Inspiration

Civic issues such as potholes, garbage, drainage problems, broken streetlights, and water-related issues are common in communities. Reporting these problems often requires users to manually describe the issue and decide how urgent it is.

CivicAlert AI was built to make civic issue reporting simpler and more intelligent by using AI to analyze reported problems and help organize them for better follow-up.

What the Project Does

CivicAlert AI is an AI-powered civic issue reporting and management platform.

Users can upload a photo of a civic problem and provide its location. The system uses AI to analyze the image and identify:

  • The type of civic issue
  • Issue severity
  • A short explanation of the problem
  • The reported location

The platform also provides additional intelligence for issue management.

Key Features

AI Image Analysis

Users can upload an image of a civic problem. The AI analyzes the image and classifies the issue into categories such as:

  • Road
  • Garbage
  • Water
  • Electricity
  • Streetlight
  • Drainage
  • Other

It also estimates the severity as low, medium, or high.

Priority Scoring

CivicAlert AI calculates a priority score based on issue severity and category.

The system converts the result into:

  • Low priority
  • Medium priority
  • High priority

This helps identify issues that may require earlier attention.

Duplicate Issue Detection

The platform checks existing reports using category, location, and title similarity.

This helps identify potentially repeated reports about the same or a similar civic problem.

AI Complaint Generation

Based on the analyzed issue, location, severity, and explanation, the system can generate a concise and professional civic complaint.

Issue Management

Reported issues can be tracked through different statuses:

  • Pending
  • In Progress
  • Resolved

Dashboard

The dashboard provides an overview of reported issues, including:

  • Total issues
  • High-severity issues
  • Pending issues
  • Reported locations
  • Category analytics
  • Recent community issues

Search and Filtering

Users can search issues and filter them by severity and status.

How I Built It

The frontend was developed using React and Vite.

The backend was built with FastAPI and provides REST API endpoints for issue reporting, image upload, AI analysis, priority scoring, duplicate detection, complaint generation, and status management.

Supabase is used for database storage and image storage.

Groq-powered AI models are used for image analysis and complaint generation.

The frontend is deployed on Vercel and the backend is deployed on Render.

Architecture

User
  ↓
React + Vite Frontend
  ↓
FastAPI Backend
  ↓
AI Analysis / Business Logic
  ↓
Supabase Database & Storage
  ↓
Issue Management Inspiration

Challenges
One of the main challenges was connecting AI analysis with real application workflows.
The project needed to handle image uploads, AI-generated results, database storage, duplicate detection, priority calculation, and issue status management while keeping the user experience simple.
Another challenge was making AI responses structured and reliable enough to be used directly by the application.
What I Learned
Through this project, I worked with:
FastAPI REST APIs
React frontend integration
Supabase database and storage
AI-powered image analysis
Structured JSON responses from AI models
Duplicate detection logic
Priority scoring
AI-generated complaint workflows
Full-stack deployment using Vercel and Render
Future Improvements
Future versions could include:
Real-time notifications
Map-based issue visualization
More advanced duplicate detection using embeddings
Government department routing
User authentication and roles
Email and notification integration
Historical issue analytics
AI-powered resolution recommendations
Project Links
Frontend: https://civic-alert-ai-frontend.vercel.app/⁠�
Backend: https://civicalert-ai.onrender.com/⁠�
GitHub: https://github.com/santoshml-lab/CivicAlert-AI-Frontend⁠�


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