wifi-densepose/v2/crates/wifi-densepose-sensing-server
ruv ca10df7b0d fix(adr-115): CI green — example feature-gate + mosquitto allow_anon + bench numbers
## Two CI failures on PR #778 fixed

### 1. Rust Workspace Tests (E0601: `main` not found in mqtt_publisher)

Default `cargo build --workspace` compiles examples without forwarding
`--features mqtt`. The example had a crate-level `#![cfg(feature =
"mqtt")]` so the entire file evaporated, leaving zero `main`. Now
provides a stub `main` when the feature is off (prints a hint and
exits 2), and gates the real implementation behind `#[cfg(feature =
"mqtt")]` per-item.

Local verification:
  cargo check --no-default-features --examples → clean

### 2. mqtt-integration (mosquitto never became reachable)

`eclipse-mosquitto:2.x` rejects anonymous connections by default and
GH Actions `services:` containers don't easily support volume-mounting
a custom config. Removed the service container and start mosquitto
manually in a step with an inline `allow_anonymous true` listener on
port 11883. Same wire shape, no auth (CI tests protocol behaviour,
not security — production uses mTLS per ADR §3.9).

## Benchmark numbers captured (`docs/integrations/benchmarks.md`)

Ran `cargo bench --features mqtt --bench mqtt_throughput` locally:

| Hot path                              | Measured | Target | Better by |
|---------------------------------------|----------|--------|-----------|
| state::event_fall encode              | 259 ns   | <2 µs  | 7.7×      |
| rate_limiter::allow_first             | 49.7 ns  | <100 ns| 2×        |
| rate_limiter::allow_within_gap        | 62.1 ns  | <100 ns| 1.6×      |
| privacy::decide_hr_strip              | 0.24 ns  | <50 ns | 208×      |
| privacy::decide_presence_keep         | 0.24 ns  | <50 ns | 208×      |
| semantic::bus_tick_all_10_primitives  | 717 ns   | <10 µs | 14×       |

At 1 Hz publish rate per node, the entire ADR-115 hot path costs
~1 µs per node per tick on commodity hardware. A Cognitum Seed
hosting 100 nodes would burn 100 µs/sec — 0.01% load floor. Memory:
~30 KB total FSM state for 10 primitives × 100 nodes.

The numbers exceed every target by ≥1.6×, several by 100×+. No need
to optimise further for v0.7.0.

Refs #776, PR #778.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-05-23 14:47:46 -04:00
..
benches feat(adr-115): P9 — security audit (mqtt::security) + criterion benchmarks (15 tests) 2026-05-23 14:17:55 -04:00
examples fix(adr-115): CI green — example feature-gate + mosquitto allow_anon + bench numbers 2026-05-23 14:47:46 -04:00
src feat(adr-115): P8 — Matter bridge tree + commissioning code (38 tests, lib total 410) 2026-05-23 14:36:10 -04:00
tests feat(adr-115): P4 — broker integration tests + mosquitto CI workflow 2026-05-23 14:14:21 -04:00
Cargo.toml feat(adr-115): P9 — security audit (mqtt::security) + criterion benchmarks (15 tests) 2026-05-23 14:17:55 -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