AI-CPS: Nepal Earthquake Severity Prediction

This repository is a fork of the MarcusGrum/AI-CPS repository and has been modified to include a custom project for the course:

“M. Grum: Advanced AI-Based Application Systems”
Junior Chair for Business Information Systems, esp. AI-Based Application Systems
University of Potsdam

---

Project Overview

The project aims to predict earthquake severity levels using data from the Nepal Earthquake dataset. This involves:

• Scraping, cleaning, and processing earthquake-related data.
• Developing AI models using TensorFlow.
• Implementing OLS models for comparison.
• Packaging the solution into Docker images for deployment.

---

Repository Structure

• data/: Contains raw and processed data files (joint_data_collection.csv, training_data.csv, etc.).
• models/: Stores trained AI and OLS models.
• code/: Python scripts for data preprocessing, model training, and evaluation.
• docker/: Dockerfiles and related configurations.
• documentation/: Course-related documentation and the final team report..
• images/: Example Docker images for the project.
• scenarios/: Sample docker-compose.yml files for integrating AI models and data processing.

---

Dataset

The dataset used in this project is the Nepal Earthquake Dataset from Kaggle, sourced from: https://www.kaggle.com/datasets/

Data files:

• joint_data_collection.csv: Cleaned and combined dataset.
• training_data.csv: 80% of the dataset for training.
• test_data.csv: 20% of the dataset for testing.
• activation_data.csv: A single data point for model activation testing.

---

License

This repository adheres to the terms of the AGPL-3.0 License as required by the course.

---

Acknowledgments

This project was created as part of the course “M. Grum: Advanced AI-Based Application Systems” at the University of Potsdam.