wifi-densepose/v2/crates/wifi-densepose-sensing-server
ruv df95360e52 feat(adr-110 P10): apply_to_local + NodeState::mesh_aligned_us + full ADR rewrite
Iter 16 closes the math loop and updates ADR-110 to reflect the full
P1-P10 sprint outcome (per user request).

Code (the math layer that converts the iter 15 stored sync into a
per-frame mesh-aligned timestamp):

  wifi-densepose-hardware:
    SyncPacket::apply_to_local(local_at_frame_us: u64) -> u64
      Pure integer math: offset = epoch - local; mesh = local_at_frame + offset.
      3 new unit tests (10 total, all green):
      - apply_to_local_recovers_packet_epoch (identity at the packet's local_us)
      - apply_to_local_preserves_inter_frame_delta (Δlocal == Δmesh)
      - apply_to_local_on_leader_is_near_identity (leader offset ≈ 0)

  wifi-densepose-sensing-server:
    NodeState::mesh_aligned_us(local_at_frame_us: u64) -> Option<u64>
      Returns the recovered mesh timestamp using the most-recent sync
      packet, or None if no sync seen or last one older than 9 s
      (3× firmware VALID_WINDOW_MS = 9 s staleness gate).
      cargo check -p wifi-densepose-sensing-server --no-default-features
        → green

ADR-110 substantial rewrite (per user "update adr 110 with details"):

  - Status line: P1-P10 complete, firmware-side substrate closed at v0.7.0.
  - Front matter now lists all 4 firmware releases + witness link.
  - Phase table grows a P10 row capturing the v0.6.8 / v0.6.9 / v0.7.0
    arc (EMA smoother + sync packet + bit-4 wire-fix + host crates).
  - New §4.1 — /loop 5m SOTA sprint summary table (iters 1-16, 4 releases,
    17 commits, 13 unit tests, what shipped each iter).
  - New §4.2 — measured numbers table with 99.56% RX, 104.1 µs smoothed
    stdev, 3.95x suppression, 1.4 ppm crystal skew, etc — every cell
    backed by a witness §A0.x entry and a preserved bench log.
  - New §4.3 — host-side production surface listing (sync_packet.rs +
    sensing-server NodeState + Python parser, with file paths).
  - §5 open question on 802.15.4 channel resolved (Kconfig, default ch26
    not ch15, with the witness §D1 rationale).
  - New §6 — explicit scope of what's outside this ADR (multistatic fusion
    math in ADR-029/030, hardware-gated measurements needing INA / 11ax AP,
    IDF upstream fixes pending).

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-05-23 13:16:11 -04:00
..
src feat(adr-110 P10): apply_to_local + NodeState::mesh_aligned_us + full ADR rewrite 2026-05-23 13:16:11 -04:00
tests feat(introspection): I6 — regime-changed signal + per-frame analyze + honest ADR-099 D8 amendment 2026-05-13 23:29:37 -04:00
Cargo.toml feat(sensing-server): consume ADR-110 §A0.12 sync packets, store per-node 2026-05-23 13:11:35 -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