KrishiSaarthi AI - Smart Farming Advisor

A web application that helps farmers make crop and fertilizer decisions using simple inputs, even without soil reports.

🌾 Overview

KrishiSaarthi AI is a hackathon-ready farming recommendation system that provides:

• Crop Recommendations: Suggest top 2-3 crops based on farm conditions
• Fertilizer Planning: Detailed NPK recommendations with costs
• Multiple Input Methods: Soil report or simple questionnaire
• Location-based Guidance: Find nearby soil testing labs
• Government Schemes: Information on agricultural benefits and subsidies

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🔗 Live Links

• Frontend App (Vercel): https://krishi-sarthi-ai.vercel.app
• Backend API (Render): https://astrax-greentech.onrender.com

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🚀 Features

Core Features

1. Soil Report Analysis - Upload soil test results (N, P, K, pH) for precise recommendations

2. Questionnaire Mode - Simple questions for farmers without soil reports

3. Smart Recommendations:

   • Crop suitability scoring
   • Fertilizer calculation and scheduling
   • Cost optimization suggestions
   • Yield potential estimates

4. Support Services:

   • Soil testing lab finder with contact details
   • Government schemes information
   • Agricultural best practices guide
   • Cost-saving tips

📁 Project Structure

AstraX_Greentech/
├── frontend/                 # React Frontend
│   ├── public/
│   │   └── index.html       # HTML template
│   ├── src/
│   │   ├── pages/           # Page components
│   │   │   ├── Home.js
│   │   │   ├── SoilReportAdvisor.js
│   │   │   ├── QuestionnaireAdvisor.js
│   │   │   ├── SoilTestingLabs.js
│   │   │   └── GovernmentSchemes.js
│   │   ├── services/        # API services
│   │   │   └── api.js       # Axios configuration
│   │   ├── styles/          # CSS files
│   │   ├── App.js
│   │   └── index.js
│   └── package.json
│
├── backend/                  # Node.js Backend
│   ├── routes/              # API routes
│   │   ├── recommendations.js
│   │   ├── soilLabs.js
│   │   └── schemes.js
│   ├── services/            # Business logic
│   │   └── recommendationEngine.js
│   ├── data/                # Mock data
│   │   ├── soilLabs.js
│   │   └── schemes.js
│   ├── server.js            # Express server
│   ├── package.json
│   └── .env.example
│
└── README.md

🛠️ Tech Stack

Frontend:

• React 18
• React Router DOM
• Axios (HTTP client)
• CSS3 (Responsive Design)

Backend:

• Node.js
• Express.js
• CORS
• dotenv

⚙️ Installation & Setup

1. Clone the Repository

git clone https://github.com/ankitkumar764/AstraX_Greentech.git
cd AstraX_Greentech

2. Backend Setup

# Navigate to backend directory
cd backend

# Install dependencies
npm install

# Create .env file
copy .env.example .env

# Start the backend server
npm run dev
# Backend runs on http://localhost:5000

3. Frontend Setup (in new terminal)

# Navigate to frontend directory
cd frontend

# Install dependencies
npm install

# Start the development server
npm start
# Frontend opens at http://localhost:3000

🎯 Usage Guide

Soil Report Mode

1. Click on "📊 Soil Report" from navigation
2. Enter your soil test parameters (N, P, K, pH)
3. Select your crop and budget
4. Get detailed fertilizer recommendations

Questionnaire Mode

1. Click on "❓ Questionnaire"
2. Answer simple questions about your farm
3. Receive top 3 crop recommendations with fertilizer plans

Other Features

• Soil Testing Labs: Find nearby labs with contact details
• Government Schemes: Browse agricultural subsidies and benefits
• Testing Guide: Learn how to collect soil samples

📊 API Endpoints

Recommendations

POST /api/recommendations/get
POST /api/recommendations/soil-report

Soil Labs

GET /api/soil-labs/:state
GET /api/soil-labs

Government Schemes

GET /api/schemes/list
GET /api/schemes/category/:category

🎓 Supported Crops

• Wheat (Rabi)
• Rice (Kharif)
• Maize (Kharif/Rabi)
• Cotton (Kharif)
• Sugarcane (Kharif/Rabi)
• Pulses (Rabi)
• Vegetables (Year-round)

🧮 How Recommendations Work

1. Crop Scoring: Algorithm evaluates soil type, season, pH, water needs, and budget
2. Fertilizer Calculation: Determines NPK deficit and calculates optimal fertilizer mix
3. Cost Optimization: Provides cost-saving suggestions and government scheme info

📋 Fertilizer Types

Fertilizer	N%	P%	K%	Cost/50kg
Urea	46	0	0	₹250
DAP	18	46	0	₹1100
MOP	0	0	60	₹600
Neem	3	1	1	₹400

🔐 Environment Variables

Create .env in backend directory:

PORT=5000
NODE_ENV=development
FRONTEND_URL=http://localhost:3000

📱 Example API Responses

Soil Report API

{
  "success": true,
  "crop": "wheat",
  "soilAnalysis": {
    "nitrogen": 200,
    "phosphorus": 20,
    "potassium": 150,
    "pH": 6.8
  },
  "fertilizerPlan": {
    "recommendations": [
      {
        "name": "DAP",
        "bags": 2,
        "timing": "At planting",
        "cost": 2200
      }
    ],
    "totalCost": 3500
  }
}

🚀 Deployment

Backend (Heroku)

heroku create your-app-name
git push heroku main

Frontend (Vercel)

npm run build
vercel --prod

🔄 Extending the System

Add New Crops

Edit backend/services/recommendationEngine.js and add to cropDatabase

Add States in Soil Labs

Edit backend/data/soilLabs.js

Add Government Schemes

Edit backend/data/schemes.js

🐛 Troubleshooting

Backend not running:

• Ensure Node.js is installed: node --version
• Run npm install in backend folder
• Check port 5000 is free

Frontend API errors:

• Verify backend is running
• Check REACT_APP_API_URL in frontend .env
• Open browser console for error messages

Port in use:

# Windows
netstat -ano | findstr :5000
taskkill /PID <PID> /F

# Linux/Mac
lsof -i :5000
kill -9 <PID>

📞 Support

For issues or questions, check:

1. Troubleshooting section above
2. Browser console (F12)
3. Backend terminal logs

🎯 Future Enhancements

• Database integration (MongoDB)
• User authentication
• Real crop price updates
• Weather-based recommendations
• Mobile app
• Multi-language support
• Plant disease detection
• Historical yield tracking

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Made with 🌱 for Indian Farmers