Krishimitr: A cloud computing and platform for disease detection in agriculture

Abstract

Automating disease detection is a cornerstone in the journey to achieving sustainable agriculture. We describe a framework utilizing Machine Learning, Cloud Computing and Internet-of-Things which brings experts to farmers, allowing for timely detection of diseases. This innovative and comprehensive framework provides agronomists and farmers with a solution for diagnosing plant diseases. By leveraging modern ICT capabilities, this extensible framework is currently trained for over 15 plant types and more than 51 disease types. Our framework employs a hybrid model combining use of both online and offline resources to provide up-to-date information to farmers even in case of patchy connectivity.