Files
ruvnet--RuView/v2/crates/wifi-densepose-sensing-server
ruv a47bb71b22 fix(adr-185): hoist AETHER compute surface into a std-only leaf crate
ADR-185 §13 flagged the `[aether]` wheel as linking the whole
`wifi-densepose-sensing-server` Axum/tokio/worldgraph/ruvector tree via the
non-optional deps of that crate. Hoist the pure-compute AETHER stack out so the
binding depends only on pure Rust.

New crate `wifi-densepose-aether` (std-only, ZERO external deps) holds the four
self-contained modules the AETHER surface needs — `embedding`, `graph_transformer`,
`sona`, `sparse_inference` (verified: no serde/tokio/axum/crate:: refs outside the
set; the four form a closed dependency graph). `wifi-densepose-sensing-server`
now `pub use`s them from the leaf crate, so its own code (`crate::embedding`, …)
and public API (`wifi_densepose_sensing_server::embedding`, …) are unchanged —
`main.rs`/`trainer.rs` untouched. The Python binding + parity test + `[aether]`
feature repoint at the leaf crate; the sensing-server dep is dropped from python.

MEASURED wheel size (maturin build --release --features aether --strip; each
wheel install-verified to actually contain `AetherConfig`):
  BEFORE (aether -> sensing-server): 369,782 B (~361 KB)
  AFTER  (aether -> leaf crate):     319,719 B (~312 KB)

HONEST CORRECTION to the §9/§13 premise: the pre-hoist wheel was NOT over the
ADR-117 §5.4 5 MB budget — it was ~361 KB, ~14x under. Linker dead-code
elimination (--gc-sections on the pyo3 cdylib) already strips the unreached
server tree because the binding only reaches pure-compute symbols. So this is
"blows the budget" CLAIMED, not MEASURED. The hoist is still worthwhile and
lands the real, measured wins:
  - `[aether]` build time 71s -> 12s (no server tree to compile),
  - python/Cargo.lock -1238 lines (server tree no longer resolved),
  - ~50 KB smaller wheel,
  - honest, minimal declared dependency surface + removes the latent risk that a
    future change makes some server code reachable and *then* bloats the wheel.

Verified this session (real counts):
  - cargo test --features aether --test aether_parity: 2 passed / 0 failed
  - pytest tests/test_aether.py (maturin develop --features aether): 9 passed
  - cargo test -p wifi-densepose-sensing-server --no-default-features: 217 bin +
    388 lib, 0 failed (no regression)
  - cargo test -p wifi-densepose-aether: 96 passed (the relocated unit tests)

The §9/§13 wheel-size narrative in ADR-185 (owned by the ADR author) should be
corrected to reflect the measured reality — flagged to the team lead.
2026-07-21 17:43:32 -07:00
..

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