Crop Management System

The Crop Management System is a machine learning-based project designed to provide predictions and recommendations for farmers. The system uses different algorithms to predict crops, recommend fertilizers, and provide rainfall and yield predictions to help farmers make informed decisions about their crops.

Installation

1. Clone the repository to your local machine.

git clone https://github.com/ab007shetty/crop-management-system.git

2. Install the required packages using pip.

pip install -r requirements.txt

3. Run Apache web server using XAMPP.

Features

• Crop Prediction
• Crop Recommendation
• Fertilizer Recommendation
• Rainfall Prediction
• Yield Prediction

Technologies Used

• Python
• PHP
• Pandas
• NumPy
• JavaScript
• HTML/CSS
• Bootstrap4
• Scikit-learn

Dataset

The Crop Management System dataset includes the following features:

Crop Prediction Dataset

• State_Name
• District_Name
• Season
• Crop

Crop Recommendation Dataset

• N
• P
• K
• Temperature
• Humidity
• pH
• Rainfall
• Label

Fertilizer Recommendation Dataset

• Temparature
• Humidity
• Soil Moisture
• Soil Type
• Crop Type
• Nitrogen
• Phosphorous
• Potassium
• Fertilizer Name

Rainfall Prediction Dataset

• SUBDIVISION
• YEAR
• JAN
• FEB
• MAR
• APR
• MAY
• JUN
• JUL
• AUG
• SEP
• OCT
• NOV
• DEC
• ANNUAL
• Jan-Feb
• Mar-May
• Jun-Sep
• Oct-Dec

Yield Prediction Dataset

• State_Name
• District_Name
• Crop_Year
• Season
• Crop
• Area
• Production

How to Use

• Crop Prediction: Input State_Name, District_Name, and Season to get the predicted crop for that location.
• Crop Recommendation: Input N, P, K, Temperature, Humidity, pH, and Rainfall for that location to get recommended crops for that location.
• Fertilizer Recommendation: Input Temperature, Humidity, Soil Moisture, Soil Type, Crop Type, Nitrogen, Phosphorous, and Potassium to get recommended fertilizer for that crop and location.
• Rainfall Prediction: Input Subdivision and Year to get rainfall prediction for that year.
• Yield Prediction: Input State_Name, District_Name, Crop_Year, Season, Crop, Area, Production to get predicted yields for that crop and location.

Contributors

• AB Shetty
• ChatGPT 3.5 Turbo

License

This project is licensed under the MIT License.