Privacy-Preserving AI in Agriculture: A Review of Federated Learning Approaches
Jigar A. Soni, Nitin R. Pandya, Rajan B. Patel, Jinit S. Raval · SPU Journal of Science Technology and Management Research · 2025
Federated Machine Learning (FML) is a revolutionary approach for training machine learning models while ensuring data privacy and security. This paper provides a comprehensive analysis of FML and its applications in agriculture. We examine how FML enhances predictive analytics, fosters collaborative learning among agricultural stakeholders, and addresses challenges such as communication constraints and data heterogeneity. Additionally, we explore real-world implementations and present relevant datasets that highlight the impact of FML on modern agricultural practices.