Crop Yield and Rainfall Prediction in Tumakuru District using Machine Learning

Abstract

Smart Agriculture is a development that emphasizes the use of information technology in the farming. Most of the population in India depending on agriculture. This situation is one of the reason, that hindering the development of country. Nowadays, even though farmers get more yield for their crop but the market price for that crop will be less, in that case farmers get loss for their product and vice versa. Particularly, when growing new crops, farmers face the risks of both market price and production problems. To overcome these problems, a machine learning technology is used. Predictive analysis is a branch of data mining which predicts the future probabilities and trends. The prediction will help the farmers to choose whether the particular crop is suitable for specific rainfall and crop price values. This approach is to increase the net yield rate of the crop, based on rainfall. Prediction can be carried out by using various machine learning algorithms like linear regression, SVM, K NN method and decision tree algorithm out of which SVM is giving the highest efficiency. The predictive analysis technique can be implemented in several government sectors like APMC, kissan call center etc., by which the government and farmers can get the information of the future rainfall, crop yield and the market price.