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It is an innovative app that integrates a YOLOv5-based machine learning model that automatically detects problems in images in real time and generates automated reports to local authorities. #FlutterApp #AI/ML #SmartCity #YOLOv5

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🏙️ Fix-The-City

AI-Enhanced Smart Community Complaint Application

Typing SVG

Made with FlutterPowered by DartFirebasePythonYOLOv5


VersionLicenseStatusPlatform


🎯 Empowering Citizens to Build Better Communities Through Technology


📋 Table of Contents


🌟 Overview

Fix-The-City is a cutting-edge mobile application that revolutionizes civic engagement by enabling citizens to report community issues efficiently. Leveraging the power of artificial intelligence and real-time processing, the app bridges the gap between citizens and municipal authorities, ensuring faster resolution of infrastructure problems.

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🎓 Final Year Project

Project Name: AI-Enhanced Smart Community Complaint Application
Application Name: Fix-The-City
Domain: Smart City Solutions | AI/ML | Mobile Application Development


🔥 Problem Statement

Traditional complaint submission systems are plagued with:

  • ❌ Lengthy bureaucratic processes
  • ❌ Lack of real-time tracking and transparency
  • ❌ Manual verification and classification delays
  • ❌ Poor communication between citizens and authorities
  • ❌ Difficulty in prioritizing urgent issues
  • ❌ Limited citizen engagement and accountability

Fix-The-City eliminates these challenges through intelligent automation, real-time updates, and community-driven problem-solving.


📸 Shots

Colorful QR Example 1Colorful QR Example 2

✨ Key Features

👤 User Features

🎨 Intuitive Dashboard

  • At-a-Glance Metrics: View total reported issues, in-progress complaints, and resolved cases
  • Visual Analytics: Beautiful charts and statistics for community impact
  • Quick Actions: Fast access to submit new complaints or view recent activities

📱 Dual Reporting Modes

  • Basic Mode: Manual entry with image upload
  • Advanced Mode (AI-Powered): Upload image → Auto-detection → Auto-generated report
    • Instant problem classification
    • Automatic severity assessment
    • Location tagging with GPS integration

🗂️ Comprehensive Complaint History

  • Status Indicators: Resolved, In Progress, Pending
  • Detailed Information: Ticket number, submission date/time, ETA
  • Priority Levels: High (Red), Medium (Orange), Low (Green)
  • Withdraw Option: Cancel complaints before processing

🎬 Preview 1

Experience a sleek splash screen, seamless login, and an intuitive dashboard for automated complaint categorization with smart detection and location tagging for easy submission.

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FLow2.mp4
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📍 Advanced Complaint Tracking

  • Full Timeline View: Track every status update from submission to resolution
  • Category Classification: Potholes, cracks, open manholes, traffic lights, waste containers, stray animals
  • Location Mapping: Interactive maps showing exact problem locations
  • Photo Documentation: Before and after images of reported issues

🌐 Community Feed (Social Feature)

  • Real-Time Updates: See complaints submitted by fellow citizens (displayed as "Anonymous User")
  • Engagement Tools: Like, comment, and share complaints on social platforms
  • Community Awareness: Foster collective responsibility and civic participation
  • Viral Potential: Share urgent issues to gain quick attention

🔐 Robust Verification System

Two-step verification to prevent fake complaints:

  1. General Details: Name, contact information, address
  2. Official Document Verification:
    • Adults: Government-issued citizenship card
    • Minors: School ID card

Only verified users can submit complaints.

