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

Record Type:	Electronic resources : Monograph/item
Title/Author:	Federated learning applications in the Industrial Internet of Everything (IoE) edited by Rajni Mohana ... [et al.].
other author:	Mohana, Rajni.
Published:	Cham :Springer Nature Switzerland :2025.
Description:	xii, 287 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Internet of things.
Online resource:	https://doi.org/10.1007/978-3-031-99270-4
ISBN:	9783031992704$q(electronic bk.)

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.3..

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$q(electronic bk.)

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

670954
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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245 0 0 $a Federated learning applications in the Industrial Internet of Everything (IoE) $h [electronic resource] / $c edited by Rajni Mohana ... [et al.].
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505 0 $a 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.
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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650 2 4 $a Communications Engineering, Networks. $3 273745
650 2 4 $a Mathematical and Computational Engineering Applications. $3 915034
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