AgriTech is an innovative web platform designed to empower farmers and agricultural communities with AI-powered tools, real-time insights, and interactive collaboration features.

Crop Recommendation	Disease Detection	Community Chat

• Web browser (Chrome, Firefox, Safari, or Edge)
• Local server (for full functionality)

1. Clone the repository

   git clone https://github.com/omroy07/AgriTech.git
   cd AgriTech

Run the application

Option A: Simple HTML Preview

# Open index.html in your browser
open index.html 

Option B: Local Server (Recommended)

# Using Python
python -m http.server 8000
Then visit http://localhost:8000

# Or install live-server: npm install -g live-server

• live-server

• Access the application

• Open your web browser

Navigate to http://localhost:8000 (or the port shown in terminal)

• Start exploring AgriTech features!

See our Contributing Guide for detailed setup instructions, coding standards, and pull request process.

🌟 Features

• Crop Recommendation Get suggestions for the best crops to cultivate based on soil and weather conditions.

• Yield Prediction Predict expected yields using advanced AI models tailored to different crop types.

• Disease Prediction Early detection of plant diseases along with treatment and preventive measures.

• Farmer Connection Connect with fellow farmers to share experiences, resources, and advice.

• Shopkeeper Listings Discover local agricultural product and service providers.

AgriTech/
├── 📁 docs/ # Documentation files\
│ ├── CONTRIBUTING.md
│ ├── TROUBLESHOOTING.md
│ ├── API_DOCUMENTATION.md
│ └── SETUP_GUIDE.md
│ ├── 📁 images/ # All images and visual assets
│ ├── screenshots/
│ │ ├── dashboard.png
│ │ ├── crop-recommendation.png
│ │ ├── disease-detection.png
│ │ └── community-chat.png
│ │ │ ├── gifs/ # Preview GIFs for README
│ │ ├── crop-recommendation.gif
│ │ ├── community-chat.gif
│ │ └── yield-prediction.gif
│ │ │ ├── icons/
│ │ ├── favicon.ico
│ │ ├── logo.png
│ │ └── apple-touch-icon.png
│ │ │ └── mockups/
│ ├── mobile-view.png
│ └── tablet-view.png
│ ├── 📁 src/ # Main source code
│ ├── 📁 frontend/
│ │ ├── index.html # Main entry point
│ │ ├── 📁 css/
│ │ │ ├── style.css
│ │ │ ├── components/
│ │ │ │ ├── navbar.css
│ │ │ │ ├── sidebar.css
│ │ │ │ ├── cards.css
│ │ │ │ └── forms.css
│ │ │ ├── pages/
│ │ │ │ ├── dashboard.css
│ │ │ │ ├── crop-recommendation.css
│ │ │ │ ├── disease-detection.css
│ │ │ │ └── community.css
│ │ │ └── responsive.css
│ │ │ │ │ ├── 📁 js/
│ │ │ ├── app.js # Main application logic
│ │ │ ├── 📁 modules/
│ │ │ │ ├── auth.js
│ │ │ │ ├── utils.js
│ │ │ │ └── animations.js
│ │ │ ├── 📁 features/
│ │ │ │ ├── crop-recommendation.js
│ │ │ │ ├── yield-prediction.js
│ │ │ │ ├── disease-detection.js
│ │ │ │ └── community-chat.js
│ │ │ └── 📁 components/
│ │ │ ├── navbar.js
│ │ │ ├── modal.js
│ │ │ └── charts.js
│ │ │ │ │ ├── 📁 assets/
│ │ │ ├── 📁 fonts/
│ │ │ ├── 📁 icons/ # SVG icons
│ │ │ └── 📁 data/ # Sample data for demos
│ │ │ │ │ └── 📁 pages/ # HTML pages for different features
│ │ ├── dashboard.html
│ │ ├── crop-recommendation.html
│ │ ├── yield-prediction.html
│ │ ├── disease-detection.html
│ │ ├── community.html
│ │ ├── shopkeepers.html
│ │ └── plantation-guide.html
│ │ │ ├── 📁 backend/ # Backend server code
│ │ ├── app.py # Flask main application
│ │ ├── requirements.txt
│ │ ├── 📁 routes/
│ │ │ ├── auth_routes.py
│ │ │ ├── crop_routes.py
│ │ │ ├── disease_routes.py
│ │ │ ├── yield_routes.py
│ │ │ └── community_routes.py
│ │ ├── 📁 models/
│ │ │ ├── user_model.py
│ │ │ ├── crop_model.py
│ │ │ ├── disease_model.py
│ │ │ └── database.py
│ │ ├── 📁 ml_models/ # AI/ML model files
│ │ │ ├── crop_recommendation/
│ │ │ │ ├── model.pkl
│ │ │ │ ├── train_model.py
│ │ │ │ └── preprocessing.py
│ │ │ ├── yield_prediction/
│ │ │ │ ├── model.h5
│ │ │ │ ├── train_model.py
│ │ │ │ └── data_processing.py
│ │ │ └── disease_detection/
│ │ │ ├── model.h5
│ │ │ ├── train_model.py
│ │ │ └── image_processing.py
│ │ ├── 📁 utils/
│ │ │ ├── helpers.py
│ │ │ ├── validators.py
│ │ │ └── constants.py
│ │ └── 📁 config/
│ │ ├── database.py
│ │ └── settings.py
│ │ │ └── 📁 database/ # Database related files
│ ├── schema.sql
│ ├── sample_data.sql
│ └── migrations/
│ ├── 📁 tests/ # Test files
│ ├── 📁 frontend/
│ │ ├── unit/
│ │ └── integration/
│ ├── 📁 backend/
│ │ ├── unit/
│ │ └── integration/
│ └── 📁 ml_models/
│ ├── test_crop_model.py
│ ├── test_yield_model.py
│ └── test_disease_model.py
│ ├── 📁 scripts/ # Utility scripts
│ ├── setup.sh # Quick setup script
│ ├── deploy.sh
│ ├── backup_database.sh
│ └── generate_gifs.py # Script to create preview GIFs
│ ├── 📁 config/ # Configuration files
│ ├── environment.yml
│ ├── nginx.conf
│ └── gunicorn.conf.py
│ ├── 📁 .github/ # GitHub workflows and templates
│ ├── workflows/
│ │ ├── ci-cd.yml
│ │ └── deploy.yml
│ ├── ISSUE_TEMPLATE/
│ │ ├── bug_report.md
│ │ └── feature_request.md
│ └── PULL_REQUEST_TEMPLATE.md
│ ├── 📁 data/ # Datasets and training data
│ ├── 📁 crop_data/
│ ├── 📁 disease_images/
│ └── 📁 yield_data/
│ ├── 📁 logs/ # Application logs
│ ├── app.log
│ ├── error.log
│ └── access.log
│ ├── 📄 .env.example # Environment variables template
├── 📄 .gitignore
├── 📄 README.md # Main documentation
├── 📄 package.json # Node.js dependencies (if using Node)
├── 📄 requirements.txt # Python dependencies
├── 📄 Dockerfile # Container configuration
├── 📄 docker-compose.yml # Multi-container setup
└── 📄 LICENSE # Project license\

