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      Federated Learning for IoT Applications

      1 in stock

      Firm sale: non returnable item
      SKU 9783030855581 Categories ,
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      This book presents how federated learning helps to understand and learn from user activity in Internet of Things (IoT) applications while protecting user privacy.
      This book presents how federated learning helps to understand and learn from user activity in Internet of Thing...

      £109.99

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      Description

      Product ID:9783030855581
      Product Form:Hardback
      Country of Manufacture:GB
      Series:EAI/Springer Innovations in Communication and Computing
      Title:Federated Learning for IoT Applications
      Authors:Author: Bhoopesh Singh Bhati, Satya Prakash Yadav, Sachin Kumar, Dharmendra Prasad Mahato
      Page Count:265
      Subjects:Cybernetics and systems theory, Cybernetics & systems theory, Computer hardware, Data mining, Artificial intelligence, Computer hardware, Data mining, Artificial intelligence
      Description:Select Guide Rating
      This book presents how federated learning helps to understand and learn from user activity in Internet of Things (IoT) applications while protecting user privacy.
      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. 
      Imprint Name:Springer Nature Switzerland AG
      Publisher Name:Springer Nature Switzerland AG
      Country of Publication:GB
      Publishing Date:2022-02-03

      Additional information

      Weight556 g
      Dimensions160 × 241 × 24 mm