🌾 KrishiMitra: Smart Agricultural E-Commerce Platform

A smart agricultural platform that empowers farmers by removing middlemen, enabling direct market access, and delivering AI-powered recommendations, real-time pricing, and automated logistics.

📌 Overview

KrishiMitra is a comprehensive agricultural platform that revolutionizes the traditional farming supply chain by eliminating middlemen and providing direct market access to farmers. The platform leverages AI and machine learning to offer smart crop recommendations, real-time price insights, and automated logistics solutions.

🎯 Key Objectives

• Connect farmers directly with consumers for better profits
• Provide AI-powered crop recommendations and market insights
• Enable bulk trading and cold storage management
• Ensure fair pricing through transparent market data
• Support multilingual chatbot assistance for better accessibility

🚀 Key Features

🤖 AI Intelligence

• Smart Crops Recommendation – Auto-suggest crops using location, season & trends
• Market Insights – Predict prices & demand in real-time
• Multilingual Agriculture Chatbot – AI chatbot for instant query resolution

🛍️ Marketplace

• Direct Trade – Farmer-to-consumer, no middlemen
• Bulk Exchange – Seamless large-scale buying/selling
• Cold Storage – Book & manage storage units
• Live Rates – Track current crop prices
• Product + Orders – Browse, buy, and manage orders

👨‍🌾 User Experience

• Dashboards – Tailored for farmers & buyers
• Multilingual Chat – Hindi, Marathi, English support
• JWT Auth – Secure logins
• Responsive UI – Mobile-first design
• Profiles + Alerts – Real-time updates & user settings

🛠️ Tech Stack

Frontend: React.js (Vite), Tailwind CSS, Context API, React Router, Axios, Framer Motion, Chart.js, React Hot Toast, React Icons
Backend: Node.js, Express.js, JWT, REST APIs, CORS, Multer, Async Handler, MongoDB (Mongoose)
Database: MongoDB with Mongoose ODM, schema validation, document refs
AI/ML: Random Forest (Crop), TensorFlow/PyTorch (Price), Gemini 1.5 Flash (Chatbot)

📸 Screenshots

🎥 Demo Video

📌 Project Reports & Presentations

Presentations

• Syrus Hackathon-2025 PPT
• Field Project(VESIT) PPT

Project Report

• Project Report - VESIT

Take a look at these documents for a deeper understanding of the projects.

🚀 Installation & Setup

Prerequisites

• Node.js (v14 or higher)
• MongoDB
• Python (v3.7+ for ML models)
• Git

Backend Setup

1. Clone the repository:

   git clone https://github.com/parthnarkar/Krishi-Mitra.git
   cd Krishi-Mitra/backend

2. Install dependencies:

   npm install

3. Start the server:

   npm start

4. Run the ML Model Server (in a new terminal)

   cd Krishi-Mitra/backend/ml_model/model
   python app.py

   Make sure Python and required libraries for the ML model are installed. You can use a virtual environment if needed.

Frontend Setup

1. Navigate to frontend directory:

   cd ../frontend

2. Install dependencies:

   npm install

3. Start development server:

   npm run dev

4. Access the application at http://localhost:5173

🤝 Contributing

We welcome contributions! Please follow these steps:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📄 License

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

👥 Team

• Team Name: Krishi Mitra
• Institute: Vivekanand Education Society's Institute of Technology

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Made with ❤️ by Team Krishi-Mitra