408 lines
12 KiB
Markdown
408 lines
12 KiB
Markdown
# 🏗️ CityPulse - Smart Citizen-Driven Urban Maintenance Platform
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CityPulse is a comprehensive citizen reporting application that combines **Flutter frontend** with **Python FastAPI backend** and **AI-powered image classification**. Users can capture urban issues (potholes, broken streetlights, trash, etc.), get automatic AI classification, and track their reports through a complete management system.
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## 🎯 System Architecture
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### Frontend (Flutterrr)
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- **Location**: Root directory
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- **Technology**: Flutter (Dart) with Material Design
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- **Purpose**: Cross-platform mobile and web interface for citizens
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- **Features**: Camera integration, GPS location, map visualization, bilingual support (EN/BM)
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### Backend (Python FastAPI)
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- **Location**: `backend/` directory
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- **Technology**: Python FastAPI with SQLAlchemy + SQLite
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- **Purpose**: RESTful API server with AI-powered image classification
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- **Features**: YOLO-based object detection, severity classification, ticket management
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### Data Flow
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```
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User takes photo → Flutter App → FastAPI Backend → AI Analysis → Database
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↓ ↓ ↓ ↓ ↓
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Reports List ←────── API Calls ←─── HTTP/REST ──→ YOLO Model ─→ SQLite
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```
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## 🚀 Quick Start Guide
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### Prerequisites
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- **Flutter SDK** 3.8.1+ ([Install Guide](https://docs.flutter.dev/get-started/install))
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- **Python** 3.11+ ([Install Guide](https://python.org/downloads/))
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- **Git** for version control
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### 1. Clone and Setup
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```bash
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git clone <your-repo-url>
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cd fixmate-frontend
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```
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### 2. Install Flutter Dependencies
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```bash
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flutter pub get
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```
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### 3. Setup Backend
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```bash
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cd backend
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pip install -r requirements.txt
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```
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### 4. Start Backend Server (Terminal 1)
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```bash
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cd backend
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python main.py
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```
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✅ Backend will run on: `http://127.0.0.1:8000`
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### 5. Start Flutter App (Terminal 2)
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```bash
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# Navigate back to project root
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cd ..
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# Start Flutter app (choose your target)
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flutter run # Mobile (Android/iOS)
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# OR
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flutter run -d chrome # Web (Chrome)
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# OR
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flutter run -d web-server # Web Server
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```
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## 🔧 Alternative Startup Methods
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### Method A: Backend Only
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```bash
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cd backend
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python main.py
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```
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### Method B: Using Uvicorn (Alternative)
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```bash
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cd backend
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uvicorn main:app --host 127.0.0.1 --port 8000 --reload
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```
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### Method C: Flutter Web (Web Version)
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```bash
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flutter run -d chrome # or firefox, edge
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```
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### Method D: Development Mode (Hot Reload)
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```bash
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# Terminal 1 - Backend with auto-reload
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cd backend
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uvicorn main:app --reload
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# Terminal 2 - Flutter with hot reload
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flutter run
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```
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### Method E: Dashboard Access (Web Interface)
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```bash
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# Terminal 1 - Start Backend Server
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cd backend
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python main.py
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# OR (if port conflicts occur):
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uvicorn main:app --host 127.0.0.1 --port 8000 --reload
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# Terminal 2 - Start Dashboard Server
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cd dashboard
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python -m http.server 3000
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# Open browser and navigate to:
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# http://localhost:3000
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```
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**Dashboard Features:**
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- 🗺️ Interactive map with report visualization
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- 🔍 Advanced filtering by category, severity, status, and date
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- 📊 Real-time statistics and analytics
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- 🌡️ Heatmap toggle for density visualization
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- 🔄 Status management (submitted → in_progress → fixed)
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- 📱 Responsive design for desktop and mobile
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- 🌍 Bilingual support (English/Bahasa Malaysia)
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**Troubleshooting Dashboard:**
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- **Port 8000 in use?** Try: `uvicorn main:app --host 127.0.0.1 --port 8080 --reload` (then update dashboard to use port 8080)
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- **Port 3000 in use?** Try: `python -m http.server 3001`
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- **Backend connection fails?** Dashboard will automatically use demo data
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- **CORS issues?** Ensure backend allows requests from `http://localhost:3000`
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## 📱 API Endpoints
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The Flutter app communicates with these backend endpoints:
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| Endpoint | Method | Purpose |
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|----------|--------|---------|
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| `/api/tickets` | GET | Fetch all reports |
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| `/api/report` | POST | Submit new report with image |
