Rainfall Prediction for Agriculture Optimization

This paper presents a machine learning based approach to predict rainfall and crop yields, leveraging the MERN stack to develop a user friendly web based application for farmers. The proposed system uses time series algorithms for rainfall prediction and regression models for estimating crop yields. These predictions help farmers optimize their resource management and make data driven decisions. The system integrates MongoDB for data storage, Express and Node.js for backend processing, and React for a dynamic front end interface. This innovative solution empowers farmers to adapt to climate changes and improve agricultural productivity.