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Researchers have demonstrated the ability to track human movement through walls using standard WiFi routers, leveraging Channel State Information (CSI) and neural networks. This technique, known as DensePose-from-WiFi, captures phase and amplitude reflections from WiFi signals to reconstruct human poses in real time.
Key Components:
- 3×3 MIMO WiFi Router (e.g., Nighthawk mesh router)
- CSI Data Extraction (captures signal variations caused by human movement)
- Dual-Branch Encoder Neural Network (processes amplitude and phase data)
- RTMP Streaming (for live video output)
You Should Know:
1. Extracting CSI Data from WiFi
To capture WiFi signals for movement tracking, use Linux-based tools like:
Install required tools sudo apt-get install libpcap-dev git clone https://github.com/dhalperi/linux-80211n-csitool.git cd linux-80211n-csitool make sudo make install Capture CSI data sudo ./log_to_file csi.dat
2. Processing CSI Data with Python
Use Python to analyze WiFi reflections:
import numpy as np
import matplotlib.pyplot as plt
csi_data = np.fromfile('csi.dat', dtype=np.complex64)
phase = np.angle(csi_data)
amplitude = np.abs(csi_data)
plt.plot(phase, label='Phase')
plt.plot(amplitude, label='Amplitude')
plt.legend()
plt.show()
3. Neural Network for Pose Estimation
A PyTorch-based model processes WiFi reflections into human poses:
import torch import torch.nn as nn class WiFiPoseNet(nn.Module): def <strong>init</strong>(self): super(WiFiPoseNet, self).<strong>init</strong>() self.encoder = nn.LSTM(input_size=64, hidden_size=128, batch_first=True) self.decoder = nn.Linear(128, 18 2) 18 keypoints (x,y) def forward(self, x): x, _ = self.encoder(x) return self.decoder(x[:, -1, :]) model = WiFiPoseNet()
4. Real-Time Tracking with RTMP
Stream processed poses using FFmpeg:
ffmpeg -i pose_output.mp4 -c:v libx264 -f flv rtmp://live.twitch.tv/app/your-stream-key
What Undercode Say:
This technology has significant implications for surveillance, security, and privacy. While useful for law enforcement and smart homes, it also raises ethical concerns—WiFi signals can now act as invisible cameras. Future developments may include:
– WiFi-based intrusion detection
– Gesture-controlled smart environments
– Countermeasures (e.g., WiFi signal jamming)
Expected Output:
A live dashboard displaying human poses through walls, generated solely from WiFi signals.
Prediction:
WiFi sensing will evolve into ubiquitous surveillance tech, leading to new privacy regulations and anti-tracking solutions.
Relevant Links:
IT/Security Reporter URL:
Reported By: Reuvencohen In – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
