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GDG-TechSprint

🏛️ CivicFix AI

A transparent, scalable, and citizen-first civic engagement platform designed to streamline complaint reporting, enhance community participation, and improve governance through data-driven prioritization.


🌐 Live Deployment

Live Demo: https://civic-fix-ai-eight.vercel.app


🌟 Overview

CivicFix AI bridges the gap between citizens and local authorities by providing a unified digital platform for reporting civic issues, tracking resolutions, and prioritizing problems through community voting.

The platform promotes accountability, transparency, and data-driven governance, ensuring that critical civic problems receive the attention they deserve.


🧩 Problem Statement

Urban governance systems often suffer from:

  • Manual and opaque complaint redressal processes
  • No clear prioritization of urgent civic issues
  • Low citizen engagement after complaint submission
  • Inefficient communication between citizens and authorities

CivicFix AI addresses these gaps by digitizing complaints, introducing democratic prioritization via voting, and empowering authorities with structured dashboards and analytics.


🎯 Core Functionality

🧱 Basic Features

  • Citizen Complaint Reporting
    Submit complaints with descriptions, images, and precise geo-location.

  • Role-Based Authentication
    Secure JWT-based authentication for Citizens, Authorities, and Admins.

  • Complaint Lifecycle Tracking
    Track complaints through Pending, In Progress, and Resolved states.

  • Community Voting System
    One-vote-per-user mechanism to prioritize high-impact issues.


⚙️ Advanced Features

  • 📍 Location-Based Filtering
    Ward-wise and area-wise complaint views for authorities.

  • 📊 Priority Analytics
    Ranking of complaints based on votes and engagement metrics.

  • 🖼️ Secure Image Uploads
    Media storage and optimization using Cloudinary.

  • 🧩 Clean Backend Architecture
    Modular structure with Controllers, Services, Middlewares, and Utilities.


🤖 System & Technical Capabilities

  • JWT + Role Guards for fine-grained access control
  • Vote Deduplication enforced via database-level indexing
  • Centralized Error Handling using ApiError and ApiResponse
  • Scalable MongoDB Schema Design for high-volume civic data

🎨 User Experience

  • 📱 Fully Responsive UI for mobile, tablet, and desktop
  • ⚡ Fast State Management using Zustand
  • 🧭 Intuitive Workflows from complaint creation to resolution tracking
  • 🗺️ Interactive Maps for visualizing complaint locations

🧠 Tech Stack

🎨 Frontend

  • React 19 + Vite
  • Tailwind CSS
  • Zustand (state management)
  • Axios
  • Leaflet & React Leaflet
  • Google OAuth (@react-oauth/google)
  • Recharts (analytics & charts)
  • Lucide React (icons)
  • React Hot Toast (notifications)

⚙️ Backend

  • Node.js & Express.js (v5)
  • MongoDB & Mongoose
  • JWT Authentication
  • bcrypt (password hashing)
  • Cloudinary (media storage)
  • Multer & Multer-Cloudinary
  • Nodemailer (email services)
  • OpenAI API
  • UUID
  • dotenv, CORS, Cookie Parser

☁️ Google Technologies Used

This project integrates multiple Google-powered technologies to enhance authentication, mapping, and AI-driven analysis:

  • Google OAuth 2.0
    Secure and seamless authentication for users using Google accounts.

  • Google Cloud Vision API
    AI-powered image analysis for validating and categorizing complaint images.

  • Google Auth Library
    Secure token verification and authentication handling on the backend.

These technologies collectively improve security, accuracy, and user experience while ensuring enterprise-grade reliability.


🚀 Setup & Installation

Prerequisites

  • Node.js (v18+ recommended)
  • MongoDB (local or cloud)
  • Cloudinary account
  • Google Cloud project (OAuth, Maps, Vision API enabled)

🧭 Steps

# Clone the repository
git clone https://github.com/your-username/civicfix-ai.git

# Navigate to the project directory
cd civicfix-ai

# Backend setup
cd backend
npm install
npm run dev

# Frontend setup (new terminal)
cd frontend
npm install
npm run dev

👥 Team

This project was developed collaboratively as a team effort:

  • Pratyush Bhaskar
  • Rudraksh Mall
  • Rajeev Dixit
  • Sahil Bharne

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