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OverviewThis book presents a comprehensive exploration of federated learning and its transformative potential across industries, focusing on privacy-preserving, decentralized AI solutions. It introduces novel frameworks and applications in healthcare, smart transportation, energy optimization, and Industry 4.0, emphasizing real-world use cases and addressing key challenges in privacy, scalability, and collaboration. By bridging theory and practice, the book provides actionable insights into implementing federated learning for dynamic, interconnected ecosystems like the Industrial Internet of Everything (IoE). Aimed at researchers, practitioners, and policymakers, it offers cutting-edge strategies to enhance efficiency, security, and innovation in diverse industrial domains. Full Product DetailsAuthor: Rajni Mohana , Aman Sharma , Anand Nayyar , Poonam SainiPublisher: Springer International Publishing AG Imprint: Springer International Publishing AG Volume: 611 ISBN: 9783031992698ISBN 10: 3031992695 Pages: 287 Publication Date: 27 September 2025 Audience: Professional and scholarly , College/higher education , Professional & Vocational , Postgraduate, Research & Scholarly Format: Hardback Publisher's Status: Active Availability: Manufactured on demand We will order this item for you from a manufactured on demand supplier. Table of Contents.- Introduction to Federated Learning and its applications in the IoE.- Techniques used in Federated Learning.- Federated Learning in the Manufacturing Industry.- Federated Learning in the Transportation Industry.- Federated Learning in the Healthcare Industry.- Challenges and Opportunities in Federated Learning for the IoE.- Conclusion and future research directions, etc.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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