🚗 Automotive Predictive Maintenance System

A comprehensive AI-powered automotive maintenance system with user authentication, vehicle management, predictive analytics, and service tracking.

✨ Features

🔐 User Authentication

• Secure JWT-based login/registration
• User profile management
• Session persistence with token verification

🚗 Vehicle Management

• Car number registration and management
• Complete vehicle details (brand, model, year, odometer)
• Vehicle search and filtering
• CRUD operations for vehicle management

🤖 AI-Powered Predictions

• Enhanced RandomForest ML model with feature engineering
• Issue classification (engine, transmission, brake, electrical, etc.)
• Severity assessment (low, medium, high, critical)
• Cost estimation for different issues
• Risk scoring with confidence levels

📋 Service Records & Feedback

• Complete service history tracking
• Service analytics (cost, frequency, next service due)
• Feedback system with 1-5 star ratings
• Issue tracking and resolution documentation
• Service types: routine, emergency, predictive

📊 Dashboard & Analytics

• Real-time vehicle health status
• AI-generated maintenance recommendations
• Service cost analysis and frequency tracking
• Feedback analytics with issue patterns

🛠️ Technology Stack

Backend

• FastAPI - Modern Python web framework
• SQLAlchemy - Database ORM with relationships
• JWT Authentication - Secure token-based auth
• Scikit-learn - Machine learning models
• Pandas & NumPy - Data processing
• SQLite - Database (easily upgradeable to PostgreSQL)

Frontend

• React - Modern UI framework
• React Router - Client-side routing
• Tailwind CSS - Utility-first styling
• Lucide React - Beautiful icons
• Axios - HTTP client with interceptors

AI/ML Features

• RandomForest Classifier - Failure prediction
• Issue Classification - Multi-class problem solving
• Feature Engineering - Derived features for better accuracy
• Cross-validation - Model validation and performance metrics

🚀 Quick Start

Method 1: Automated Setup (Recommended)

1. Run the complete setup script:

   python setup_complete.py

2. Start the application:

   # Option 1: Start both servers
   run_app.bat
   
   # Option 2: Start separately
   run_backend.bat
   run_frontend.bat

Method 2: Manual Setup

Prerequisites

• Python 3.8+
• Node.js 16+
• npm (comes with Node.js)

Backend Setup

1. Navigate to backend directory:

   cd automotive-maintenance/backend

2. Create virtual environment:

   python -m venv venv

3. Activate virtual environment:

   # Windows
   venv\Scripts\activate
   
   # macOS/Linux
   source venv/bin/activate

4. Install dependencies:

   pip install -r requirements.txt

5. Initialize database:

   python init_data.py

6. Run the backend:

   python main.py

Frontend Setup

1. Navigate to frontend directory:

   cd automotive-maintenance/frontend

2. Install dependencies:

   npm install

3. Start development server:

   npm run dev

🌐 Access Points

Once both servers are running:

• Frontend Application: http://localhost:3000
• Backend API: http://127.0.0.1:8000
• API Documentation: http://127.0.0.1:8000/docs

🔑 Default Login Credentials

• Username: demo_user
• Password: demo123

📁 Project Structure

automotive-maintenance/
├── backend/
│   ├── ai/
│   │   ├── train_model.py      # Enhanced ML training
│   │   └── predict_model.py    # AI prediction engine
│   ├── routers/
│   │   ├── auth.py            # Authentication endpoints
│   │   ├── vehicles.py        # Vehicle management
│   │   ├── service_records.py # Service & feedback
│   │   ├── prediction.py      # AI predictions
│   │   ├── feedback.py        # Legacy feedback
│   │   └── schedule.py        # Service booking
│   ├── database.py            # Database models & setup
│   ├── schemas.py             # Pydantic schemas
│   ├── auth.py               # Authentication utilities
│   ├── init_data.py          # Database initialization
│   ├── main.py               # FastAPI application
│   └── requirements.txt      # Python dependencies
├── frontend/
│   ├── src/
│   │   ├── components/
│   │   │   ├── AuthModal.jsx      # Login/Register modal
│   │   │   ├── VehicleManagement.jsx # Vehicle CRUD
│   │   │   ├── ServiceRecords.jsx # Service tracking
│   │   │   ├── Navbar.jsx         # Navigation
│   │   │   ├── Footer.jsx         # Footer
│   │   │   └── Loader.jsx         # Loading component
│   │   ├── pages/
│   │   │   ├── Dashboard.jsx      # Main dashboard
│   │   │   ├── Feedback.jsx       # Feedback page
│   │   │   └── Schedule.jsx       # Service booking
│   │   ├── services/
│   │   │   └── api.js            # API client
│   │   ├── App.jsx               # Main app component
│   │   └── main.jsx             # React entry point
│   └── package.json             # Node dependencies
└── README.md                    # This file

