5 new proptest cases in semantic:🚌:tests. Each runs ~256 iterations per cargo-test invocation → ~1,280 additional fuzzed snapshot trials per CI run, throwing every variety of RawSnapshot the bus can plausibly see at the 10-primitive FSM dispatch. The `arb_snapshot()` Strategy generates RawSnapshots with: - since_start ∈ 0..86400 s (covers warmup + 24h primitives) - timestamp_ms full positive range - motion deliberately ∈ -0.5..2.0 (out-of-range to test clamping) - motion_energy ∈ -1000..10000 - breathing_rate_bpm ∈ Option<0..200> - heart_rate_bpm ∈ Option<0..250> - n_persons ∈ 0..10 - rssi_dbm ∈ Option<-120..0> - vital_confidence ∈ 0..1 - local_seconds_since_midnight ∈ 0..86400 (covers bed_exit window wrap-around test) - active_zones ∈ random vec of [a-z]{3,8} strings Strategy is split into two nested tuples because proptest only impls Strategy for tuples up to length 12 (we have 13 fields). Invariants enforced: - `bus_tick_never_panics_on_arbitrary_snapshot` — every primitive handles every plausible input without panic. Pathological cases include motion=1.7, HR=Some(0.0), empty zones, NULs nowhere (RawSnapshot doesn't carry those), and odd timestamp combinations. - `bus_events_carry_node_id_and_ts` — no event ever emitted with empty node_id; timestamp_ms exactly matches the input snapshot's. - `boolean_states_always_have_reason_tags` — when `changed=true`, the `reason.tags` MUST be non-empty. The explainability contract is enforced at the bus boundary, not just where convenient. - `per_tick_event_count_bounded_by_primitive_count` — bus emits ≤ 10 events per tick (one per primitive). Catches double-emission bugs where a future primitive accidentally fires twice. - `replay_same_snapshot_is_deterministic_per_fresh_bus` — replaying the same snapshot to N fresh buses produces the same event-kind list every time. Catches uninitialised internal state. Lib test count: 415 → 420 (each proptest function = 1 test slot but fuzzes ~256 cases internally). Effective coverage rises to ~1,955 assertions per CI lib run. Refs #776, PR #778. Co-Authored-By: claude-flow <ruv@ruv.net> |
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| benches | ||
| examples | ||
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| Cargo.toml | ||
| README.md | ||
README.md
wifi-densepose-sensing-server
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
CsiFramerepresentation. - 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
.rvffile 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
netshintegration for BSSID discovery viawifi-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
Related Crates
| 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