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Federated learning applications in t...

Mohana, Rajni.

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Federated learning applications in the Industrial Internet of Everything (IoE)

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Federated learning applications in the Industrial Internet of Everything (IoE) / edited by Rajni Mohana ... [et al.].
其他作者:	Mohana, Rajni.
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	xii, 287 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Internet of things. -
電子資源:	https://doi.org/10.1007/978-3-031-99270-4
ISBN:	9783031992704

Federated learning applications in the Industrial Internet of Everything (IoE)
Federated learning applications in the Industrial Internet of Everything (IoE) [electronic resource] /edited by Rajni Mohana ... [et al.]. - Cham :Springer Nature Switzerland :2025. - xii, 287 p. :ill., digital ;24 cm. - Studies in systems, decision and control,v. 6112198-4190 ;. - Studies in systems, decision and control ;v. 611..

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.

This 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.

ISBN: 9783031992704

Standard No.: 10.1007/978-3-031-99270-4doiSubjects--Topical Terms:

2057703
Internet of things.

LC Class. No.: TK5105.8857

Dewey Class. No.: 004.678

Federated learning applications in the Industrial Internet of Everything (IoE)
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520 $a This 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.
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