AI-Based Civic Issue Reporting System

🎯 Project Overview

A full-stack web application with integrated AI capabilities that enables citizens to report civic problems such as garbage accumulation, water issues, streetlight malfunctions, potholes, and other infrastructure concerns. The system leverages artificial intelligence to verify the authenticity of complaints and streamline the resolution process through automated departmental routing.

✨ Key Features

🤖 AI-Powered Verification

• Intelligent Complaint Analysis: AI model evaluates submitted reports to distinguish genuine issues from fraudulent submissions
• Image Recognition: Analyzes uploaded photos to validate the reported problem
• Pattern Detection: Identifies suspicious patterns in reporting behavior

🔄 Multi-Level Verification System

Level 1: AI Verification

• Automated initial screening of all submitted complaints
• Real-time authenticity assessment
• Immediate feedback to citizens

Level 2: Department Action

• Automatic routing to appropriate government departments
• Task assignment and tracking
• Status updates and progress monitoring

Level 3: Citizen Confirmation

• Citizens verify issue resolution
• Feedback collection on department response
• Closure confirmation

🎁 Incentive System

• Rewards: Points/credits for genuine, verified reports
• Penalties: Consequences for submitting fake or fraudulent complaints
• Gamification: Encourage civic participation through achievement badges

🏗️ System Architecture

Technology Stack (Implemented)

• Frontend: Next.js 14, React 18, TypeScript, TailwindCSS
• Backend: Node.js, Express, Mongoose
• AI/ML: Python, Flask, TensorFlow/PyTorch (ready for integration)
• Database: MongoDB (with Mongoose ODM)
• Authentication: JWT-based authentication with bcrypt
• File Upload: Multer for image handling
• Maps: React Leaflet for location selection
• Notifications: Nodemailer (email), Twilio (SMS - ready)

Core Components

1. Citizen Portal: Report submission and tracking interface
2. AI Verification Engine: Machine learning models for authenticity checking
3. Department Dashboard: Management interface for government officials
4. Admin Panel: System oversight and configuration
5. Notification System: Real-time updates via email/SMS/push notifications

🚀 Getting Started

Prerequisites

• Node.js (v18+)
• MongoDB (v6+) or PostgreSQL
• Python (v3.9+)
• npm or yarn

Quick Installation

See detailed setup instructions in SETUP.md

# Clone the repository
git clone https://github.com/Unique-45/SEC_Project.git
cd SEC_Project

# Backend setup
cd backend
npm install
cp .env.example .env
# Edit .env with your configuration
npm run dev

# AI Service setup (in new terminal)
cd ai-model
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate
pip install -r requirements.txt
python app.py

# Frontend setup (in new terminal)
cd frontend
npm install
cp .env.example .env.local
npm run dev

Access the Application

• Frontend: http://localhost:3000
• Backend API: http://localhost:5000
• AI Service: http://localhost:8000
• API Documentation: http://localhost:5000/api-docs (coming soon)

📋 Usage

For Citizens

1. Register/Login to the platform
2. Submit a complaint with details and photo evidence
3. Receive AI verification results
4. Track complaint status
5. Confirm resolution and provide feedback

For Government Departments

1. Access assigned complaints
2. Update status and actions taken
3. Mark issues as resolved
4. Communicate with citizens

For Administrators

1. Monitor system performance
2. Manage departments and users
3. Review AI accuracy metrics
4. Handle escalations

🎯 Roadmap

✅ Completed (Phase 1)

• Project setup and architecture design
• Database schema design (5 models)
• User authentication system (JWT)
• Complaint submission API with image upload
• AI verification service framework
• Department routing system
• Notification service (email)
• Reward/penalty mechanism
• Frontend application (Next.js)
• Landing page and basic UI

🚧 In Progress (Phase 2)

• Complete frontend pages (dashboard, forms)
• AI model training with real data
• Advanced image verification
• Real-time notifications (WebSockets)

📝 Planned (Phase 3)

• Mobile responsive optimization
• Comprehensive testing suite
• API documentation (Swagger)
• Admin analytics dashboard
• Production deployment
• Performance monitoring
• Mobile app (React Native)

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

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

� Project Structure

SEC_Project/
├── backend/              # Node.js/Express REST API
│   ├── src/
│   │   ├── controllers/  # Route controllers
│   │   ├── models/       # Mongoose models
│   │   ├── routes/       # API routes
│   │   ├── services/     # Business logic
│   │   ├── middleware/   # Auth, validation
│   │   └── server.js     # Entry point
│   └── README.md
│
├── frontend/             # Next.js 14 React app
│   ├── src/
│   │   ├── app/         # App router pages
│   │   ├── components/  # React components
│   │   ├── services/    # API integration
│   │   └── lib/         # Utilities
│   └── README.md
│
├── ai-model/            # Python Flask AI service
│   ├── services/        # Verification modules
│   ├── app.py          # Flask app
│   └── README.md
│
├── README.md           # Main documentation
└── SETUP.md           # Setup instructions

📚 Documentation

• SETUP.md - Comprehensive setup guide
• backend/README.md - Backend API documentation
• frontend/README.md - Frontend documentation
• ai-model/README.md - AI service documentation

🔐 Security Features

• JWT authentication with refresh tokens
• Password hashing with bcrypt
• Input validation and sanitization
• File upload restrictions
• CORS configuration
• Helmet.js security headers
• Rate limiting (ready to implement)

🧪 Testing

# Backend tests
cd backend
npm test

# Frontend tests
cd frontend
npm test

# AI service tests
cd ai-model
pytest tests/

�👥 Team

Project developed by the SEC_Project team.

📞 Contact

For questions or suggestions, please open an issue in the repository.

🙏 Acknowledgments

• MongoDB for database
• OpenAI for AI inspiration
• TailwindCSS for styling
• Next.js team for the framework

---

Status: ✅ Core implementation complete | 🚧 Frontend UI in progress | 🎯 Ready for AI model training

Last Updated: October 21, 2025