Federated Learning in Smart Agriculture: An Overview

Agriculture is critical to the socioeconomic growth of countries across the world. Agricultural methods in many countries have been affected by current scientific and technical breakthroughs. However, ASEAN nations, which rely largely on agriculture, have an urgent need for smart agricultural research. While detailed assessments have been undertaken throughout the world, a gap in the research of federated learning has been observed. This article intends to fill this need by collecting research on machine learning, deep learning, and federated learning techniques in agriculture from both industrialized countries and those with economic constraints similar to those of ASEAN. Analyses have revealed that the combination of federated learning with IoT devices is the best way to develop smart agriculture.