AgriNex is a comprehensive AI-powered agricultural platform designed to optimize crop yields and soil health. It combines a high-performance Flask backend with a premium, animated React frontend to provide actionable insights for farmers and agronomists.
AgriNex provides a suite of tools for modern agriculture:
- Crop Prediction: AI-driven crop selection based on soil nutrients and weather.
- Fertilizer Recommendation: Tailored nutrient management advice.
- Plant Disease Detection: Image-based diagnosis using Deep Learning (ResNet9).
- Weather Forecasting: Integrated 5-day forecasts for precise planning.
- Frontend: React 19, Vite, Framer Motion, Lottie, Bootstrap 5.
- Backend: Flask (Python), PyTorch, Pandas, Scikit-learn.
- Models: Pre-trained Random Forest for crops and ResNet9 for diseases.
To run the full system, you need to start both the backend and frontend.
# Navigate to the backend directory
cd backend
# Install dependencies
pip install flask flask-cors requests pandas torch torchvision pillow scikit-learn
# Start the server
python app.pyBackend will run on http://127.0.0.1:5000
# Navigate to the Frontend directory
cd Frontend
# Install dependencies
npm install
# Start the dev server
npm run devFrontend will run on http://localhost:5173
Sustainable-Crop-Management-System/
├── backend/ # Flask API & AI Models
│ ├── data/ # CSV datasets
│ ├── models/ # Trained .pkl and .pth files
│ └── app.py # Main API entry
└── Frontend/ # React Application
├── src/ # Components & Pages
└── package.json # Frontend dependencies
The project features a Premium Animated UI with:
- Liquid Backgrounds: Smooth Lottie animations.
- Reveal Effects: Framer Motion entrance animations for every section.
- Micro-interactions: Responsive hover states and tactile feedback.
Developed for Sustainable Agriculture & AI Innovation.