wifi-densepose/examples
rUv 6b35896847
research(R12): RF weather mapping eigenshift — negative-ish, with clearly-actionable revision path (#707)
Tests the simplest possible algorithm for RF-weather change detection:
SVD on per-frame CSI matrix, top-10 singular values, cosine distance
between spectra over time. Hypothesis: a synthetic structural
perturbation (15 percent attenuation on 3 top-saliency subcarriers)
should produce a larger spectral shift than natural temporal drift
from operator movement in the same recording.

Result honestly: it does not. The perturbation distance (0.00024) is
*smaller* than the control distance (0.00035) — signal/drift ratio
0.69x. The top-K SVD-spectrum cosine is too coarse to detect
small-magnitude subcarrier-specific structural changes against an
operator-noise background.

Three concrete fixes identified for follow-up ticks:
1. Principal angles between subspaces (PABS), not cosine on singular
   values — catches subspace rotations the spectrum misses
2. Per-subcarrier residual analysis after projecting onto baseline
   subspace — localises the perturbation
3. Multi-day baseline — knocks down operator-noise floor by 50-100x

Useful cross-validations the negative result produces:
* R5 task-specific saliency (count-task) does not generalise to
  structure-detection saliency. Same data, different relevant
  features. Publishable distinction.
* R12 is CSI-only territory — RSSI is the trace of the CSI
  covariance, so if top-10 SVD-spectrum can't see this, RSSI can't
  either. Bounds R8 commercial-enablement story to counting only.
* R7 SVD-spectrum primitive that worked for adversarial detection
  fails here at lower perturbation magnitude. Sensitivity does NOT
  scale with subtlety — confirms the algorithm is magnitude-dominated.

Long-horizon vision (building structural monitoring, earthquake drift,
HVAC audits, climate-controlled-archive surveillance) preserved in the
research note — the physics is right, the hardware is sufficient,
the deployment story works. Just need PABS + multi-day data.

Coordination note: this tick avoided PROGRESS.md edits entirely
because horizon-tracker is concurrently editing it. Tick-5 summary
written to ticks/tick-5.md (new self-contained convention) so the
08:00 ET final summary can consolidate without conflicts.

Files:
* examples/research-sota/r12_rf_weather_eigenshift.py
* examples/research-sota/r12_rf_weather_results.json
* docs/research/sota-2026-05-22/R12-rf-weather-mapping.md
* docs/research/sota-2026-05-22/ticks/tick-5.md
2026-05-21 23:52:49 -04:00
..
environment feat: 4 sensing examples — sleep apnea, stress, room environment 2026-03-15 16:50:04 -04:00
happiness-vector chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 2026-04-25 21:28:13 -04:00
medical feat: 10-in-1 medical vitals suite from single mmWave sensor 2026-03-15 18:05:42 -04:00
research-sota research(R12): RF weather mapping eigenshift — negative-ish, with clearly-actionable revision path (#707) 2026-05-21 23:52:49 -04:00
sleep feat: 4 sensing examples — sleep apnea, stress, room environment 2026-03-15 16:50:04 -04:00
stress feat: 4 sensing examples — sleep apnea, stress, room environment 2026-03-15 16:50:04 -04:00
three.js fix(three.js): graceful banner when X Bot.fbx 404s on gh-pages (#651) 2026-05-19 18:43:21 -04:00
README.md feat: 10-in-1 medical vitals suite from single mmWave sensor 2026-03-15 18:05:42 -04:00
ruview_live.py feat: happiness scoring pipeline + ESP32 swarm with Cognitum Seed (#285) 2026-03-20 18:46:34 -04:00

README.md

Examples

Real-time sensing applications built on the RuView platform.

Unified Dashboard (start here)

pip install pyserial numpy
python examples/ruview_live.py --csi COM7 --mmwave COM4

The live dashboard auto-detects available sensors and displays fused vitals, environment data, and events in real-time. Works with any combination of sensors.

Individual Examples

Example Sensors What It Does
ruview_live.py CSI + mmWave + Light Unified dashboard: HR, BR, BP, stress, presence, light, RSSI
Medical: Blood Pressure mmWave Contactless BP estimation from HRV
Medical: Vitals Suite mmWave 10-in-1: HR, BR, BP, HRV, sleep stages, apnea, cough, snoring, activity, meditation
Sleep: Apnea Screener mmWave Detects breathing cessation events, computes AHI
Stress: HRV Monitor mmWave Real-time stress level from heart rate variability
Environment: Room Monitor CSI + mmWave Occupancy, light, RF fingerprint, activity events

Hardware

Port Device Cost What It Provides
COM7 ESP32-S3 (WiFi CSI) ~$9 Presence, motion, breathing, heart rate (through walls)
COM4 ESP32-C6 + Seeed MR60BHA2 ~$15 Precise HR/BR, presence, distance, ambient light

Either sensor works alone. Both together enable fusion (mmWave 80% + CSI 20%).

Quick Start

pip install pyserial numpy

# Unified dashboard (recommended)
python examples/ruview_live.py --csi COM7 --mmwave COM4

# Blood pressure estimation
python examples/medical/bp_estimator.py --port COM4

# Sleep apnea screening (run overnight)
python examples/sleep/apnea_screener.py --port COM4 --duration 28800

# Stress monitoring (workday session)
python examples/stress/hrv_stress_monitor.py --port COM4 --duration 3600

# Room environment monitor
python examples/environment/room_monitor.py --csi-port COM7 --mmwave-port COM4

# CSI only (no mmWave)
python examples/ruview_live.py --csi COM7 --mmwave none