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AgriMind 🌱

AI-powered crop recommendation and yield prediction platform. Built with Vite + React frontend and Flask backend, integrating PostgreSQL for robust data storage.

Live Demo | Crop Recommender | Yield Predictor | Settings | Equipment Rentals | CommunityHub |


Overview

AgriMind helps farmers maximize yield, profitability, and sustainability with personalized crop recommendations using real-time soil, weather, market data, and AI-powered yield/profit estimation.


✨ Features

  • Smart Crop Recommendation using soil, weather, and market analytics.
  • Yield/Profit Prediction supporting 30+ crops.
  • Soil Health Monitor for real-time NPK/pH/moisture.
  • Weather & Market Trends live updates.
  • Clean, Responsive UI with React + Tailwind.
  • Role-based access & secure login.

🛠 Tech Stack

  • Frontend: Vite, React, TypeScript, Tailwind CSS
  • Backend: Flask (Python)
  • ML: scikit-learn, pandas, numpy
  • Database: PostgreSQL (default), SQLite (fallback)
  • Deployment: Vercel (FE), Render (BE)

📂 File Structure


AgriMind/
├── Flask/
│ ├── app/
│ │ ├── init.py
│ │ ├── database.py
│ │ ├── models.py
│ │ ├── routes.py
│ │ ├── services.py
│ │ ├── storage.py
│ │ └── templates/
│ │ └── index.html
│ ├── instance/
│ │ └── agrimind.db
│ ├── ml/
│ │ ├── crop_recommender/
│ │ │ ├── Crop_recommendation.csv
│ │ │ ├── model_training.py
│ │ │ ├── predict.py
│ │ │ └── synthetic_missing_crops.csv
│ │ └── yield_predictor/
│ │ ├── synthetic_crop_yield_dataset_full.csv
│ │ ├── yield_model_training.py
│ │ └── yield_predict.py
│ ├── app.py
│ └── requirements.txt
├── Frontend/
│ ├── public/
│ ├── src/
│ │ ├── components/
│ │ │ ├── auth/
│ │ │ ├── settings/
│ │ │ └── ui/
│ │ ├── pages/
│ │ ├── contexts/
│ │ ├── hooks/
│ │ ├── App.tsx
│ │ ├── AppRoutes.tsx
│ │ ├── index.css
│ │ ├── main.tsx
│ ├── package.json
│ ├── tailwind.config.ts
│ ├── tsconfig.json
│ └── README.md
├── .gitignore
├── README.md
└── requirements.txt


  • (.pkl ML model files are omitted for clarity.)

🚀 Getting Started

Prerequisites

  • Python 3.8+
  • Node.js & npm
  • PostgreSQL

Backend Setup (Flask)


cd Flask
python -m venv venv
  • Windows
venv\Scripts\activate
  • macOS/Linux
source venv/bin/activate
pip install -r requirements.txt
  • Setup DB (optional: adjust config for PostgreSQL)
python app.py

Frontend Setup (Vite + React)

cd Frontend
npm install
npm run dev

🖥 Usage

  • Register/login and explore crop recommendations, yield predictions, soil monitor, and farming resources.
  • Toggle between modules using the navigation bar.

🤝 Contributing

  1. Fork the project
  2. Create your feature branch
    git checkout -b feature/YourFeature
  3. Commit your changes
    git commit -m 'Add feature X'
  4. Push to the branch
    git push origin feature/YourFeature
  5. Open a pull request

Owned By:

Srivathsa Bhat | Niranjan C N | Shreyas S | Yogith D | Sinchana K

📄 License

This project is licensed under the MIT License.

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