Federated Learning for IoT Applications

Inbunden, Engelska, 2022

Av Satya Prakash Yadav, Bhoopesh Singh Bhati, Dharmendra Prasad Mahato, Sachin Kumar, Bhoopesh Singh Bhati

1 679 kr

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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. 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.

Produktinformation

  • Utgivningsdatum2022-02-03
  • Mått155 x 235 x 24 mm
  • Vikt556 g
  • FormatInbunden
  • SpråkEngelska
  • SerieEAI/Springer Innovations in Communication and Computing
  • Antal sidor265
  • FörlagSpringer Nature Switzerland AG
  • ISBN9783030855581

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