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docs: Add use cases section and fix multi-person limit accuracy
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 <[email protected]>
Copy file name to clipboardExpand all lines: README.md
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@@ -48,7 +48,7 @@ docker run -p 3000:3000 ruvnet/wifi-densepose:latest
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| 🔒 |**Privacy-First**| Tracks human pose using only WiFi signals — no cameras, no video, no images stored |
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| ⚡ |**Real-Time**| Analyzes WiFi signals in under 100 microseconds per frame — fast enough for live monitoring |
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| 💓 |**Vital Signs**| Detects breathing rate (6-30 breaths/min) and heart rate (40-120 bpm) without any wearable |
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| 👥 |**Multi-Person**|Simultaneously tracks multiple people (default 10, configurable up to 50+), each with independent pose and vitals |
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| 👥 |**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)|
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| 🧱 |**Through-Wall**| WiFi passes through walls, furniture, and debris — works where cameras cannot |
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| 🚑 |**Disaster Response**| Detects trapped survivors through rubble and classifies injury severity (START triage) |
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| 🐳 |**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
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<details>
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<summary><strong>🏢 Use Cases & Applications</strong> — From hospital rooms to concert halls</summary>
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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.
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**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.
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### Everyday — Proven with commodity WiFi
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| Use Case | What It Does | Hardware Needed |
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|----------|-------------|-----------------|
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|**Elderly care / assisted living**| Fall detection, nighttime activity monitoring, breathing rate during sleep — no wearable compliance needed | 1 ESP32-S3 per room ($8) |
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|**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 |
|**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 |
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|**Office space utilization**| Which desks/rooms are actually occupied, meeting room no-shows, HVAC optimization based on real presence | Existing enterprise WiFi |
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|**Hotel & hospitality**| Room occupancy without door sensors, minibar/bathroom usage patterns, energy savings on empty rooms | Existing hotel WiFi |
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### Specialized — Requires CSI-capable hardware
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| Use Case | What It Does | Hardware Needed |
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|----------|-------------|-----------------|
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|**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) |
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|**Fitness & sports**| Rep counting, posture correction, breathing cadence during exercise — no wearable, no camera in locker rooms | 3+ ESP32-S3 mesh |
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|**Childcare & schools**| Naptime breathing monitoring, playground headcount, restricted-area alerts — privacy-safe for minors | 2-4 ESP32-S3 per zone |
|**Warehouse & logistics**| Worker safety zones, forklift proximity alerts, occupancy in hazardous areas — works through shelving and pallets | Industrial AP mesh |
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|**Civic infrastructure**| Public restroom occupancy (no cameras possible), subway platform crowding, shelter headcount during emergencies | Municipal WiFi + ESP32 |
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### Extreme — Through-wall and disaster scenarios
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| Use Case | What It Does | Hardware Needed |
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|----------|-------------|-----------------|
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|**Search & rescue (WiFi-Mat)**| Detect survivors through rubble/debris via breathing signature, START triage color classification, 3D localization | Portable ESP32 mesh + laptop |
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|**Prison & secure facilities**| Cell occupancy verification, distress detection (abnormal vitals), perimeter sensing — no camera blind spots | Dedicated AP infrastructure |
|**Mining & underground**| Worker presence in tunnels where GPS/cameras fail, breathing detection after collapse, headcount at safety points | Ruggedized ESP32 mesh |
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|**Wildlife research**| Non-invasive animal activity monitoring in enclosures or dens — no light pollution, no visual disturbance | Weatherproof ESP32 nodes |
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