Arecanut Crop Disease Prediction using IoT and Machine Learning

Abstract

A prevailing recession in the agricultural goods sector is evident from the present scarcity and lack of food supplies. A major reason for this scarcity is the inherent growth of diseases in essential crops. A major development is thus required in this field for avoiding these problems in the future. This development is intended to simplify the management tasks of different roles in agricultural industries. A proper intimation of the importance of disease prediction and environmental factors must be done to the less aware farmers. To address these challenges, we have proposed a disease prediction system that takes into consideration temperature (°C), humidity(%), rainfall(cm), wind flow(m/s) and soil moisture (%) around the region of crop and developed a model to predict the occurrence of disease. This system will provide information prior to the occurrence of disease by analyzing different relationships among environmental factors.