wifi-densepose/v2/crates/wifi-densepose-sensing-server
ruv 07d22247b5 feat(adr-115): P2 — HA discovery emitter + privacy filter + config (27 tests)
Implements ADR-115 §3.1–§3.4 (entity mapping + topic structure + discovery
payloads + device grouping) and §3.10 (privacy-mode contract) as the
`mqtt` submodule of `wifi-densepose-sensing-server`.

Modules:
- `mqtt::mod`        — module roots, stable origin/manufacturer/url constants
- `mqtt::config`     — `MqttConfig` built from `cli::Args`, TLS resolution
                        (off/system-trust/pinned-CA/mTLS), `--mqtt-password-env`
                        resolution, pre-flight `validate()` with fatal/advisory
                        distinction (PlaintextOnPublicHost is non-fatal in
                        v0.7.0, hard-fail in v0.8.0 per §3.9 / §9.5).
- `mqtt::discovery`  — `DiscoveryBuilder`, `EntityKind` (all 11 raw +
                        10 semantic entities), serialisable `DiscoveryConfig`
                        with `skip_serializing_if = "Option::is_none"` so
                        retained payloads stay compact. Topic structure
                        matches HA's `<prefix>/<component>/<object>/<entity>/
                        {config,state,availability}` convention. `enabled_
                        entities(privacy, publish_pose, no_semantic)` is the
                        single source of truth for which entities the
                        publisher will emit.
- `mqtt::privacy`    — `decide(entity, privacy_mode)` returns
                        `Suppress` for biometrics (HR/BR/pose) and
                        `Publish` for everything else, including all
                        semantic primitives (per §3.12.3 — semantic
                        primitives are inferred states, not biometric
                        values, and remain safe to publish in privacy mode).

Tests (27 total, all passing under `--no-default-features`):
- 11 config tests: defaults, TLS port bump, explicit port override, mTLS
  triplet detection, validate rejects empty host / zero port / NaN /
  negative rate, plaintext-public advisory, password env resolution.
- 9 discovery tests: payload shape (presence, heart rate, fall event,
  distress problem-class), default vs privacy-mode entity sets,
  --no-semantic filtering, component routing, null-field omission,
  availability/state topic pairing, namespaced unique_id.
- 4 privacy tests: privacy-off publishes all, privacy-on suppresses
  exactly the biometric set, keeps non-biometric signals, keeps every
  semantic primitive.

Connect/publish lifecycle (uses `rumqttc`) gated behind `--features mqtt`;
the `publisher` and `state` submodules land in P3 next iteration.

Refs #776.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-05-23 13:50:33 -04:00
..
src feat(adr-115): P2 — HA discovery emitter + privacy filter + config (27 tests) 2026-05-23 13:50:33 -04:00
tests fix(security): audit — fix RUSTSEC vulns, clippy warnings, dead code (#769) 2026-05-23 05:36:13 -04:00
Cargo.toml feat(adr-115): P1 — Cargo features + CLI flags for MQTT/Matter/Semantic 2026-05-23 13:43:02 -04:00
README.md chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 2026-04-25 21:28:13 -04:00

README.md

wifi-densepose-sensing-server

Crates.io Documentation License

Lightweight Axum server for real-time WiFi sensing with RuVector signal processing.

Overview

wifi-densepose-sensing-server is the operational backend for WiFi-DensePose. It receives raw CSI frames from ESP32 hardware over UDP, runs them through the RuVector-powered signal processing pipeline, and broadcasts processed sensing updates to browser clients via WebSocket. A built-in static file server hosts the sensing UI on the same port.

The crate ships both a library (wifi_densepose_sensing_server) exposing the training and inference modules, and a binary (sensing-server) that starts the full server stack.

Integrates wifi-densepose-wifiscan for multi-BSSID WiFi scanning per ADR-022 Phase 3.