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| `/api/tickets/{id}` | GET | Get specific report |
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| `/api/tickets/{id}` | PATCH | Update report status |
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| `/api/analytics` | GET | Get dashboard analytics |
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| `/api/users` | POST | Create user account |
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### API Documentation
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View interactive API documentation at: `http://127.0.0.1:8000/docs`
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---
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## 🎮 Features Overview
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### Flutter Frontend Features
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- ✅ **Report Flow**: Camera/gallery photo capture with GPS location
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- ✅ **AI Classification**: Automatic issue type and severity detection
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- ✅ **Map View**: Interactive OpenStreetMap with clustering and filtering
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- ✅ **Report Management**: View, edit, and track report status
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- ✅ **Bilingual Support**: English and Bahasa Malaysia
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- ✅ **Settings**: Language toggle and data management
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### Backend AI Features
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- ✅ **YOLO Object Detection**: Detects urban issues from images
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- ✅ **Severity Classification**: ML model assesses issue severity
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- ✅ **SQLite Database**: Local data storage with full CRUD operations
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- ✅ **RESTful API**: Complete API for mobile app integration
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- ✅ **File Upload**: Image storage and processing
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## 📁 Project Structure
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### Frontend (Flutter)
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```
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lib/
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├── app.dart # Main app widget and routing
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├── main.dart # App entry point
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├── models/
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│ ├── report.dart # Report data model
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│ └── enums.dart # Category, severity, status enums
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├── screens/
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│ ├── report_flow/ # Photo capture flow
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│ ├── map/ # Map visualization screen
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│ ├── my_reports/ # User reports management
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│ └── settings/ # App settings
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├── services/
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│ ├── api_service.dart # Backend API communication
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│ ├── storage.dart # Local data storage
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│ ├── location_service.dart # GPS location services
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│ └── mock_ai.dart # AI classification logic
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├── theme/
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│ └── themes.dart # App theming
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├── widgets/ # Reusable UI components
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└── l10n/ # Internationalization
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```
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### Backend (Python)
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```
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backend/
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├── main.py # FastAPI server entry point
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├── requirements.txt # Python dependencies
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├── app/
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│ ├── database.py # SQLite database setup
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│ ├── models/ # Database models
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│ ├── routes/ # API route handlers
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│ ├── services/ # Business logic and AI services
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│ ├── schemas/ # Pydantic data models
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│ └── static/uploads/ # Image storage
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└── test/ # Test files and utilities
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```
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## 🛠️ Technology Stack
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### Frontend Technology Stack
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- **Flutter**: 3.8.1+ with Material Design
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- **Key Packages**:
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- `flutter_map` + `flutter_map_marker_cluster` (Interactive maps)
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- `geolocator` (GPS location services)
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- `image_picker` (Camera integration)
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- `http` (API communication)
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- `provider` (State management)
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- `shared_preferences` (Local storage)
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### Backend Technology Stack
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- **FastAPI**: 0.117.1+ (Modern Python web framework)
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- **SQLAlchemy**: 2.0.43+ (ORM for database operations)
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- **PyTorch**: 2.8.0+ (Machine learning framework)
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- **Ultralytics YOLO**: 8.3.203+ (Object detection)
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- **SQLite**: Local database for data persistence
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### AI Models
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- **Object Detection**: YOLOv12n for issue identification
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- **Severity Classification**: Custom PyTorch model
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- **Model Storage**: `backend/app/models/` directory
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## 🛠️ Troubleshooting
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### Backend Issues
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**Port 8000 already in use:**
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```bash
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# Windows
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netstat -ano | findstr :8000
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taskkill /F /IM python.exe
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# Alternative: Kill specific process
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Get-Process -Name python | Stop-Process -Force
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```
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**Missing dependencies:**
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```bash
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cd backend
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pip install -r requirements.txt
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pip install python-multipart pydantic[email]
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```
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**Backend not starting:**
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```bash
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# Test if modules can be imported
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cd backend
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python -c "import main; print('Import successful')"
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```
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### Frontend Issues
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**Flutter dependencies:**
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```bash
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flutter clean
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flutter pub get
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```
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**Device connection issues:**
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```bash
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flutter devices # List connected devices
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flutter doctor # Check Flutter installation
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```
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**Web-specific issues:**
