🌿 Smart Fertilizer Management System

A comprehensive digital platform designed to modernize agricultural management, providing tools for fertilizer recommendation, machinery rental, expert consultation, and marketplace services.

🚀 Overview

The Smart Fertilizer Management System is a full-stack application built to empower farmers and agricultural stakeholders. It integrates machine learning for smart recommendations, a robust backend for managing complex agricultural workflows, and a modern, responsive frontend for an intuitive user experience.

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✨ Key Features

• 🌾 Fertilizer Recommendation: ML-powered insights for optimal crop yields.
• 🚜 Machinery Rental: Seamless booking system for agricultural equipment.
• 👨‍🌾 Expert Consultation: Connect with authorized Agricultural Officers for tailored advice.
• 🛒 Agri-Store Marketplace: Buy and sell agricultural products and fertilizers.
• 🛡️ Multi-Role System: Dedicated dashboards for Admin, Seller, and Farmer/User.
• 🔔 Real-time Notifications: Stay updated on rental status, consultation reviews, and marketplace activity.
• 📊 Analytics Dashboard: Comprehensive view for admins to monitor platform activity.

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🛠️ Tech Stack

Frontend

• Framework: React 19 (Vite)
• Language: TypeScript
• Routing: React Router 7
• Styling: Vanilla CSS (Modern aesthetic)

Backend

• Runtime: Node.js
• Framework: Express.js
• Language: TypeScript
• Database: MongoDB (Mongoose ODM)
• Security: JWT & Bcrypt Auth, Helmet.js

Machine Learning

• Language: Python
• Framework: Flask/FastAPI (Placeholder for ml_service)

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🛠️ Prerequisites

Before you begin, ensure you have the following installed:

• Node.js (v18+)
• npm or yarn
• Python 3.10+ (for ML Service)
• MongoDB (Local or Atlas instance)

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📥 Installation

1. Clone the repository:

   git clone https://github.com/piumi2004/Smart_Fertilizer.git
   cd Smart_Fertilizer

2. Install Root Dependencies:

   npm install

3. Install Backend Dependencies:

   cd backend
   npm install
   cd ..

4. Set up Environment Variables:

   • Create a .env file in the root directory based on .env.example.
   • Create a .env file in the backend/ directory based on backend/.env.example.

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🏃 Running the Application

You can run segments of the application individually or all at once.

🏁 Full Stack (Frontend + Backend + ML)

From the root directory:

npm run dev:full

💻 Frontend Only

From the root directory:

npm run dev

⚙️ Backend Only

From the root directory:

npm run dev --prefix backend

🤖 ML Service Only

From the root directory:

npm run dev:ml

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📂 Project Structure

Smart_Fertilizer/
├── backend/                # Express + TS Backend
│   ├── src/                # Backend Source Code
│   │   ├── models/         # Mongoose Schemas
│   │   ├── routes/         # API Route Definitions
│   │   └── services/       # Business Logic
│   └── scripts/            # Database migration scripts
├── ml_service/             # Python Machine Learning Service
│   ├── data/               # Dataset storage
│   └── models/             # Trained model files
├── src/                    # React + TS Frontend
│   ├── components/         # Reusable UI components
│   ├── pages/              # Application views/pages
│   ├── context/            # Global State Management
│   └── assets/             # Images and styles
├── public/                 # Static assets
└── package.json            # Root scripts and workspace config

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🔑 Environment Variables

Backend (backend/.env)

• PORT: Port for the server (default: 5000)
• MONGODB_URI: Connection string for MongoDB
• JWT_SECRET: Secret key for authentication
• CORS_ORIGIN: Allowed frontend origins

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📄 License

This project is licensed under the ISC License.

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Developed for Smart Agriculture Initiatives. 🌿📖