Advancements in Federated Intelligence and Decentralized IoT Systems

This book series explores the rapid convergence of Internet of Things (IoT) ecosystems and advanced Machine Learning, highlighting privacy-preserving paradigms such as Federated Learning that have become essential for handling decentralized data. It aims to bridge the gap between intelligent optimization algorithms, edge-cloud architectures, and trustworthy AI. The series covers cutting-edge topics including communication-efficient federated learning, bio-inspired optimization in heterogeneous networks, privacy-preserving IoT frameworks, and real-world applications in healthcare, smart cities, and Industry 4.0.