Agricultural Efficiency using Machine Learning

Abstract

Agriculture is the key economic foundation of our nation. The price of the crop has fluctuated
to a greater degree in recent years as a result of unclear climate trends and other price swings.
Farmers are blind to these uncertainties, which ruin harvests and result in enormous losses.
They are uninformed of the type of crop that would most benefit them. Due to their
insufficient understanding of many agricultural diseases and their unique treatments, crops
are harmed. This system is convenient and easy to use. It gives accurate findings for crop
price forecasting. This system predicts crop price using the Decision Tree Regression
Algorithm of Machine Learning. Prediction factors include precipitation, the wholesale price
index, the month, and the year. As a result, the system provides farmers with a projection in
advance, which increases their rate of profit and the country's economy. In addition to
weather forecast, crop recommendation, and fertiliser recommendation, this system also
implements shop, chat portal, and guide modules.