Federated Learning for Smart Communication using IoT Application

By: Kaushal Kishor (Editor), Parma Nand (Editor), Vishal Jain (Editor)

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Hardcover | 30 October 2024 | Edition Number 1

At a Glance

Hardcover
276 Pages

Dimensions(cm)
23.39 x 15.6 x 1.75

Hardcover

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The effectiveness of federated learning in highâ'performance information systems and informaticsâ'based solutions for addressing current information support requirements is demonstrated in this book. To address heterogeneity challenges in Internet of Things (IoT) contexts, Federated Learning for Smart Communication using IoT Application analyses the development of personalized federated learning algorithms capable of mitigating the detrimental consequences of heterogeneity in several dimensions. It includes case studies of IoTâ'based human activity recognition to show the efficacy of personalized federated learning for intelligent IoT applications.

Features:

Demonstrates how federated learning offers a novel approach to building personalized models from data without invading usersâ privacy
Describes how federated learning may assist in understanding and learning from user behavior in IoT applications while safeguarding user privacy
Presents a detailed analysis of current research on federated learning, providing the reader with a broad understanding of the area
Analyses the need for a personalized federated learning framework in cloudâ'edge and wirelessâ'edge architecture for intelligent IoT applications
Comprises realâ'life case illustrations and examples to help consolidate understanding of topics presented in each chapter

This book is recommended for anyone interested in federated learningâ'based intelligent algorithms for smart communications.

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