Federated learning (FL), with the aim of training machine learning models using data and
computational resources on edge devices without sharing raw local data, is essential for …

Abstract The Internet of Things (IoT) has embedded itself in our daily lives, offering smart
services and AI-driven applications. However, traditional AI methods face challenges due to …

Simple Summary This study addresses the classification task in animal science, which helps
organize and analyze complex data, essential for making informed decisions. It introduces …

The ability to monitor ambient characteristics, interact with them, and derive information
about the surroundings has been made possible by the rapid proliferation of edge sensing …

Although federated learning is gaining prevalence in smart sensor networks, substantial
risks to data privacy and security persist. An improper application of federated learning …

This letter explores the integration of Federated Learning (FL) techniques into edge
networks to address the pressing issue of inefficient irrigation practices in paddy fields by …

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 …

The global agricultural sector confronts significant obstacles such as population growth,
climate change, and natural disasters, which negatively impact food production and pose a …