WiFi DensePose

Human Tracking Through Walls Using WiFi Signals

Revolutionary WiFi-Based Human Pose Detection

AI can track your full-body movement through walls using just WiFi signals. Researchers at Carnegie Mellon have trained a neural network to turn basic WiFi signals into detailed wireframe models of human bodies.

System Status

API Server -
Hardware -
Inference -
Streaming -

System Metrics

CPU Usage
0%
Memory Usage
0%
Disk Usage
0%

Features

Live Statistics

Active Persons 0
Avg Confidence 0%
Total Detections 0

Zone Occupancy

🏠

Through Walls

Works through solid barriers with no line of sight required

🔒

Privacy-Preserving

No cameras or visual recording - just WiFi signal analysis

Real-Time

Maps 24 body regions in real-time at 100Hz sampling rate

💰

Low Cost

Built using $30 commercial WiFi hardware

24 Body Regions
100Hz Sampling Rate
87.2% Accuracy (AP@50)
$30 Hardware Cost

Hardware Configuration

3×3 Antenna Array

Click antennas to toggle their state

Transmitters (3)
Receivers (6)

WiFi Configuration

2.4GHz ± 20MHz
30
100 Hz
$30

Real-time CSI Data

Amplitude:
0.75
Phase:
1.2π

Live Demonstration

Ready

WiFi Signal Analysis

Signal Strength: -45 dBm
Processing Latency: 12 ms

Human Pose Detection

Persons Detected: 0
Confidence: 0.0%
Keypoints: 0/0

System Architecture

WiFi DensePose Architecture
1

CSI Input

Channel State Information collected from WiFi antenna array

2

Phase Sanitization

Remove hardware-specific noise and normalize signal phase

3

Modality Translation

Convert WiFi signals to visual representation using CNN

4

DensePose-RCNN

Extract human pose keypoints and body part segmentation

5

Wireframe Output

Generate final human pose wireframe visualization

Performance Analysis

Performance Comparison Chart

WiFi-based (Same Layout)

Average Precision: 43.5%
AP@50: 87.2%
AP@75: 44.6%

Image-based (Reference)

Average Precision: 84.7%
AP@50: 94.4%
AP@75: 77.1%

Advantages & Limitations

Advantages

  • Through-wall detection
  • Privacy preserving
  • Lighting independent
  • Low cost hardware
  • Uses existing WiFi

Limitations

  • Performance drops in different layouts
  • Requires WiFi-compatible devices
  • Training requires synchronized data

Real-World Applications

👴

Elderly Care Monitoring

Monitor elderly individuals for falls or emergencies without invading privacy. Track movement patterns and detect anomalies in daily routines.

Fall Detection Activity Monitoring Emergency Alert
🏠

Home Security Systems

Detect intruders and monitor home security without visible cameras. Track multiple persons and identify suspicious movement patterns.

Intrusion Detection Multi-person Tracking Invisible Monitoring
🏥

Healthcare Patient Monitoring

Monitor patients in hospitals and care facilities. Track vital signs through movement analysis and detect health emergencies.

Vital Sign Analysis Movement Tracking Health Alerts
🏢

Smart Building Occupancy

Optimize building energy consumption by tracking occupancy patterns. Control lighting, HVAC, and security systems automatically.

Energy Optimization Occupancy Tracking Smart Controls
🥽

AR/VR Applications

Enable full-body tracking for virtual and augmented reality applications without wearing additional sensors or cameras.

Full Body Tracking Sensor-free Immersive Experience

Implementation Considerations

While WiFi DensePose offers revolutionary capabilities, successful implementation requires careful consideration of environment setup, data privacy regulations, and system calibration for optimal performance.