Collaborate and discuss challenges, share solutions, and keep up with the latest in agriculture.

Plantation Guidance Access helpful plantation techniques and strategies for better crop growth.

Crop Planning Plan your season with confidence and unlock your farm's true potential for a more profitable and sustainable future.

• Frontend: HTML, CSS, JavaScript

• Backend: Flask / Node.js

• AI/ML Models: For prediction modules (Crop, Yield, Disease)

• Database: MySQL / MongoDB

• Hosting: Localhost (127.0.0.1), with option for cloud deployment

• Om Roy – Project Lead & Web Developer & Machine Learning Engineer

• Kanisha Ravindra Sharma – Machine Learning Engineer & Backend Developer

• Shubhangi Roy – Machine Learning Engineer & Backend Developer

We welcome contributions! Please read our Contributing Guide to get started. It includes:

Setting up the development environment

Code style guidelines

How to submit pull requests

Reporting issues

🌐 Future Scope ☁ Cloud deployment (e.g., Vercel, Heroku)

📱 Mobile app integration

🌦 Real-time weather API

🤖 AI chatbot for agriculture support

🗣 Support for regional languages

📞 Support If you encounter any issues:

Check the Troubleshooting Guide

Search existing Issues

Create a new issue with details about your problem

📄 License This project is licensed under the MIT License.

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Thank you for your interest in contributing to AgriTech! Here's how you can help:

1. Fork the repository
2. Clone your fork

   git clone https://github.com/your-username/AgriTech.git
   cd AgriTech

Set up development environment

# Install dependencies (if any)
npm install
# or
pip install -r requirements.txt
Start development server

npm run dev
# or
python app.py
Making Changes
Create a new branch:

git checkout -b feature/your-feature-name
Make your changes and test thoroughly

Commit your changes:

git commit -m "Add: description of your changes"
Push to your fork:

git push origin feature/your-feature-name
Create a Pull Request

• Use meaningful variable names

• Comment complex logic

• Follow existing code formatting

• Test your changes across different browsers

• Join our discussions in Issues

• Contact maintainers for guidance

• text

markdown

• Ensure you're running a local server, not just opening HTML files directly
• Check if port 8000 is available, try a different port if needed

• Check browser console for errors (F12 → Console)
• Ensure all dependencies are installed
• Verify your browser supports ES6+ features

• Check file paths are correct
• Ensure images are in the correct directory
• Verify file permissions

1. Check this guide
2. Search existing issues
3. Create a new issue with:
   • Your browser and version
   • Error messages from console
   • Steps to reproduce the issue For Creating Preview GIFs You can create the suggested GIFs using:

Windows: ScreenToGif, OBS Studio

Mac: QuickTime Player, GIPHY Capture

Linux: Peek, OBS Studio

Recommended workflow:

Record 5-10 second clips of key features

Optimize file size (keep under 5MB)

Show the most valuable interactions

Add to an /images or /gifs folder in your repo