AI-Enhanced Railway Safety and Crowd Management

Overview

AI-Enhanced Railway Safety and Crowd Management is an innovative project aimed at revolutionizing the Indian Railways by leveraging cutting-edge AI technology to address critical challenges faced by the railway sector. Our project focuses on real-time anomaly detection, crowd management, and crime prevention using the existing CCTV network.

Objective

Our objective is to enhance passenger safety, comfort, and the overall travel experience within the Indian Railways by deploying state-of-the-art AI models and real-time data analysis. We aim to address the following key challenges:

• Real-time anomaly detection for enhanced crowd management and crime prevention.
• Efficient monitoring of maintenance tasks to ensure railway infrastructure remains safe and reliable.
• Providing immediate guidance and assistance to passengers during security threats or other emergencies.

Key Features

• AI Models: We fine-tune deep learning models using Vision Transformer (ViT) and You Only Look Once (YOLO) for real-time anomaly detection.
• Web Application: Our AI seamlessly integrates into a user-friendly web application for accessible results.
• CCTV Network Integration: Utilizing existing CCTV infrastructure for real-time monitoring and enhanced security.
• Frame Storage and Preprocessing: Implementation of a frame storage system for capturing and preprocessing CCTV images.
• GPS-Based Guidance: Providing real-time route guidance during emergencies for passenger safety.

Technological Stack

Our project leverages a robust technological stack, including:

• Hugging Face
• HTML, CSS
• Python Flask
• SQLAlchemy
• TensorFlow, PyTorch
• Google Maps Geolocation API
• GitHub
• OpenCV

Installation

Set Up a Virtual Environment

1. Create a virtual environment with python3 -m venv venv.
2. Activate the virtual environment using source venv/bin/activate on Linux/MacOS or venv\Scripts\activate on Windows.

Install Dependencies

1. Install the required dependencies with pip install -r requirements.txt.

Set Up the Database

1. Modify the config.py file to set up your database configuration.
2. Run flask db upgrade to set up the database.

Run the Application

1. Start the application using flask run.
2. The app should now be running on http://127.0.0.1:5000.

Docker Setup (Optional)

Build the Docker Image

1. Build the Docker image with docker build -t railway-safety-ai ..

Run the Docker Container

1. Run the Docker container with docker run -p 5000:5000 railway-safety-ai.
2. The app will be accessible at http://localhost:5000.

Usage

For detailed usage instructions and examples, please refer to the User Guide.

Partnerships

Our project's success depends on building strong collaborations with railway authorities, enabling integration with the IRCTC App, and gaining access to real-time location data to optimize crowd management and safety.

Contributing

We welcome contributions from the community. If you'd like to contribute to our project, please refer to our Contribution Guidelines.

License

This project is licensed under the MIT License.