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feat: Add macOS CoreWLAN WiFi sensing adapter and user guide
- Introduced ADR-025 documenting the implementation of a macOS CoreWLAN sensing adapter using a Swift helper binary and Rust integration. - Added a new user guide detailing installation, usage, and hardware setup for WiFi DensePose, including Docker and source build instructions. - Included sections on data sources, REST API reference, WebSocket streaming, and vital sign detection. - Documented hardware requirements and troubleshooting steps for various setups.
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‎README.md‎

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---
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## 📖 Documentation
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| Document | Description |
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|----------|-------------|
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| [User Guide](docs/user-guide.md) | Step-by-step guide: installation, first run, API usage, hardware setup, training |
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| [WiFi-Mat User Guide](docs/wifi-mat-user-guide.md) | Disaster response module: search & rescue, START triage |
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| [Build Guide](docs/build-guide.md) | Building from source (Rust and Python) |
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| [Architecture Decisions](docs/adr/) | 24 ADRs covering signal processing, training, hardware, security |
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---
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## 🚀 Key Features
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| | Feature | What It Means |
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</details>
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<details>
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<summary><strong>Rust Crates</strong> — Individual crates on crates.io</summary>
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The Rust workspace consists of 14 crates, all published to [crates.io](https://crates.io/):
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```bash
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# Add individual crates to your Cargo.toml
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cargo add wifi-densepose-core # Types, traits, errors
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cargo add wifi-densepose-signal # CSI signal processing (6 SOTA algorithms)
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cargo add wifi-densepose-nn # Neural inference (ONNX, PyTorch, Candle)
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cargo add wifi-densepose-vitals # Vital sign extraction (breathing + heart rate)
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cargo add wifi-densepose-mat # Disaster response (MAT survivor detection)
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cargo add wifi-densepose-hardware # ESP32, Intel 5300, Atheros sensors
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cargo add wifi-densepose-train # Training pipeline (MM-Fi dataset)
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cargo add wifi-densepose-wifiscan # Multi-BSSID WiFi scanning
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```
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| Crate | Description | RuVector | crates.io |
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|-------|-------------|----------|-----------|
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| [`wifi-densepose-core`](https://crates.io/crates/wifi-densepose-core) | Foundation types, traits, and utilities | -- | [![crates.io](https://img.shields.io/crates/v/wifi-densepose-core.svg)](https://crates.io/crates/wifi-densepose-core) |
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| [`wifi-densepose-signal`](https://crates.io/crates/wifi-densepose-signal) | SOTA CSI signal processing (SpotFi, FarSense, Widar 3.0) | `mincut`, `attn-mincut`, `attention`, `solver` | [![crates.io](https://img.shields.io/crates/v/wifi-densepose-signal.svg)](https://crates.io/crates/wifi-densepose-signal) |
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| [`wifi-densepose-nn`](https://crates.io/crates/wifi-densepose-nn) | Multi-backend inference (ONNX, PyTorch, Candle) | -- | [![crates.io](https://img.shields.io/crates/v/wifi-densepose-nn.svg)](https://crates.io/crates/wifi-densepose-nn) |
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| [`wifi-densepose-train`](https://crates.io/crates/wifi-densepose-train) | Training pipeline with MM-Fi dataset (NeurIPS 2023) | **All 5** | [![crates.io](https://img.shields.io/crates/v/wifi-densepose-train.svg)](https://crates.io/crates/wifi-densepose-train) |
