🧭 sensor_based_navigation #

Offline Position Tracking Using Sensor Fusion + AI

A Flutter package for estimating device position and direction without GPS, using sensor data and LSTM-based AI models.

🚀 Features #

• 📍 GPS-free indoor navigation
• 🧠 AI-based predictions using LSTM neural networks
• 🔄 Drift correction using footstep detection logic
• 🔧 Sensor fusion (accelerometer, gyroscope, magnetometer, barometer)
• ⚡ Optimized for CPU inference (XNNPACK)

📱 How It Works #

Inspired by research from the University of Utah and others:

• Detects steps and resets drift every ~100ms of foot-ground contact
• Uses direction (magnetometer), movement (accelerometer), and elevation (barometer)
• LSTM neural network processes time-series sensor input to estimate movement

🧠 Why LSTM? #

LSTM (Long Short-Term Memory) networks are ideal for sequential sensor data because they:

• Handle long-term dependencies
• Filter noisy or irrelevant input
• Model complex motion patterns over time

📦 Installation #

Add this to your pubspec.yaml:

dependencies:
  sensor_based_navigation:
    git:
      url: https://github.com/yourusername/sensor_based_navigation.git

## 📦 Performance Notes
- ONNX model not fully supported on NNAPI or CoreML
- Use CPU backend with XNNPACK for best performance

## License
This project is licensed under the MIT License.