Blossom end rot disease tracking and prevention: a smart approach

Agriculture is the foundation of any nation. It is required for the comprehensive financial turn of events. The paper centers on Blossom End Rot infection which influences the tomato plant because of pH variety in the soil. This paper presents an investigation of different strategies to sift through disease, plant infection distinguishing proof utilizing layout coordinating picture order just as deep learning based Convolutional neural systems picture arrangement and proposes a framework to forestall the event of this ailment. Deep learning based disease identification has higher exactness than conventional strategies. In traditional methods, we just pH value of the soil is measured and remedial measure is taken, but here model is proposed that combines that disease detection at the early stage itself by using Deep Learning and IoT. The general goal is to improve rural profitability and homestead salary.