Features

  • UDP CSI ingestion -- Receives ESP32 CSI frames on port 5005 and parses them into the internal CsiFrame representation.
  • Vital sign detection -- Pure-Rust FFT-based breathing rate (0.1--0.5 Hz) and heart rate (0.67--2.0 Hz) estimation from CSI amplitude time series (ADR-021).
  • RVF container -- Standalone binary container format for packaging model weights, metadata, and configuration into a single .rvf file with 64-byte aligned segments.
  • RVF pipeline -- Progressive model loading with streaming segment decoding.
  • Graph Transformer -- Cross-attention bottleneck between antenna-space CSI features and the COCO 17-keypoint body graph, followed by GCN message passing (ADR-023 Phase 2). Pure std, no ML dependencies.
  • SONA adaptation -- LoRA + EWC++ online adaptation for environment drift without catastrophic forgetting (ADR-023 Phase 5).
  • Contrastive CSI embeddings -- Self-supervised SimCLR-style pretraining with InfoNCE loss, projection head, fingerprint indexing, and cross-modal pose alignment (ADR-024).
  • Sparse inference -- Activation profiling, sparse matrix-vector multiply, INT8/FP16 quantization, and a full sparse inference engine for edge deployment (ADR-023 Phase 6).
  • Dataset pipeline -- Training dataset loading and batching.
  • Multi-BSSID scanning -- Windows netsh integration for BSSID discovery via wifi-densepose-wifiscan (ADR-022).
  • WebSocket broadcast -- Real-time sensing updates pushed to all connected clients at ws://localhost:8765/ws/sensing.
  • Static file serving -- Hosts the sensing UI on port 8080 with CORS headers.

Modules

Module Description
vital_signs Breathing and heart rate extraction via FFT spectral analysis
rvf_container RVF binary format builder and reader
rvf_pipeline Progressive model loading from RVF containers
graph_transformer Graph Transformer + GCN for CSI-to-pose estimation
trainer Training loop orchestration
dataset Training data loading and batching
sona LoRA adapters and EWC++ continual learning
sparse_inference Neuron profiling, sparse matmul, INT8/FP16 quantization
embedding Contrastive CSI embedding model and fingerprint index

Quick Start

# Build the server
cargo build -p wifi-densepose-sensing-server

# Run with default settings (HTTP :8080, UDP :5005, WS :8765)
cargo run -p wifi-densepose-sensing-server

# Run with custom ports
cargo run -p wifi-densepose-sensing-server -- \
    --http-port 9000 \
    --udp-port 5005 \
    --static-dir ./ui

Using as a library

use wifi_densepose_sensing_server::vital_signs::VitalSignDetector;

// Create a detector with 20 Hz sample rate
let mut detector = VitalSignDetector::new(20.0);

// Feed CSI amplitude samples
for amplitude in csi_amplitudes.iter() {
    detector.push_sample(*amplitude);
}

// Extract vital signs
if let Some(vitals) = detector.detect() {
    println!("Breathing: {:.1} BPM", vitals.breathing_rate_bpm);
    println!("Heart rate: {:.0} BPM", vitals.heart_rate_bpm);
}

Architecture

ESP32 ──UDP:5005──> [ CSI Receiver ]
                          |
                    [ Signal Pipeline ]
                    (vital_signs, graph_transformer, sona)
                          |
                    [ WebSocket Broadcast ]
                          |
Browser <──WS:8765── [ Axum Server :8080 ] ──> Static UI files
Crate Role
wifi-densepose-wifiscan Multi-BSSID WiFi scanning (ADR-022)
wifi-densepose-core Shared types and traits
wifi-densepose-signal CSI signal processing algorithms
wifi-densepose-hardware ESP32 hardware interfaces
wifi-densepose-wasm Browser WASM bindings for the sensing UI
wifi-densepose-train Full training pipeline with ruvector
wifi-densepose-mat Disaster detection module

License

MIT OR Apache-2.0