Crop Yeild Prediction for Smart Farming

This Smart farming is the one of the most important need to grow Indian economy as most of the Indian revenue of India is based on farming. Crop yield prediction is required in farming sector to understand different conditions where farmers can get more profit. In this three applications are designed which are based on crop prediction for better yield based on soil type, crop disease prediction and recommendation of different fertilizers for better yield and third important application is based on different condition prediction of yield for specific plant in specific season. Based on the above conditions farmers can take correct decision for better yield in available farm area. Different machine learning and deep learning algorithms are used for implementation of these applications. For crop disease prediction and for soil type prediction, Convolutional neural Network (CNN) is used which performs superior to state of art algorithms while for prediction of yield from different user input condition, logistic regression (LR) is used. Proposed system is more user-friendly and going make best impact for farmers and agricultural department.