INTEGRATEDCROP MANAGEMENT SYSTEM

INTEGRATEDCROP MANAGEMENT SYSTEM

Dr . Joseph M Jerard , YOGESHWAR L , NISCHITH S GOWDA , RAMPRAKASH GOWDA

Computer Science and Engineering Presidency University, Bengaluru

ABSTRACT

The goal of the machine learning-based Crop Management System is to increase agricultural productivity. It helps farmers by providing features like yield forecasting, rainfall prediction, crop prediction, and fertilizer advice. The system analyzes important variables like rainfall, temperature, humidity, and soil type to provide useful information for improving farming methods. Utilizing machine learning frameworks such as Scikit-learn and Python and PHP, the project uses predictive algorithms to provide customized suggestions for crop management and selection. This application addresses issues like resource optimization and climatic unpredictability while enabling farmers to make data-driven decisions that increase agricultural sustainability and efficiency. The system has the friendly interfaces and accessibility

for a farmer with even lower technical background to use in its operations.