AgroClimate AI 🌾🌡️

Climate-Smart Agriculture Platform using NASA-IBM Weather Model for Precision Farming

Overview

AgroClimate AI is an innovative platform that leverages NASA and IBM's weather prediction model to help farmers make informed decisions about their agricultural practices. By combining real-time climate data with advanced machine learning models, we provide actionable insights for sustainable and efficient farming.

Project Structure

agroclimate-ai/
├── src/                    # Source code
│   ├── frontend/          # Frontend application (Next.js)
│   ├── backend/           # Backend API services (FastAPI)
│   ├── ml_model/          # Machine learning models
│   └── data_pipeline/     # Data processing pipelines
├── docs/                  # Documentation
├── tests/                 # Test suites
├── scripts/              # Utility scripts
└── config/               # Configuration files

Features

• 🛰️ NASA-IBM Weather Model Integration
• 📊 Real-time Climate Data Analysis
• 🤖 Machine Learning-based Predictions
• 🌱 Crop Recommendation System
• ⚡ Real-time Alerts and Notifications
• 📱 Farmer-friendly Dashboard
• 📈 Historical Data Analysis
• 🎯 Precision Agriculture Support

Getting Started

Prerequisites

• Python 3.8+
• Node.js 16+
• Docker (optional)

Installation

1. Clone the repository:

   git clone https://github.com/Roxonn-FutureTech/agroclimate-ai.git
   cd agroclimate-ai

2. Install dependencies:

   # Backend dependencies
   cd src/backend
   pip install -r requirements.txt
   
   # Frontend dependencies
   cd ../frontend
   npm install

3. Set up environment variables:

   cp config/.env.example config/.env

4. Start the development servers:

   # Backend
   cd src/backend
   uvicorn main:app --reload
   
   # Frontend
   cd ../frontend
   npm run dev

Contributing

We welcome contributions! Please see our Contributing Guide for details.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

• Website: roxonn.com
• GitHub: @Roxonn-FutureTech