📸 Key shots

Welcome ScreenFeatures ScreenAnalytics ScreenSecurity Screen

📰 Additional Features

  • News Section: Stay updated with local community news and announcements
  • Emergency Contacts: Quick access to police, ambulance, fire department, municipality
  • Feedback System: Rate and review complaint resolution quality

🔧 Admin Features

📊 Comprehensive Dashboard

  • Priority Queue: High-priority complaints highlighted at the top
  • Status Overview: Pending, in-progress, and resolved complaint counts
  • Analytics: Graphical representation of complaint trends and resolution rates

🛠️ Complaint Management

  • Detailed Review: Access to all complaint details including images, location, and user information
  • Status Updates:
    • Task Assigned
    • Staff On-Site
    • In Progress
    • Resolved
    • Withdrawn
    • Custom Notes
  • Location Verification: Integrated map view to verify exact problem locations
  • Priority Assignment: Set urgency levels for efficient resource allocation

👥 User Management

  • Real-Time Statistics: Total users, verified users, pending verifications
  • Verification Review: Approve or reject user verification documents
  • User Details: Access to user profiles, complaint history, and engagement metrics

💬 Feedback & Reviews

  • User Feedback: View and respond to citizen feedback
  • Performance Monitoring: Track resolution times and user satisfaction
  • Quality Assurance: Ensure timely and effective problem resolution

🎬 Preview 2

Leverage advanced AI for complaint categorization, access comprehensive complaint history, and enjoy real-time tracking with an interactive progress timeline

Advanced.AI.mp4
Flow4.mp4
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🤖 AI Integration

Custom YOLOv5 Object Detection Model

At the heart of Fix-The-City's intelligence lies a custom-trained YOLOv5 deep learning model that revolutionizes complaint processing.

🎯 Capabilities

  • Real-Time Detection: Instantly identify infrastructure problems in uploaded images
  • Multi-Class Classification: Detect and classify:
    • 🕳️ Potholes
    • 🔨 Road cracks
    • 🚧 Open manholes
    • 🚦 Malfunctioning traffic lights
    • 🗑️ Overflowing waste containers
    • 🐕 Stray animals

Workflow

  1. User uploads an image through the app
  2. Image is processed by the YOLOv5 model
  3. AI detects and highlights all problems in the image
  4. Automatic classification and severity assessment
  5. Pre-filled complaint form generated
  6. User reviews and submits with one tap

🎓 Model Training

  • Trained on thousands of labeled community issue images
  • Continuous learning from new submissions
  • High accuracy and precision rates
  • Optimized for mobile deployment

💡 Benefits

  • ✅ 10x faster complaint submission
  • ✅ Reduced human error in classification
  • ✅ Automated priority assignment
  • ✅ Enhanced data quality for authorities
  • ✅ Improved response times

🎬 Preview 3

Admin dashboard for efficient complaint management and prioritization, complemented by features like news updates and a user-friendly profile screen featuring verified badges.

AdminTask.2.mp4
trackcomplaints.mp4
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🛠️ Technology Stack

Frontend

FlutterDart

Backend & Database

FirebaseFirestoreFirebase Auth

AI/ML

PythonYOLOv5PyTorch

Additional Services

Google MapsCloud Storage


🏗️ System Architecture

┌─────────────────────────────────────────────────────────────┐ │ FLUTTER MOBILE APP │ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ │ │ User Module │ │ Admin Module │ │ AI Module │ │ │ └──────┬───────┘ └──────┬───────┘ └──────┬───────┘ │ │ │ │ │ │ └─────────┼──────────────────┼──────────────────┼──────────────┘ │ │ │ ▼ ▼ ▼ ┌─────────────────────────────────────────────────────────────┐ │ FIREBASE BACKEND │ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ │ │ Authentication│ │ Firestore │ │Cloud Storage │ │ │ └──────────────┘ └──────────────┘ └──────────────┘ │ └─────────────────────────────────────────────────────────────┘ │ │ │ └──────────────────┼──────────────────┘ ▼ ┌─────────────────────────────────────────────────────────────┐ │ PYTHON AI SERVICE (YOLOv5) │ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ │ │Image Processing│ │ Detection │ │Classification│ │ │ └──────────────┘ └──────────────┘ └──────────────┘ │ └─────────────────────────────────────────────────────────────┘ │ ▼ ┌─────────────────────────────────────────────────────────────┐ │ EXTERNAL SERVICES & APIs │ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ │ │ Google Maps │ │ Location GPS │ │ Social Share │ │ │ └──────────────┘ └──────────────┘ └──────────────┘ │ └─────────────────────────────────────────────────────────────┘ 

