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docs: Add use cases section and fix multi-person limit accuracy

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Add collapsible Use Cases & Applications section organized from
practical (elderly care, hospitals, retail) to specialized (events,
warehouses) to extreme (search & rescue, through-wall). Includes
hardware requirements and scaling notes per category.

Fix multi-person description to reflect reality: no hard software
limit, practical ceiling is signal physics (~3-5 per AP at 56
subcarriers, linear scaling with multi-AP).

Co-Authored-By: claude-flow <ruv@ruv.net>
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ruv
2026-03-01 00:36:53 -05:00
parent e2ce250dba
commit b5ca361f0e
1 changed files with 44 additions and 1 deletions
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README.md
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@@ -48,7 +48,7 @@ docker run -p 3000:3000 ruvnet/wifi-densepose:latest
| 🔒 | **Privacy-First** | Tracks human pose using only WiFi signals — no cameras, no video, no images stored |
| ⚡ | **Real-Time** | Analyzes WiFi signals in under 100 microseconds per frame — fast enough for live monitoring |
| 💓 | **Vital Signs** | Detects breathing rate (6-30 breaths/min) and heart rate (40-120 bpm) without any wearable |
| 👥 | **Multi-Person** | Simultaneously tracks multiple people (default 10, configurable up to 50+), each with independent pose and vitals |
| 👥 | **Multi-Person** | Tracks multiple people simultaneously, each with independent pose and vitals — no hard software limit (physics: ~3-5 per AP with 56 subcarriers, more with multi-AP) |
| 🧱 | **Through-Wall** | WiFi passes through walls, furniture, and debris — works where cameras cannot |
| 🚑 | **Disaster Response** | Detects trapped survivors through rubble and classifies injury severity (START triage) |
| 🐳 | **One-Command Setup** | `docker pull ruvnet/wifi-densepose:latest` — live sensing in 30 seconds, no toolchain needed |
@@ -57,6 +57,49 @@ docker run -p 3000:3000 ruvnet/wifi-densepose:latest
---
<details>
<summary><strong>🏢 Use Cases & Applications</strong> — From hospital rooms to concert halls</summary>
WiFi sensing works anywhere WiFi exists. No new hardware in most cases — just software on existing access points or a $8 ESP32 add-on. Because there are no cameras, deployments avoid privacy regulations (GDPR video, HIPAA imaging) by design.
**Scaling note:** Each access point can distinguish ~3-5 people using 56 subcarriers (ESP32-S3). Multi-AP setups multiply capacity linearly — a 4-AP mesh in a retail store covers ~15-20 simultaneous occupants. There is no hard software limit; the `persons: Vec<PersonPose>` vector grows dynamically. The practical ceiling is signal physics: subcarrier count, AP placement, and room geometry.
### Everyday — Proven with commodity WiFi
| Use Case | What It Does | Hardware Needed |
|----------|-------------|-----------------|
| **Elderly care / assisted living** | Fall detection, nighttime activity monitoring, breathing rate during sleep — no wearable compliance needed | 1 ESP32-S3 per room ($8) |
| **Hospital patient monitoring** | Continuous breathing + heart rate for non-critical beds without wired sensors; nurse alert on anomaly | 1-2 APs per ward, existing WiFi |
| **Emergency room triage** | Automated occupancy count + wait-time estimation; detect patient distress (abnormal breathing) in waiting areas | Existing hospital WiFi |
| **Retail occupancy & flow** | Real-time foot traffic, dwell time by zone, queue length — no cameras, no opt-in, GDPR-friendly | Existing store WiFi + 1 ESP32 |
| **Office space utilization** | Which desks/rooms are actually occupied, meeting room no-shows, HVAC optimization based on real presence | Existing enterprise WiFi |
| **Hotel & hospitality** | Room occupancy without door sensors, minibar/bathroom usage patterns, energy savings on empty rooms | Existing hotel WiFi |
### Specialized — Requires CSI-capable hardware
| Use Case | What It Does | Hardware Needed |
|----------|-------------|-----------------|
| **Smart home automation** | Room-level presence triggers (lights, HVAC, music) that work through walls — no dead zones, no motion-sensor timeouts | 2-3 ESP32-S3 nodes ($24) |
| **Fitness & sports** | Rep counting, posture correction, breathing cadence during exercise — no wearable, no camera in locker rooms | 3+ ESP32-S3 mesh |
| **Childcare & schools** | Naptime breathing monitoring, playground headcount, restricted-area alerts — privacy-safe for minors | 2-4 ESP32-S3 per zone |
| **Event venues & concerts** | Crowd density mapping, crush-risk detection via breathing compression, emergency evacuation flow tracking | Multi-AP mesh (4-8 APs) |
| **Warehouse & logistics** | Worker safety zones, forklift proximity alerts, occupancy in hazardous areas — works through shelving and pallets | Industrial AP mesh |
| **Civic infrastructure** | Public restroom occupancy (no cameras possible), subway platform crowding, shelter headcount during emergencies | Municipal WiFi + ESP32 |
### Extreme — Through-wall and disaster scenarios
| Use Case | What It Does | Hardware Needed |
|----------|-------------|-----------------|
| **Search & rescue (WiFi-Mat)** | Detect survivors through rubble/debris via breathing signature, START triage color classification, 3D localization | Portable ESP32 mesh + laptop |
| **Prison & secure facilities** | Cell occupancy verification, distress detection (abnormal vitals), perimeter sensing — no camera blind spots | Dedicated AP infrastructure |
| **Military / tactical** | Through-wall personnel detection, room clearing confirmation, hostage vital signs at standoff distance | Directional WiFi + custom firmware |
| **Mining & underground** | Worker presence in tunnels where GPS/cameras fail, breathing detection after collapse, headcount at safety points | Ruggedized ESP32 mesh |
| **Wildlife research** | Non-invasive animal activity monitoring in enclosures or dens — no light pollution, no visual disturbance | Weatherproof ESP32 nodes |
</details>
---
## 📦 Installation
<details>