Smart Farming System

A full-stack web application designed to empower modern farmers with intelligent crop suggestions, localized farming practices, and real-time safety monitoring. The platform leverages machine learning and location-based services to optimize agricultural yields and ensure farm safety.

🚀 Technologies Used

• Frontend: React.js, Vite
• Backend: Python, FastAPI
• Machine Learning: Scikit-Learn, Pandas

✨ Key Features

• Location-Based Crop Suggestions: Recommends the best crops to plant based on your specific geographical location and environmental factors.
• Safety Monitoring: Real-time safety analytics and safe zone tracking.
• Government Schemes Hub: A centralized dashboard to discover relevant agricultural schemes and subsidies.
• Interactive Dashboard: Real-time data visualization and farm management tools.

🛠️ Setup Instructions

Prerequisites

• Node.js (v16+)
• Python (3.9+)

1. Backend Setup

Navigate to the backend directory:

cd backend

Create and activate a virtual environment (recommended):

python -m venv venv
# On Windows:
venv\Scripts\activate
# On Mac/Linux:
source venv/bin/activate

Install the required Python packages:

pip install -r requirements.txt

Start the FastAPI server:

uvicorn main:app --reload

The backend API will be running at http://127.0.0.1:8000. You can view the interactive API documentation at http://127.0.0.1:8000/docs.

2. Frontend Setup

Open a new terminal and navigate to the frontend directory:

cd frontend

Install the Node.js dependencies:

npm install

Start the React development server:

npm run dev

The frontend application will be running at http://localhost:5173 (or the port specified by Vite).