wifi-densepose/v2/crates/wifi-densepose-sensing-server
rUv 0c2b1c16cc
fix: ESP32 vitals over-count + presence flicker (#998/#996) + Observatory per-person position/motion (#1050) (#1060)
* fix(firmware): gate phantom persons + add presence hysteresis (#998, #996)

Two ESP32 edge-vitals logic bugs in edge_processing.c. Both are
robustness/logic fixes — NOT validated-accuracy claims. True count/PCK
vs labelled ground truth remains hardware/data-gated (COM9 ESP32-S3).

#998 — n_persons over-counted (reported 4 for one person):
update_multi_person_vitals() split top-K subcarriers into top_k_count/2
groups and marked EVERY group active, so one body's multipath always
read the full EDGE_MAX_PERSONS. Added two pure, host-testable helpers:
  - count_distinct_persons(): per-group energy gate
    (EDGE_PERSON_MIN_ENERGY_RATIO) + spatial dedup
    (EDGE_PERSON_MIN_SC_SEP) so weak/adjacent multipath groups don't
    count as separate bodies. Strongest group always counts (>=1).
  - person_count_debounce(): a gated count must hold
    EDGE_PERSON_PERSIST_FRAMES consecutive frames before it's emitted,
    so a single noisy frame can't promote a phantom.
The active flags now mark only the strongest stable_count groups.

#996 — presence flag flickered at ~50cm despite high presence_score:
the bare `score > threshold` compare chattered on a noisy score
(field-observed 2.6-26.7 frame-to-frame). Replaced with a Schmitt
trigger + clear-debounce (presence_flag_update): assert above
threshold, hold in the dead band down to threshold *
EDGE_PRESENCE_HYST_RATIO, clear only after EDGE_PRESENCE_CLEAR_FRAMES
consecutive sub-low frames. presence_score itself is unchanged and
still emitted for consumer-side thresholding.

All thresholds are named, documented constants in edge_processing.h.
Firmware builds clean for esp32s3 (idf.py build RC=0).

Co-Authored-By: claude-flow <ruv@ruv.net>

* test(firmware): host C99 tests for vitals count + presence logic (#998, #996)

test/test_vitals_count_presence.c pins the two fixes with deterministic
host-buildable tests (no ESP-IDF needed). 13 cases / 22 assertions, all
passing under gcc 13 -Wall -Wextra:

  #998 count gate: single strong signature + multipath -> count==1;
  two well-separated -> 2; two strong-but-adjacent -> 1 (dedup);
  no signal -> 0; three well-separated -> 3.
  #998 debounce: transient spike rejected; sustained change accepted;
  flapping count stays stable.
  #996 presence: dithering trace -> stable flag (no flicker); brief dips
  held by clear-debounce; genuine departure clears within hold window;
  dead-band holds state.

The named tuning constants are #include'd from the real
edge_processing.h so the test and firmware can never disagree on
thresholds. `make run_vitals` / `make host_tests` added; binaries
gitignored.

Hardware-gated caveat documented in the test header: these pin the
decision LOGIC; the exact energy/separation/hysteresis values that best
match a real room vs labelled occupancy remain on-device tuning.

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs: record ESP32 vitals count/presence fixes (#998, #996)

CHANGELOG [Unreleased] Fixed: root cause + fix + named constants + test
+ explicit hardware/data-gated caveat for both bugs.

ADR-021 Implementation Notes: dated 2026-06 entry noting the edge-path
person-count + presence-flicker fixes are boolean/count emission-logic
fixes, not a validated-accuracy claim; thresholds pending on-device
calibration.

Co-Authored-By: claude-flow <ruv@ruv.net>

* fix(sensing-server): emit real field-derived person position/motion to /ws/sensing (#1050)

The Observatory 3D figure never animated because the sensing_update WS
frame carried no per-person position/motion_score/pose — only image-space
keypoints. The FigurePool/PoseSystem (and demo-data.js's own contract)
animate each figure from persons[i].position (room-world), .motion_score
(0..100), and .pose; none were on the live stream.

Honest scope (Case 2): the pipeline has no calibrated per-person room
localizer or per-person skeletal pose. New field_localize module extracts
the strongest peak(s) from the real signal_field grid (subcarrier
variances x motion-band power) and maps the peak cell to Observatory world
coords with the exact _buildSignalField transform. motion_score is the
measured motion_band_power passed through; pose is set only from a real
aggregate posture estimate, else None (never a fabricated skeleton).
Empty/below-threshold field -> persons: [] (no phantom); present person
with no resolvable peak keeps position [0,0,0], not invented coords.

attach_field_positions runs after the tracker step at all five broadcast
sites. New position/motion_score/pose fields added to both PersonDetection
structs. No UI change needed — the Observatory already reads these fields.

Tests: field_localize peak/coordinate/empty/separation units +
observatory_persons_field_position_tests (known-peak -> emitted position,
empty-room -> no phantom, pose real-or-None, below-threshold honesty).
sensing-server bin 441->451, 0 failed.

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs(changelog): record #1050 Observatory persons position/motion fix

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-06-14 00:31:30 -04:00
..
benches ADR-115: Home Assistant + Matter integration (#778) 2026-05-23 16:13:28 -04:00
examples fix(sensing-server): wire MQTT publisher into the binary — closes #872 2026-05-31 09:39:21 -04:00
src fix: ESP32 vitals over-count + presence flicker (#998/#996) + Observatory per-person position/motion (#1050) (#1060) 2026-06-14 00:31:30 -04:00
tests fix(firmware): C6 IDF v5.5 guard + HE-LTF host ingest + WITNESS-LOG-110 B1 resolution (#1005) (#1011) 2026-06-11 11:00:37 -04:00
Cargo.toml release: bump signal 0.3.4 / sensing-server 0.3.3 / cli 0.3.1 (fixes #1009, #1004) 2026-06-12 16:55:27 -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