EQ_Magnitude_Estimation_VIT

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Description:

This repository contains a comprehensive project for real-time earthquake detection and magnitude estimation using Vision Transformer (ViT). The project processes 3-axis accelerometer data from multiple devices, providing accurate P-wave detection and earthquake magnitude estimation in real-time.

Key Features

• Real-time P-wave detection using a convolutional neural network (CNN) model.
• Accurate earthquake magnitude estimation with a Vision Transformer (ViT) model.
• Synthetic data generation, preprocessing, and normalization for training.
• Detailed model training scripts with early stopping to prevent overfitting.
• Real-time data processing and estimation with sample simulations.

Folder Structure

• data_preparation.py: Script for generating and preprocessing synthetic accelerometer data.
• models/: Directory containing the model definitions for P-wave detection and magnitude estimation.
  • p_wave_model.py: P-wave detection model definition.
  • magnitude_model.py: Magnitude estimation model definition.
• train_models.py: Script for training both P-wave detection and magnitude estimation models.
• real_time_detection.py: Script for simulating real-time data and performing earthquake detection and magnitude estimation.
• utils.py: Utility functions for data preprocessing.
• data/: Directory for storing prepared data and trained model files.

Getting Started

1. Clone the repository:

   git clone https://github.com/oaslananka/EQ_Magnitude_Estimation_VIT.git
   cd EQ_Magnitude_Estimation_VIT

2. Install the required Python packages:

   pip install -r requirements.txt

3. Prepare the data:

   python data_preparation.py

4. Train the models:

   python train_models.py

5. Simulate real-time detection:

   python real_time_detection.py

License

This project is licensed under the MIT License.