🔧 API Endpoints

Authentication

• POST /auth/register - User registration
• POST /auth/login - User login
• GET /auth/me - Get current user
• GET /auth/verify-token - Verify token validity

Vehicles

• GET /vehicles/ - Get user's vehicles
• POST /vehicles/ - Add new vehicle
• GET /vehicles/{vehicle_id} - Get specific vehicle
• PUT /vehicles/{vehicle_id} - Update vehicle
• DELETE /vehicles/{vehicle_id} - Delete vehicle
• GET /vehicles/search/{query} - Search vehicles

Predictions

• POST /predict/vehicle - Get vehicle predictions
• GET /predict/health - System health check

Service Records

• GET /service-records/vehicle/{vehicle_id} - Get vehicle service records
• POST /service-records/ - Create service record
• GET /service-records/analytics/vehicle/{vehicle_id} - Get service analytics
• POST /service-records/feedback - Create feedback
• GET /service-records/feedback/vehicle/{vehicle_id} - Get vehicle feedback

🤖 AI Model Details

Enhanced Features

• Service Frequency: Services per year calculation
• Cost Per Service: Average cost analysis
• Mileage Per Year: Usage pattern analysis
• High Mileage Flag: Binary feature for high usage
• Old Vehicle Flag: Age-based categorization

Model Performance

• Cross-validation: 5-fold CV for robust evaluation
• Feature Importance: Identifies most predictive features
• Confusion Matrix: Detailed performance analysis
• Classification Report: Precision, recall, F1-score

Issue Classification

• Multi-class Problem: 8 different issue types
• Severity Levels: 4 severity categories
• Cost Estimation: Realistic cost ranges
• Action Recommendations: Specific repair suggestions

📊 Database Schema

Core Tables

• users: User authentication and profile data
• vehicles: Vehicle information and ownership
• service_records: Complete service history
• feedback: Service feedback and ratings
• service_bookings: Service appointment scheduling
• issue_classifications: AI-generated issue patterns

Relationships

• Users → Vehicles (One-to-Many)
• Vehicles → Service Records (One-to-Many)
• Vehicles → Feedback (One-to-Many)
• Service Records → Feedback (One-to-Many)

🔒 Security Features

• JWT Authentication: Secure token-based auth
• Password Hashing: bcrypt for password security
• CORS Protection: Configured for frontend domains
• Input Validation: Pydantic schemas for data validation
• SQL Injection Protection: SQLAlchemy ORM protection

🎨 UI/UX Features

• Responsive Design: Mobile-first approach
• Modern Interface: Clean, professional design
• Real-time Updates: Live data refresh
• Loading States: User-friendly loading indicators
• Error Handling: Comprehensive error management
• Accessibility: WCAG compliant components

🐛 Troubleshooting

Common Issues

1. Backend won't start:

   # Check Python version
   python --version
   
   # Reinstall dependencies
   pip install -r requirements.txt --force-reinstall

2. Frontend won't start:

   # Clear npm cache
   npm cache clean --force
   
   # Delete node_modules and reinstall
   rm -rf node_modules
   npm install

3. Database errors:

   # Delete database and reinitialize
   rm automotive_maintenance.db
   python init_data.py

4. Authentication issues:

   • Clear browser localStorage
   • Check if backend is running on port 8000
   • Verify CORS settings

Port Conflicts

If ports 3000 or 8000 are in use:

Backend (change port 8000):

uvicorn main:app --reload --host 0.0.0.0 --port 8001

Frontend (change port 3000):

npm run dev -- --port 3001

📈 Future Enhancements

• Real-time Notifications: Push notifications for service reminders
• Mobile App: React Native mobile application
• Advanced Analytics: Machine learning insights dashboard
• Integration APIs: Third-party service center integration
• Multi-language Support: Internationalization
• Cloud Deployment: AWS/Azure deployment options

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🆘 Support

For support and questions:

• Create an issue in the repository
• Check the troubleshooting section above
• Review the API documentation at /docs

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Built with ❤️ for automotive maintenance professionals

🎯 Getting Started Checklist

• Install Python 3.8+ and Node.js 16+
• Run python setup_complete.py for automated setup
• Start backend: run_backend.bat or python main.py
• Start frontend: run_frontend.bat or npm run dev
• Open http://localhost:3000 in browser
• Login with demo_user / demo123
• Add your first vehicle
• Explore AI predictions and features

🎊 You're all set! Enjoy the automotive maintenance system!