Rodity is a web-based application that leverages machine learning to predict and analyze road accident severity based on various real-world factors. It helps users understand how different conditions affect road safety, enabling proactive measures for accident prevention.
- 🚗 Accident severity prediction using trained machine learning models
- 📊 Interactive visual analysis of accident data
- 🧾 User-friendly web interface built with Flask
- 🔒 Login/signup system to restrict access to prediction tools
- 🤖 Gemini API integration for driving safety suggestions
The model takes the following features as input:
| Column | Description |
|---|---|
weather |
Weather condition during the incident |
road_condition |
Condition of the road |
road_type |
Type of road |
lighting |
Lighting condition |
vehicle_type |
Type of vehicle involved |
driver_age |
Age of the driver |
speed_limit |
Legal speed limit of the road |
traffic_volume |
Estimated traffic volume on the road |
severity |
Severity of the accident |
- Frontend: HTML, CSS, JavaScript
- Backend: Python, Flask
- Database: SQLite (for user authentication)
- ML Model: Scikit-learn model
- Visualization: Matplotlib, Seaborn
- AI Suggestions: Gemini API
Rodity/
├── static/ # CSS, JS, Images
├── templates/ # HTML Templates (login.html, predict.html, etc.)
├── app.py # Flask Application
├── accident_model.pkl # Trained ML Model
├── user.db # SQLite Database
├── README.md # Project Documentation
└── requirements.txt # Python Dependencies
- Clone the repository
https://github.com/Dhivakar2005/Roadity.git cd rodity - Install dependencies
pip install -r requirements.txt
- Run the Flask app
python app.py
- Access the app
Open your browser and go to http://127.0.0.1:5000
-
Deploy the app on cloud
-
Add a mobile-friendly version
-
Improve accuracy with advanced ML models
- Dhivakar G
- Santhosh S
- Siva E
- Baranidharan A
- Sathish B
Pull requests and feature suggestions are welcome! Feel free to fork the repo and improve Rodity.
This project is licensed under the MIT License - see the LICENSE file for details.