🚀 User Journey

1️⃣ Registration & Verification

Sign Up → Enter Details → Submit ID Document → Wait for Admin Approval → Account Activated 

2️⃣ Submitting a Complaint

Dashboard → New Complaint → Choose Mode (Basic/Advanced) ↓ Upload Image → AI Detection ↓ Review Auto-Generated Report ↓ Add Description (Optional) ↓ Confirm Location → Submit 

3️⃣ Tracking & Engagement

Complaint Submitted → Receive Ticket Number → Track Progress ↓ Task Assigned → Staff On-Site → In Progress → Resolved ↓ Receive Notification → Rate Experience 

🎛️ Admin Dashboard

Key Responsibilities

📥 Complaint Review

  • Verify complaint authenticity
  • Check location accuracy
  • Review photographic evidence
  • Assess severity and priority

📤 Status Management

  • Assign tasks to field staff
  • Update complaint status in real-time
  • Add custom notes and instructions
  • Mark complaints as resolved

User Verification

  • Review submitted ID documents
  • Approve or reject verification requests
  • Manage user access and permissions

📈 Analytics & Reporting

  • Generate reports on complaint trends
  • Monitor resolution times
  • Track user engagement metrics
  • Identify problem hotspots

💻 Installation

Prerequisites

  • Flutter SDK (v3.0+)
  • Dart SDK (v2.17+)
  • Android Studio / VS Code
  • Firebase account
  • Python 3.8+ (for AI service)

Clone Repository

git clone https://github.com/yourusername/fix-the-city.git cd fix-the-city

Install Dependencies

flutter pub get

Firebase Setup

  1. Create a new Firebase project
  2. Add Android and iOS apps to your Firebase project
  3. Download google-services.json (Android) and GoogleService-Info.plist (iOS)
  4. Place configuration files in respective directories

Python AI Service Setup

cd ai-service pip install -r requirements.txt python app.py

Run Application

flutter run

📖 Usage

For Citizens

  1. Download & Register: Install the app and complete verification
  2. Report Issues: Use basic or AI-powered mode to submit complaints
  3. Track Progress: Monitor your complaint status in real-time
  4. Engage: View community feed, like and share issues
  5. Stay Informed: Access news and emergency contacts

For Administrators

  1. Login to Admin Panel: Access the dedicated admin interface
  2. Review Complaints: Prioritize and assign tasks
  3. Manage Users: Verify new user registrations
  4. Update Status: Keep citizens informed with real-time updates
  5. Generate Reports: Analyze trends and optimize resources

🔮 Future Enhancements

  • Multilingual Support: Add support for regional languages
  • Voice Commands: Report issues using voice input
  • Gamification: Reward active citizens with badges and points
  • Advanced Analytics: Predictive maintenance using historical data
  • AR Integration: Visualize infrastructure issues in augmented reality
  • Chatbot Support: AI-powered virtual assistant for user queries
  • Dark Mode: Enhanced UI with dark theme option
  • Offline Mode: Submit complaints without internet (sync later)
  • IoT Integration: Connect with smart city sensors for automated detection

🤝 Contributing

We welcome contributions from the community! Here's how you can help:

  1. Fork the Repository
  2. Create a Feature Branch
    git checkout -b feature/AmazingFeature
  3. Commit Your Changes
    git commit -m 'Add some AmazingFeature'
  4. Push to Branch
    git push origin feature/AmazingFeature
  5. Open a Pull Request

💬 Connect & Support

For questions, feedback, or collaborations:

GitHubTwitterLinkedInEmail


🌟 Star This Repository!

If you find Fix-The-City useful, please consider giving it a star ⭐

Together, we can build smarter, safer, and more responsive communities!


Made with ❤️ and ☕ by Us

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It is an innovative app that integrates a YOLOv5-based machine learning model that automatically detects problems in images in real time and generates automated reports to local authorities. #FlutterApp #AI/ML #SmartCity #YOLOv5

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