Federated Learning for Smart Agriculture: Challenges and Opportunities

Abstract

FL is a machine learning approach that allows knowledge sharing with privacy maintenance and cost reduction. FL has the potential to revolutionize the smart agriculture sector by enabling farmers to train and deploy machine learning models on their own devices, without the need to share their data with a central server. In this article, we review the applications of FL in smart agriculture, such as disease diagnosis and severity assessment, the Internet of Agricultural Things (IoAT), and yield forecasting. We also highlight the challenges and opportunities of using FL for smart agriculture.

Topics & Concepts