🌾 Smart Crop Recommendation System

An AI/ML-powered crop recommendation web application that predicts the most suitable crop based on soil nutrients and environmental conditions.

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🚀 Live Demo

🔗 Frontend: https://akshit-srivastava1.github.io/Smart-Crop-Recommendation/

🔗 Backend API: https://crop-recommendation-api-zpdn.onrender.com

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📌 Features

• 🌱 Intelligent crop prediction using Machine Learning
• 📊 Top 3 crop recommendations with confidence scores
• 🎛️ Interactive sliders for environmental inputs
• ⚡ Real-time prediction using Flask API
• 🌐 Fully deployed full-stack application
• 📱 Responsive modern UI

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🧠 Machine Learning Model

• Algorithm: Random Forest Classifier
• Accuracy: 99.32%
• Dataset Size: 2200+ records
• Features Used:
  • Nitrogen (N)
  • Phosphorus (P)
  • Potassium (K)
  • Temperature
  • Humidity
  • Soil pH
  • Rainfall

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🛠️ Tech Stack

Frontend

• HTML5
• Tailwind CSS
• JavaScript

Backend

• Python
• Flask
• Flask-CORS

Machine Learning

• Scikit-learn
• Pandas
• Joblib

Deployment

• GitHub Pages
• Render

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📷 Project Preview

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⚙️ Installation & Setup

Clone Repository

git clone https://github.com/Akshit-Srivastava1/Smart-Crop-Recommendation.git
cd Smart-Crop-Recommendation

Install Dependencies

pip install -r requirements.txt

Train Model

python train_model.py

Run Backend

python app.py

Run Frontend

python -m http.server 5500

Open:

http://127.0.0.1:5500/index.html

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📂 Project Structure

Smart-Crop-Recommendation/
│
├── assets/ Crop.png
├── app.py
├── train_model.py
├── crop_model.joblib
├── Crop_recommendation.csv
├── index.html
├── requirements.txt
├── render.yaml
└── README.md

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📈 Future Improvements

• Weather API Integration
• Fertilizer Recommendation
• Crop Disease Detection
• AI Chat Assistant for Farmers
• Multilingual Support

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👨‍💻 Developer

Akshit Srivastava

🔗 GitHub:
https://github.com/Akshit-Srivastava1

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⭐ Support

If you liked this project, give it a ⭐ on GitHub.