Federated Learning for IoT Applications

Beschreibung

Druck auf Anfrage Neuware - Printed after ordering - This book presents how federated learning helps to understand and learn from user activity in Internet of Things (IoT) applications while protecting user privacy. The authors first show how federated learning provides a unique way to build personalized models using data without intruding on users' privacy. The authors then provide a comprehensive survey of state-of-the-art research on federated learning, giving the reader a general overview of the field. The book also investigates how a personalized federated learning framework is needed in cloud-edge architecture as well as in wireless-edge architecture for intelligent IoT applications. To cope with the heterogeneity issues in IoT environments, the book investigates emerging personalized federated learning methods that are able to mitigate the negative effects caused by heterogeneities in different aspects. The book provides case studies of IoT based human activity recognition to demonstrate the effectiveness of personalized federatedlearning for intelligent IoT applications, as well as multiple controller design and system analysis tools including model predictive control, linear matrix inequalities, optimal control, etc. This unique and complete co-design framework will benefit researchers, graduate students and engineers in the fields of control theory and engineering.

Bestandsnummer des Verkäufers 9783030855611

Verkäufer kontaktieren

Diesen Artikel melden

Bibliografische Details

Titel

Federated Learning for IoT Applications

Verlag

Springer International Publishing, Springer International Publishing

Erscheinungsjahr

2023

Sprache

Englisch

ISBN-10

3030855619

ISBN-13

9783030855611

Einband

Taschenbuch

Zustand

Neu