Files
ruvnet--RuView/v2/crates/wifi-densepose-sensing-server
Dragan Spiridonov 788d685b9f fix(python,training): validate PyO3 inputs; make the single-training-job guard atomic
Closes the two findings from the adversarial review that were verified but left
unfixed. Both now have proper tests, each proven to fail against the old code.

1. PyO3 bindings panicked / over-allocated on caller input (aether.rs).
   `EmbeddingExtractor(n_heads=0)` reached `d_model % n_heads` in the transformer
   and panicked (surfacing to Python as an opaque PanicException); a non-divisor
   head count tripped the native assert; and `AetherConfig(d_model=100_000)`
   allocated multi-gigabyte weight matrices that abort the interpreter. The
   binding did no validation.

   Now both constructors return `PyResult` and validate at the boundary —
   positive dims, `d_model % n_heads == 0`, and a generous MAX_DIM/MAX_LAYERS cap
   — raising `ValueError`. Proven: `n_heads=0` -> "n_heads must be positive",
   `d_model=100_000` -> a clean ValueError, both previously a
   PanicException / abort. +10 pytest cases (test_aether.py); a valid config
   still constructs and embeds.

2. The single-training-job guard was a TOCTOU race (training_api.rs).
   `spawn_training_job` checked `is_active()` under a `state` READ lock, released
   it, then set `active` later. A tokio RwLock read lock is SHARED, so two
   concurrent `POST /train/start` could both hold it, both see the slot free, and
   both spawn jobs — sharing/overwriting one status+cancel and orphaning a task
   handle.

   Extracted `claim_training_slot`, which does the check-and-set in ONE `status`
   mutex scope — the atomicity lives on the status mutex, not the coarse state
   lock — so concurrent starts serialise and exactly one wins. This also makes it
   unit-testable without a full AppState.

   Test: 32 threads hit a barrier and race to claim; asserts EXACTLY ONE wins.
   Mutation-proven — reverting to the split check-then-set makes it fail
   (`left: 3, right: 1`), and it returns to 1 with the fix.

Verified on aarch64/macOS: training_api 28 pass (26 existing + 2 new), full
python/tests suite 237 pass (227 + 10). The native module keeps its internal
assert as a defence-in-depth invariant; the binding now enforces it at the edge.

Co-Authored-By: Ruflo & AQE
2026-07-24 14:45:55 +02:00
..

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