719875ea1d
First deferred follow-up from R6. Productises R6's Fresnel forward model into a 2D placement-search CLI: given a room + target occupancy zones, recommend Tx/Rx positions that maximise first-Fresnel coverage. Benchmark on 5x5 m bedroom (bed 3 m^2 + chair 0.64 m^2, 2900 pairs evaluated at 2.4 GHz): - OPTIMAL: 51.1% coverage (Tx 1.25,0; Rx 4.75,5; diagonal 6.10 m link) - MEDIAN: 0.5% coverage - WORST: 0.0% coverage - 93x improvement, median to optimal Counter-intuitive insight: longer links cover MORE space. Fresnel envelope width = sqrt(d * lambda) / 2 grows with link length, so the 6.10 m diagonal beats wall-parallel 5.00 m links. Up to the R10 link-budget gate. Per-cog deployment recommendations: - cog-person-count: diagonal across longest axis - cog-pose: zone inside ~50% midpoint envelope - AETHER re-ID: Tx near doorway, Rx diagonal - cog-maritime-watch: vertical diagonal through cabin - cog-wildlife (future): Tx/Rx opposite trees, threading clearing midline Improvements come from physics, not algorithms - no model retraining needed. Existing customers can re-mount seeds today for 10-100x better sensing. Honest scope: 2D approximation, free-space, rectangular zones, single-pair only, perimeter-only candidates, no link-budget gate. CLI shape ready for productisation as 'wifi-densepose plan-antennas'. Also surfaces as a deferred MCP tool 'ruview_placement_recommend'. Composes with: - R6 (direct 2D extension) - R1 (placement x precision = full geometry budget) - R10 (sets the link-budget gate this ignores) - R11 (same recipe in steel cabins) - R14 (determines whether V1/V2/V3 see the right occupant) - ADR-105 (better placement = faster epsilon convergence) Next R6.2 follow-ups catalogued: R6.2.1 (3D), R6.2.2 (N-anchor union), R6.2.3 (pose-trajectory target zones). Coordination: ticks/tick-16.md, no PROGRESS.md edit. |
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| .. | ||
| environment | ||
| happiness-vector | ||
| medical | ||
| research-sota | ||
| sleep | ||
| stress | ||
| three.js | ||
| README.md | ||
| ruview_live.py | ||
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