Fertilizer Recommendation System (Client & Server)

Overview

The Fertilizer Recommendation System is a web-based application designed to provide tailored fertilizer recommendations for different crops based on various factors like growth stage, soil properties, climate, and more. It consists of a frontend built with React and a backend powered by Flask, using Prolog for inference.

Features

• Real-time Fertilizer Recommendations based on multiple parameters.
• Interactive UI allowing users to input their crop and environmental data.
• Backend Inference Engine using Prolog to calculate optimal fertilizer recommendations.

Tech Stack

• Frontend: React, JSX, Vite (with fetch for API requests)
• Backend: Flask, Python, SWI-Prolog
• Docker: For containerization and deployment

Installation

To get started with the project locally, follow the steps below:

1. Clone the Repository

git clone --recurse-submodules https://github.com/Programming-Sai/Fertilizer-Recommendation-System-Client-Server.git
cd Fertilizer-Recommendation-System-Client-Server

Note

If you have already cloned the repository without --recurse-submodules, you can initialize the submodules separately with:

git submodule update --init --recursive

Repositories

• Frontend: Fertilizer Recommendation System Client
• Backend: Fertilizer Recommendation System Server

2. Set Up the Backend

1. Navigate to the server directory.

   cd server

2. Install the necessary dependencies:

   pip install -r requirements.txt

3. Start the backend server:

   python scripts/server.py

   The backend should now be running at http://localhost:5000.

3. Set Up the Frontend

1. Navigate to the client directory.

   cd client

2. Install dependencies:

   npm install

3. Start the frontend:

   npm run dev

   The frontend should now be accessible at http://localhost:3000.

4. Running the Full Application Using Docker

1. From the root directory, run:

   docker-compose up --build

   • To stop it you can run

     # Ctrl + C  # If running in the foreground
     docker-compose down  # To stop and remove containers

   This will build and run the frontend and backend containers.

Usage

Once both the frontend and backend are running, you can navigate to http://localhost:3000 in your browser and start using the application.

How to Use

• Navigate to Predict from the Navbar to get to the parameters form
• Input the required crop, environmental and soil parameters.
• Click Get Recommendations to receive fertilizer recommendations tailored to your inputs.