — no new dependency and no package.json needed. Run: `node --test ui/services/`. Covers: no token means no fetch and an unchanged URL; the bearer reaches the Authorization header and NEVER the URL; `?` vs `&` when a query already exists; ticket URL-encoding; 404 treated as a pre-ADR-272 server (the property that lets one UI work against old and new servers, and therefore lets the legacy escape hatch be removed later); 503 and network failure swallowed rather than breaking the connect path; and that a fresh ticket is minted per call, since tickets are single-use and caching one fails on the second reconnect. STATED PRECISELY, because the distinction matters: this EXECUTES the module in Node with stubbed fetch/localStorage. It is more than the `node --check` it replaces and less than a browser — no real WebSocket upgrade, no real cookies, no page wiring. "The UI JavaScript has never been run" is no longer true of this module. "Browser-tested" still is not. Tests: 547 sensing-server lib, 5 wiring integration, 87 ruview-auth, 9 JS. Co-Authored-By: Ruflo & AQE
WiFi DensePose UI
A modular, modern web interface for the WiFi DensePose human tracking system. Provides real-time monitoring, WiFi sensing visualization, and pose estimation from CSI (Channel State Information).
Architecture
The UI follows a modular architecture with clear separation of concerns:
ui/
├── app.js # Main application entry point
├── index.html # HTML shell with tab structure
├── style.css # Complete CSS design system
├── config/
│ └── api.config.js # API endpoints and configuration
├── services/
│ ├── api.service.js # HTTP API client
│ ├── websocket.service.js # WebSocket connection manager
│ ├── websocket-client.js # Low-level WebSocket client
│ ├── pose.service.js # Pose estimation API wrapper
│ ├── sensing.service.js # WiFi sensing data service (live + simulation fallback)
│ ├── health.service.js # Health monitoring API wrapper
│ ├── stream.service.js # Streaming API wrapper
│ └── data-processor.js # Signal data processing utilities
├── components/
│ ├── TabManager.js # Tab navigation component
│ ├── DashboardTab.js # Dashboard with live system metrics
│ ├── SensingTab.js # WiFi sensing visualization (3D signal field, metrics)
│ ├── LiveDemoTab.js # Live pose detection with setup guide
│ ├── HardwareTab.js # Hardware configuration
│ ├── SettingsPanel.js # Settings panel
│ ├── PoseDetectionCanvas.js # Canvas-based pose skeleton renderer
│ ├── gaussian-splats.js # 3D Gaussian splat signal field renderer (Three.js)
│ ├── body-model.js # 3D body model
│ ├── scene.js # Three.js scene management
│ ├── signal-viz.js # Signal visualization utilities
│ ├── environment.js # Environment/room visualization
│ └── dashboard-hud.js # Dashboard heads-up display
├── utils/
│ ├── backend-detector.js # Auto-detect backend availability
│ ├── mock-server.js # Mock server for testing
│ └── pose-renderer.js # Pose rendering utilities
└── tests/
├── test-runner.html # Test runner UI
├── test-runner.js # Test framework and cases
└── integration-test.html # Integration testing page
Features
WiFi Sensing Tab
- 3D Gaussian-splat signal field visualization (Three.js)
- Real-time RSSI, variance, motion band, breathing band metrics
- Presence/motion classification with confidence scores
- Data source banner: green "LIVE - ESP32", yellow "RECONNECTING...", or red "SIMULATED DATA"
- Sparkline RSSI history graph
- "About This Data" card explaining CSI capabilities per sensor count
Live Demo Tab
- WebSocket-based real-time pose skeleton rendering
- Estimation Mode badge: green "Signal-Derived" or blue "Model Inference"
- Setup Guide panel showing what each ESP32 count provides:
- 1 ESP32: presence, breathing, gross motion
- 2-3 ESP32s: body localization, motion direction
- 4+ ESP32s + trained model: individual limb tracking, full pose
- Debug mode with log export
- Zone selection and force-reconnect controls
- Performance metrics sidebar (frames, uptime, errors)
Dashboard
- Live system health monitoring
- Real-time pose detection statistics
- Zone occupancy tracking
- System metrics (CPU, memory, disk)
- API status indicators
Hardware Configuration
- Interactive antenna array visualization
- Real-time CSI data display
- Configuration panels
- Hardware status monitoring
Data Sources
The sensing service (sensing.service.js) supports three connection states:
| State | Banner Color | Description |
|---|---|---|
| LIVE - ESP32 | Green | Connected to the Rust sensing server receiving real CSI data |
| RECONNECTING | Yellow (pulsing) | WebSocket disconnected, retrying (up to 20 attempts) |
| SIMULATED DATA | Red | Fallback to client-side simulation after 5+ failed reconnects |
Simulated frames include a _simulated: true marker so code can detect synthetic data.
Backends
Rust Sensing Server (primary)
The Rust-based wifi-densepose-sensing-server serves the UI and provides:
GET /health— server healthGET /api/v1/sensing/latest— latest sensing featuresGET /api/v1/vital-signs— vital sign estimates (HR/RR)GET /api/v1/model/info— RVF model container infoWS /ws/sensing— real-time sensing data streamWS /api/v1/stream/pose— real-time pose keypoint stream
Python FastAPI (legacy)
The original Python backend on port 8000 is still supported. The UI auto-detects which backend is available via backend-detector.js.
Quick Start
With Docker (recommended)
cd docker/
# Default: auto-detects ESP32 on UDP 5005, falls back to simulation
docker-compose up
# Force real ESP32 data
CSI_SOURCE=esp32 docker-compose up
# Force simulation (no hardware needed)
CSI_SOURCE=simulated docker-compose up
Open http://localhost:3000/ui/index.html
With local Rust binary
cd v2
cargo build -p wifi-densepose-sensing-server --no-default-features
# Run with simulated data
../../target/debug/sensing-server --source simulated --tick-ms 100 --ui-path ../../ui --http-port 3000
# Run with real ESP32
../../target/debug/sensing-server --source esp32 --tick-ms 100 --ui-path ../../ui --http-port 3000
Open http://localhost:3000/ui/index.html
With Python HTTP server (legacy)
# Start FastAPI backend on port 8000
wifi-densepose start
# Serve the UI on port 3000
cd ui/
python -m http.server 3000
Pose Estimation Modes
| Mode | Badge | Requirements | Accuracy |
|---|---|---|---|
| Signal-Derived | Green | 1+ ESP32, no model needed | Presence, breathing, gross motion |
| Model Inference | Blue | 4+ ESP32s + trained .rvf model |
Full 17-keypoint COCO pose |
To use model inference, start the server with a trained model:
sensing-server --source esp32 --model path/to/model.rvf --ui-path ./ui
Configuration
API Configuration
Edit config/api.config.js:
export const API_CONFIG = {
BASE_URL: window.location.origin,
API_VERSION: '/api/v1',
WS_CONFIG: {
RECONNECT_DELAY: 5000,
MAX_RECONNECT_ATTEMPTS: 20,
PING_INTERVAL: 30000
}
};
Testing
Open tests/test-runner.html to run the test suite:
cd ui/
python -m http.server 3000
# Open http://localhost:3000/tests/test-runner.html
Test categories: API configuration, API service, WebSocket, pose service, health service, UI components, integration.
Styling
Uses a CSS design system with custom properties, dark/light mode, responsive layout, and component-based styling. Key variables in :root of style.css.
License
Part of the WiFi-DensePose system. See the main project LICENSE file.