🌿 BloomIQ - Smart Crop Analysis Platform

BloomIQ is a production-level, AI-powered crop health monitoring application built with YOLOv8 for real-time flower and fruit stage detection. It combines modern web and mobile technologies to deliver accurate, fast, and visually rich crop analysis.

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📋 Table of Contents

• Features
• Tech Stack
• Architecture
• Prerequisites
• Installation
• Usage
• API Documentation
• Deployment
• Contributing

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✨ Features

🌿 Home Dashboard

• Beautiful plant-themed interface with natural animations
• Quick stats: weather, total analyses, recent reports
• Quick actions: Analyze Now, View Reports, Check Weather

📸 Crop Analysis

• Upload or capture crop images
• Dual YOLOv8 Model Integration:
  • flower_model.pt - Flower stage detection
  • fruit_model.pt - Fruit stage detection
• Real-time inference and stage determination
• Confidence levels and health summaries
• Actionable care recommendations

📊 Reports

• Complete analysis history
• Expandable detailed reports
• Detection counts and confidence metrics
• Care recommendations archive

☁️ Weather Insights

• Live weather data (OpenWeatherMap API)
• Temperature, humidity, rainfall probability
• Smart farming recommendations based on conditions
• Watering and fertilization timing suggestions

👤 Authentication

• Email + Password authentication
• JWT-based secure sessions
• Profile management (name, region, language)

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🛠️ Tech Stack

Frontend

• Web: React.js 18
• Mobile: React Native (Android)
• Styling: TailwindCSS
• Animations: Framer Motion (web), React Native Reanimated (mobile)
• HTTP Client: Axios

Backend

• Server: Node.js + Express.js
• Database: SQLite (lightweight, file-based)
• Authentication: JWT (JSON Web Tokens)
• File Upload: Multer

AI/ML

• Framework: Python + Flask
• Model: YOLOv8 (Ultralytics)
• Image Processing: OpenCV, Pillow

APIs

• Weather: OpenWeatherMap API

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🏗️ Architecture

┌─────────────────┐
│   React Web     │
│   React Native  │
└────────┬────────┘
         │ HTTP/REST
         ▼
┌─────────────────┐
│  Node.js Server │
│   (Express.js)  │
└────┬───────┬────┘
     │       │
     │       └──────────────┐
     ▼                      ▼
┌─────────┐        ┌────────────────┐
│ SQLite  │        │ Python Service │
│   DB    │        │   (YOLOv8)     │
└─────────┘        └────────────────┘

Inference Flow

1. User uploads image → Express server
2. Server sends image → Python Flask service
3. Python loads both models:
   • flower_model.pt
   • fruit_model.pt
4. Both models run inference
5. System compares confidence scores
6. Returns dominant stage (Flower/Fruit) + recommendations
7. Server stores result in database
8. Client displays analysis

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📦 Prerequisites

General

• Node.js 16.x or higher
• Python 3.9 or higher
• npm or yarn
• pip (Python package manager)

For Mobile (Optional)

• React Native CLI
• Android Studio (for Android development)
• Java JDK 11 or higher

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🚀 Installation

1. Clone the Repository

git clone <repository-url>
cd BloomIQ-v4

2. Backend Setup

Install Node.js Dependencies

cd backend
npm install

Install Python Dependencies

cd python-service
pip install -r requirements.txt
cd ..

Configure Environment Variables

cp .env.example .env

Edit .env:

PORT=5000
JWT_SECRET=your-super-secret-jwt-key-change-this
PYTHON_SERVICE_URL=http://localhost:8000
WEATHER_API_KEY=your-openweathermap-api-key

Add YOLOv8 Models

Place your trained models in backend/models/:

• flower_model.pt
• fruit_model.pt

Note: If models are missing, the system uses YOLOv8n as fallback.

3. Web Frontend Setup

cd ../web
npm install

Create .env:

cp .env.example .env

Edit .env:

REACT_APP_API_URL=http://localhost:5000/api

4. Mobile Setup (Optional)

cd ../mobile
npm install

For Android:

npx react-native run-android

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🎯 Usage

Start All Services

Terminal 1: Node.js Backend

cd backend
npm run dev

Server runs on http://localhost:5000

Terminal 2: Python Inference Service

cd backend/python-service
python app.py

Service runs on http://localhost:8000

Terminal 3: React Web App

cd web
npm start

App opens at http://localhost:3000

Using the Application

1. Register/Login: Create account or sign in
2. Dashboard: View stats and weather
3. Analyze: Upload/capture crop image
4. Results: View stage, confidence, recommendations
5. Reports: Check analysis history
6. Weather: Get farming recommendations

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📡 API Documentation

Authentication

Register

POST /api/auth/register
Content-Type: application/json

{
  "email": "[email protected]",
  "password": "password123",
  "name": "John Doe",
  "region": "California",
  "language": "en"
}

Login

POST /api/auth/login
Content-Type: application/json

{
  "email": "[email protected]",
  "password": "password123"
}

Analysis

Analyze Crop

POST /api/analysis/analyze
Authorization: Bearer <token>
Content-Type: multipart/form-data

image: <file>

Response:

{
  "reportId": "uuid",
  "stage": "Flower",
  "confidence": 0.89,
  "detections": [...],
  "health_summary": "Detected 3 flowers...",
  "recommendations": ["Ensure pollination", ...],
  "imageUrl": "http://..."
}

Weather

Get Current Weather

GET /api/weather/current?city=California
Authorization: Bearer <token>

Reports

Get All Reports

GET /api/reports
Authorization: Bearer <token>

Get Report by ID

GET /api/reports/:id
Authorization: Bearer <token>

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🌐 Deployment

Backend (Node.js + Python)

Option 1: Traditional Server

# Install PM2
npm install -g pm2

# Start Node.js
cd backend
pm2 start server.js --name bloomiq-backend

# Start Python (separate process)
cd python-service
pm2 start app.py --name bloomiq-python --interpreter python3

Option 2: Docker

# Example Dockerfile for backend
FROM node:18
WORKDIR /app
COPY package*.json ./
RUN npm install --production
COPY . .
EXPOSE 5000
CMD ["node", "server.js"]

Frontend

Web (React)

cd web
npm run build
# Deploy 'build' folder to:
# - Vercel
# - Netlify
# - AWS S3 + CloudFront
# - GitHub Pages

Mobile (React Native)

cd mobile
# Android
npx react-native build-android --release

# Generate APK in android/app/build/outputs/apk/release/

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🔧 Troubleshooting

Python Service Not Connecting

# Check if service is running
curl http://localhost:8000/health

# Restart service
cd backend/python-service
python app.py

Models Not Loading

• Ensure flower_model.pt and fruit_model.pt are in backend/models/
• Check file permissions
• Verify PyTorch and Ultralytics are installed

Database Issues

# Reset database
cd backend
rm database.sqlite
npm run dev  # Recreates tables

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📝 License

MIT License - See LICENSE file

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🤝 Contributing

1. Fork the repository
2. Create feature branch (git checkout -b feature/AmazingFeature)
3. Commit changes (git commit -m 'Add AmazingFeature')
4. Push to branch (git push origin feature/AmazingFeature)
5. Open Pull Request

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📞 Support

For issues and questions:

• Open a GitHub Issue
• Email: [email protected]

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🌟 Acknowledgments

• Ultralytics YOLOv8 - Object detection framework
• OpenWeatherMap - Weather data API
• React Team - Frontend framework
• Express.js - Backend framework

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Made with 🌱 by the BloomIQ Team