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portada Federated Learning for Iot Applications
Type
Physical Book
Publisher
Language
English
Pages
265
Format
Paperback
Dimensions
23.4 x 15.6 x 1.5 cm
Weight
0.39 kg.
ISBN13
9783030855611

Federated Learning for Iot Applications

Satya Prakash Yadav (Illustrated by) · Bhoopesh Singh Bhati (Illustrated by) · Dharmendra Prasad Mahato (Illustrated by) · Springer · Paperback

Federated Learning for Iot Applications - Yadav, Satya Prakash ; Bhati, Bhoopesh Singh ; Mahato, Dharmendra Prasad

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Synopsis "Federated Learning for Iot Applications "

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 federated learning 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.

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