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| [`wifi-densepose-mat`](https://crates.io/crates/wifi-densepose-mat) | Mass Casualty Assessment Tool (disaster survivor detection) | `solver`, `temporal-tensor` | [![crates.io](https://img.shields.io/crates/v/wifi-densepose-mat.svg)](https://crates.io/crates/wifi-densepose-mat) |
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| [`wifi-densepose-vitals`](https://crates.io/crates/wifi-densepose-vitals) | Vital signs: breathing (6-30 BPM), heart rate (40-120 BPM) | -- | [![crates.io](https://img.shields.io/crates/v/wifi-densepose-vitals.svg)](https://crates.io/crates/wifi-densepose-vitals) |
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| [`wifi-densepose-hardware`](https://crates.io/crates/wifi-densepose-hardware) | ESP32, Intel 5300, Atheros CSI sensor interfaces | -- | [![crates.io](https://img.shields.io/crates/v/wifi-densepose-hardware.svg)](https://crates.io/crates/wifi-densepose-hardware) |
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| [`wifi-densepose-wifiscan`](https://crates.io/crates/wifi-densepose-wifiscan) | Multi-BSSID WiFi scanning (Windows-enhanced) | -- | [![crates.io](https://img.shields.io/crates/v/wifi-densepose-wifiscan.svg)](https://crates.io/crates/wifi-densepose-wifiscan) |
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| [`wifi-densepose-wasm`](https://crates.io/crates/wifi-densepose-wasm) | WebAssembly bindings for browser deployment | -- | [![crates.io](https://img.shields.io/crates/v/wifi-densepose-wasm.svg)](https://crates.io/crates/wifi-densepose-wasm) |
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| [`wifi-densepose-sensing-server`](https://crates.io/crates/wifi-densepose-sensing-server) | Axum server: UDP ingestion, WebSocket broadcast | -- | [![crates.io](https://img.shields.io/crates/v/wifi-densepose-sensing-server.svg)](https://crates.io/crates/wifi-densepose-sensing-server) |
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| [`wifi-densepose-cli`](https://crates.io/crates/wifi-densepose-cli) | Command-line tool for MAT disaster scanning | -- | [![crates.io](https://img.shields.io/crates/v/wifi-densepose-cli.svg)](https://crates.io/crates/wifi-densepose-cli) |
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| [`wifi-densepose-api`](https://crates.io/crates/wifi-densepose-api) | REST + WebSocket API layer | -- | [![crates.io](https://img.shields.io/crates/v/wifi-densepose-api.svg)](https://crates.io/crates/wifi-densepose-api) |
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| [`wifi-densepose-config`](https://crates.io/crates/wifi-densepose-config) | Configuration management | -- | [![crates.io](https://img.shields.io/crates/v/wifi-densepose-config.svg)](https://crates.io/crates/wifi-densepose-config) |
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| [`wifi-densepose-db`](https://crates.io/crates/wifi-densepose-db) | Database persistence (PostgreSQL, SQLite, Redis) | -- | [![crates.io](https://img.shields.io/crates/v/wifi-densepose-db.svg)](https://crates.io/crates/wifi-densepose-db) |
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All crates integrate with [RuVector v2.0.4](https://github.com/ruvnet/ruvector) for graph algorithms and neural network optimization.
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</details>
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## 🚀 Quick Start
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| **Confidence** | 0.0-1.0 per sign | Spectral coherence + signal quality |
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```bash
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./target/release/sensing-server --source simulate --ui-path ../../ui
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curl http://localhost:8080/api/v1/vital-signs
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./target/release/sensing-server --source simulate --http-port 3000 --ws-port 3001 --ui-path ../../ui
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curl http://localhost:3000/api/v1/vital-signs
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See [ADR-021](docs/adr/ADR-021-vital-sign-detection-rvdna-pipeline.md).
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POST /api/v1/model/sona/activate # Activate SONA profile
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WebSocket: `ws://localhost:8765/ws/sensing` (real-time sensing + vital signs)
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WebSocket: `ws://localhost:3001/ws/sensing` (real-time sensing + vital signs)
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> Default ports: HTTP 8080, WS 8765. Docker images remap to 3000/3001 via `--http-port` / `--ws-port`.
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> Default ports (Docker): HTTP 3000, WS 3001. Binary defaults: HTTP 8080, WS 8765. Override with `--http-port` / `--ws-port`.
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</details>
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