Ruview/ui
rUv 3733e54aef
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feat: cross-node fusion + DynamicMinCut + RSSI tracking (v0.5.3)
* feat(server): cross-node RSSI-weighted feature fusion + benchmarks

Adds fuse_multi_node_features() that combines CSI features across all
active ESP32 nodes using RSSI-based weighting (closer node = higher weight).

Benchmark results (2 ESP32 nodes, 30s, ~1500 frames):

  Metric               | Baseline | Fusion  | Improvement
  ---------------------|----------|---------|------------
  Variance mean        |    109.4 |    77.6 | -29% noise
  Variance std         |    154.1 |   105.4 | -32% stability
  Confidence           |    0.643 |   0.686 | +7%
  Keypoint spread std  |      4.5 |     1.3 | -72% jitter
  Presence ratio       |   93.4%  |  94.6%  | +1.3pp

Person count still fluctuates near threshold — tracked as known issue.

Verified on real hardware: COM6 (node 1) + COM9 (node 2) on ruv.net.

Co-Authored-By: claude-flow <ruv@ruv.net>

* fix(ui): add client-side lerp smoothing to pose renderer

Keypoints now interpolate between frames (alpha=0.25) instead of
jumping directly to new positions. This eliminates visual jitter
that persists even with server-side EMA smoothing, because the
renderer was drawing every WebSocket frame at full rate.

Applied to skeleton, keypoints, and dense body rendering paths.

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat: DynamicMinCut person separation + UI lerp smoothing

- Added ruvector-mincut dependency to sensing server
- Replaced variance-based person scoring with actual graph min-cut on
  subcarrier temporal correlation matrix (Pearson correlation edges,
  DynamicMinCut exact max-flow)
- Recalibrated feature scaling for real ESP32 data ranges
- UI: client-side lerp interpolation (alpha=0.25) on keypoint positions
- Dampened procedural animation (noise, stride, extremity jitter)
- Person count thresholds retuned for mincut ratio

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs: update CHANGELOG with v0.5.1-v0.5.3 releases

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-03-30 21:55:44 -04:00
..
components fix: WebSocket race condition, data source indicators, auto-start pose detection (#96) 2026-03-02 13:47:49 -05:00
config fix(ui): WebSocket protocol matches page protocol, not hostname (#272) 2026-03-16 11:35:11 -04:00
mobile fix: complete sensing server API, WebSocket connectivity, and mobile tests (#125) 2026-03-03 13:27:03 -05:00
observatory fix: brighten ambient light color and increase multiplier for room brightness slider 2026-03-05 10:56:37 -05:00
pose-fusion brand: rename DensePose to RuView in pose-fusion UI 2026-03-12 21:55:09 -04:00
services fix: complete sensing server API, WebSocket connectivity, and mobile tests (#125) 2026-03-03 13:27:03 -05:00
tests updates 2025-06-07 13:55:28 +00:00
utils feat: cross-node fusion + DynamicMinCut + RSSI tracking (v0.5.3) 2026-03-30 21:55:44 -04:00
app.js fix: complete sensing server API, WebSocket connectivity, and mobile tests (#125) 2026-03-03 13:27:03 -05:00
index.html feat(demo): wire all 6 RuVector WASM attention mechanisms into pose fusion 2026-03-12 20:59:57 -04:00
observatory.html docs: update README with ADR-045–048, Observatory, adaptive classifier, AMOLED display 2026-03-05 10:20:48 -05:00
pose-fusion.html brand: rename DensePose to RuView in pose-fusion UI 2026-03-12 21:55:09 -04:00
README.md docs: update UI README with sensing tab, Rust backend, data sources 2026-03-02 10:57:56 -05:00
start-ui.sh docs: Revamp README and UI documentation; enhance CLI usage instructions and API configuration details 2025-06-07 13:40:52 +00:00
style.css fix: WebSocket race condition, data source indicators, auto-start pose detection (#96) 2026-03-02 13:47:49 -05:00
TEST_REPORT.md I've successfully completed a full review of the WiFi-DensePose system, testing all functionality across every major 2025-06-09 17:13:35 +00:00
viz.html feat: Add Three.js visualization entry point and data processor 2026-02-28 06:29:28 +00:00

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 health
  • GET /api/v1/sensing/latest — latest sensing features
  • GET /api/v1/vital-signs — vital sign estimates (HR/RR)
  • GET /api/v1/model/info — RVF model container info
  • WS /ws/sensing — real-time sensing data stream
  • WS /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

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 rust-port/wifi-densepose-rs
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

Open http://localhost: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.