Civic Problem Reporter with AI-Powered Classification
Citizens encounter civic issues like potholes, garbage dumps, water leaks, and broken streetlights daily, but face challenges in:
- Lack of accessible reporting channels - Most people don't know where to complain
- Poor response from authorities - Issues remain unaddressed until multiple complaints are filed
- Zero transparency - No tracking or status updates on reported problems
- Complex reporting processes - Platforms like CPGRAMS require extensive documentation
- Language barriers - Limited multilingual support for diverse communities
A comprehensive web and mobile platform that democratizes civic problem reporting through:
- πΈ One-Click Reporting: Upload photo + location with optional description
- π€ AI-Powered Classification: Automatic problem categorization using computer vision
- πΊοΈ Interactive Problem Mapping: Location-based visualization of civic issues
- π Community Validation: Upvoting system for issue priority ranking
- π Real-time Tracking: Status updates from Unresolved β In Progress β Resolved
- π¬ Community Engagement: Comments and feedback on reported problems
- π Multilingual Support: Available in English, Hindi, Bengali, Marathi, Tamil, Telugu
- π Secure Authentication: OTP-based passwordless login system
- ποΈ Centralized Issue Management: View all reported problems on interactive maps
- β‘ Quick Status Updates: Mark issues as resolved or in-progress
- π Analytics Dashboard: Track resolution rates and community engagement
- π CPGRAMS Integration: Direct escalation to official government portals
- Framework: React.js + Vite (fast development & optimized builds)
- Mapping: Leaflet + OpenStreetMap (open-source mapping solution)
- Geolocation: IP-API + LocationIQ (accurate location detection)
- Styling: Modern responsive design with mobile-first approach
- Runtime: Node.js + Express.js (scalable server architecture)
- Database: MongoDB Atlas (cloud-native document database)
- Image Storage: Cloudinary CDN (optimized image delivery)
- Authentication: JWT tokens in HTTP-only cookies + OTP verification
- Model: Custom-trained EfficientNet-Lite0 / MobileNetV3-Small
- Framework: TensorFlow Lite (mobile-optimized inference)
- Categories: Automatic classification of civic issues (potholes, garbage, lighting, water, etc.)
- Platform: Native Android (Java + XML)
- Features: Camera integration, GPS location, offline capability
POST /api/report # Submit new civic issue
GET /api/issues # Fetch nearby issues
POST /api/issues/:id/upvote # Upvote existing issue
POST /api/issues/:id/comment # Add comment to issue
POST /api/classify # AI model classification
GET /api/admin/issues # Fetch all pending issues
POST /api/admin/issues/:id/status # Update issue status
GET /api/admin/analytics # Get resolution metrics
POST /api/auth/signup # User registration with OTP
POST /api/auth/login # OTP-based login
POST /api/auth/verify-otp # OTP verification
POST /api/auth/logout # Secure logout
graph TD
A[User uploads photo] --> B[Location detection]
B --> C[AI classification]
C --> D[Store in MongoDB]
D --> E[Display on map]
- Users can upvote similar issues they've encountered
- Comments provide additional context and updates
- Popular issues get higher visibility and priority
- Admins review issues on centralized dashboard
- Status updates notify community of progress
- Integration with CPGRAMS for official escalation
- Node.js 18+ and npm/yarn
- MongoDB Atlas account
- Cloudinary account
- LocationIQ API key
cd backend
npm install
cp .env.example .env # Configure environment variables
npm run devcd frontend
npm install
npm run devMONGODB_URI=your_mongodb_connection_string
CLOUDINARY_URL=your_cloudinary_url
LOCATIONIQ_API_KEY=your_locationiq_key
JWT_SECRET=your_jwt_secret
OTP_SERVICE_KEY=your_otp_service_keyThe Android app provides native mobile experience with:
- Camera Integration: Direct photo capture for issue reporting
- GPS Location: Automatic location detection and manual address input
- Offline Mode: Queue reports when internet is unavailable
- Push Notifications: Updates on reported issue status
- Custom Training: Model trained on Indian civic infrastructure dataset
- Multi-category Detection: Potholes, garbage, street lights, water issues, etc.
- Confidence Scoring: Ensures accurate categorization
- Continuous Learning: Model improves with community feedback
- Automated Escalation: Issues with high upvotes auto-escalate after 5 days
- CPGRAMS Integration: Direct submission to government grievance portal
- Multi-level Authorities: Route to appropriate municipal departments
- Hotspot Detection: Identify areas with frequent civic issues
- Resolution Metrics: Track government response times
- Community Engagement: Monitor user participation and feedback
- Immutable issue tracking and resolution verification
- Transparent fund allocation for civic improvements
- Community-driven governance mechanisms
- Reward System: Points and badges for active community members
- Leaderboards: Recognize top contributors and issue reporters
- Municipal Partnerships: Official collaboration with local governments
- Real-time Translation: Automatic translation of reports across all supported languages
- Progress Verification: AI-powered verification of issue resolution
- Predictive Analytics: Forecast potential civic problems before they occur
- Direct Hiring: Connect communities with verified cleaners and fixers
- Service Ratings: Community-driven quality assurance
- Emergency Response: Priority routing for urgent civic issues
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AI-First Approach: Automated issue classification reduces manual effort
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Community-Driven: Upvoting system ensures democratic prioritization
-
Multilingual by Design: Serves India's diverse linguistic communities
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Government Integration: Direct pipeline to official grievance channels
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Mobile-Optimized: Lightweight AI models for real-time mobile inference
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Passwordless Security: OTP-based authentication reduces security vulnerabilities
FixMyNagar - Because every neighborhood deserves better infrastructure! ποΈβ¨