Applications of Federated Learning in Technological Advancements: Use Cases and Applications by S. Jayachitra, A. Prasanth, Rajesh Kumar Dhanaraj, Balasubramaniam S & Danilo Pelusi instant download
This book explores the applications and advancements of federated learning across diverse sectors, focusing on its integration with cutting-edge technologies like Internet of Things (IoT), artificial intelligence (AI), blockchain, and digital twins. Real-world examples and case studies illustrate federated learningâ••s role in healthcare, smart cities, and maritime applications while addressing critical concerns such as security. It provides insights into federated learningâ••s transformative potential, offering practical strategies for intelligent systems and sustainable environments. The book particularly:
Focuses on the federated learningâ••based model optimization, addressing the significance of IoT and federated learning in the evolution of intelligent systems for various applications;It covers fundamental concepts, practical implementations, and trends to serve as a reference resource for professionals and researchers in the field.Describes the different optimization techniques of federated learning systems from a practical point of view;Highlights economic, social, and environmental impacts of smart technologies and provides insights into IoT, 5G/6G communication, and computing standards;Provides analysis of the use cases of federated learning regarding the development of IoT, AI, blockchain, digital twins;Offers strategies for overcoming challenges associated with federated learning systems, including connectivity, computation, threats, privacy, and security issues.
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