IoT Based Smart Agriculture and Plant Disease Prediction

Abstract

Agriculture is a very prominent sector in our country and has been one of the highest contributors to the GDP. During the 1960s, an all-time high was reached with approximately 50% contribution to the GDP of the country, as more than half of the population was rural and focused primarily on agriculture as means of their livelihood. But from the latest records of 2019, the contribution by this sector has decreased to 15.96 percent. IoT plays a significant tole in remote sensing with machine learning in monitoring crops and surveying, which in turn aids agriculturists in ways for efficient field management. The proposed work integrates the role of Internet of Things and Deep learning deployment in farm management and disease identification of leaves. With the use of Internet of Things through remote sensing this work monitors the agriculture field parameters in remote cloud environment. With modified Resnet model deployed on the cloud for the purpose building a smart disease prediction. This system achieves 99.35% accuracy for the dataset. Overall this approach will provide an opportunity for agriculturists to test the plant disease with a smart phone connected to Internet and take appropriate actions.