Smart Fleet Guardian is a predictive maintenance system designed to enhance fleet management by forecasting potential failures before they happen. Using machine learning and real-time data monitoring, it helps fleet operators improve vehicle reliability, reduce downtime, and optimize maintenance schedules.
- Predictive maintenance alerts using a Random Forest Machine Learning model
- Dashboard to monitor real-time fleet health and performance
- Historical data visualization for better decision-making
- Automated maintenance scheduling recommendations
- Scalable system architecture built for growing fleets
- Frontend: React.js
- Backend: Node.js (Express.js)
- Database: PostgreSQL
- Machine Learning: Random Forest Algorithm
- APIs: RESTful APIs for frontend-backend communication
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Clone the repository
git clone https://github.com/your-username/smart-fleet-guardian.git cd smart-fleet-guardian -
Frontend Setup
cd frontend npm install npm start -
Backend Setup
cd backend npm install npm run dev -
Database Setup
- Install PostgreSQL
- Create the necessary tables and seed initial data (scripts available in
/backend/db)
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Environment Variables Create a
.envfile in both frontend and backend with necessary environment variables:DATABASE_URL=your_postgresql_connection_url PORT=backend_server_port FRONTEND_URL=http://localhost:3000
- The Random Forest model is trained using historical fleet data (mileage, usage patterns, sensor readings, etc.)
- Predictions are made server-side and results are sent to the dashboard in real-time.
- Live vehicle telematics integration
- Driver behavior analysis
- Mobile app version
- AI-driven maintenance cost optimization
This project is licensed under the MIT License — see the LICENSE file for details.