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```bash
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flutter config --enable-web
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```
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### Common Issues
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**"Connection refused" errors:**
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- Ensure backend server is running on port 8000
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- Check firewall settings
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- Verify API base URL in `lib/services/api_service.dart`
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- For dashboard: Check browser console for CORS errors
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**Camera/Geolocation not working:**
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- Grant permissions in device settings
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- Use HTTPS for web deployment
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- Check browser permissions
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**Slow AI processing:**
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- First startup downloads ML models (may take time)
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- Consider using CPU-only builds for faster startup
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- Check available memory
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## 🧪 Testing & Development
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### Backend Testing
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```bash
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cd backend
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python -m pytest test/ # Run all tests
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python test/check_torch.py # Verify PyTorch setup
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```
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### Flutter Testing
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```bash
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flutter test # Run unit tests
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flutter test --coverage # With coverage report
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```
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### Database Management
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```bash
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cd backend
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python -c "from app.database import engine; print('Database file:', engine.url.database)"
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# Database file: backend/app/db/fixmate.db
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```
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## 📊 Performance Considerations
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### Backend Performance
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- **First Startup**: ML models download (~200MB) - may take several minutes
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- **Memory Usage**: PyTorch models require significant RAM
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- **CPU vs GPU**: CPU-only builds available for compatibility
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- **Database**: SQLite suitable for small-scale deployments
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### Frontend Performance
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- **Image Processing**: Images compressed before upload
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- **Map Rendering**: Clustering optimizes marker display
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- **Caching**: Local storage for offline functionality
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## 🚀 Production Deployment
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### Backend Deployment
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```bash
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cd backend
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# Production server
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uvicorn main:app --host 0.0.0.0 --port 8000 --workers 4
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# Or with Gunicorn
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gunicorn main:app -w 4 -k uvicorn.workers.UvicornWorker
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```
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### Flutter Deployment
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```bash
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# Build for production
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flutter build apk --release # Android
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flutter build ios --release # iOS
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flutter build web --release # Web
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# Build for specific targets
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flutter build appbundle # Android App Bundle
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flutter build ipa # iOS Archive
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```
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## 📚 Key Files Reference
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### Essential Flutter Files
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- `lib/main.dart` - App entry point
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- `lib/app.dart` - Main app widget and navigation
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- `lib/services/api_service.dart` - Backend communication
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- `lib/models/report.dart` - Data models
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- `pubspec.yaml` - Flutter dependencies
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### Essential Backend Files
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- `backend/main.py` - FastAPI server
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- `backend/app/database.py` - Database configuration
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- `backend/app/routes/tickets.py` - Ticket API endpoints
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- `backend/app/services/ai_service.py` - AI classification logic
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- `backend/requirements.txt` - Python dependencies
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## 🎯 Future Enhancements
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### Planned Features
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- [ ] Real-time notifications for status updates
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- [ ] Advanced filtering and search capabilities
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- [ ] User authentication and profiles
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- [ ] Admin dashboard for report management
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- [ ] Push notifications for mobile
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- [ ] Offline mode with sync capabilities
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- [ ] Multi-language support expansion
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- [ ] Analytics and reporting dashboard
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### Technical Improvements
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- [ ] Database optimization for large datasets
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- [ ] Caching layer implementation
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- [ ] API rate limiting
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- [ ] Image compression optimization
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- [ ] Background processing for AI tasks
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- [ ] Monitoring and logging enhancement
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## 📄 License & Acknowledgments
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### License
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- Placeholder: Add appropriate license for your project
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### Acknowledgments
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- **OpenStreetMap** - Map data and tile services
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- **Leaflet** - Interactive mapping library
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- **Flutter Community** - Dart packages and plugins
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- **Ultralytics** - YOLO implementation
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- **PyTorch** - Machine learning framework
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- **FastAPI** - Modern Python web framework
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### References
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1. [Flutter Documentation](https://docs.flutter.dev/)
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2. [FastAPI Documentation](https://fastapi.tiangolo.com/)
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3. [YOLOv12 Implementation](https://github.com/ultralytics/ultralytics)
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4. [PyTorch Models](https://pytorch.org/)
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