🌱 KISAN SAHAYTA – Smart Farming Assistant

A project developed for Smart India Hackathon (SIH) to empower farmers with AI-driven crop yield prediction and advisory support.
The platform helps farmers make data-driven decisions about crop selection, irrigation, and fertilizer management, ultimately increasing productivity and sustainability.

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🚩 Problem Statement

Farmers often face challenges like:

• Lack of reliable data on crop yield predictions.
• Dependence on traditional practices leading to reduced productivity.
• Difficulty in accessing modern farming insights due to language and accessibility barriers.

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💡 Our Solution

KISAN SAHAYTA provides a one-stop AI-powered web application that:

• 📊 Predicts crop yield using Machine Learning models trained on agricultural datasets.
• 🌦️ Considers soil parameters, weather conditions, and crop type.
• 💻 Offers a farmer-friendly interface for easy input and instant insights.
• 🌍 Supports multiple languages for inclusivity.
• 🚀 Can be scaled and integrated with government schemes & databases.

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🛠️ Tech Stack

• Frontend: React.js, Tailwind CSS
• Backend: FastAPI (Python)
• Machine Learning: Scikit-learn, Pandas, NumPy
• Database: SQLite / PostgreSQL
• Deployment: Docker, Render/Heroku (or chosen platform)

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📂 Repository Structure

- backend/ # FastAPI backend with ML model
  - main.py # API routes
  - model.pkl # Trained ML model
  - requirements.txt
- frontend/ # React.js frontend
  - src/
  - public/
  - package.json
- data/ # Dataset files (crop_yield.xlsx, data_core.xlsx, etc.)
- notebooks/ # Jupyter notebooks for model training & experiments
- docs/ # Project documentation, presentations
- README.md # Project overview (this file)

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⚙️ Installation & Setup

1. Clone the repository

bash git clone https://github.com/your-username/sih-kisan-sahayta.git cd sih-kisan-sahayta

2. Backend Setup (Fast API and ML Model)

cd backend pip install -r requirements.txt uvicorn main:app --reload Backend will run on: http://127.0.0.1:8000

3. Frontend Setup

cd frontend npm install npm start Frontend will run on: http://localhost:3000

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🎯 Features

• ✅ AI-powered crop yield prediction
• ✅ Real-time weather & soil data integration
• ✅ Multilingual farmer-friendly UI
• ✅ Lightweight farmer-friendly UI
• ✅ Open for integration with government databases

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🚀 Future Scope

• Integration with IOT-based sensors for real time soil data.
• Mobile app development for wider accessibility.
• Direct linkage with government subsidy schemes.
• AI chatbot assistant for farmer queries.

👥 Team - HackersInc

• Vishnukant Bajpai
• Naman Kumar Bansal
• Saad Khan
• Virat Singh
• Nikita
• Ankit Singh