Federated Learning for IoT Applications
(Sprache: Englisch)
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...
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Klappentext zu „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 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.
Inhaltsverzeichnis zu „Federated Learning for IoT Applications “
Chapter 1. Introduction to Federated Learning.- Chapter 2. Federated Learning for IoT Devices.- Chapter 3. Personalized Federated Learning.- Chapter 4. Federated Learning for an IoT Application.- Chapter 5. Some observations on the behaviour of Federated Learning.- Chapter 6. Federated Learning with Cooperating Devices: A Consensus Approach.- Chapter 7. A prospective study of federated machine learning in medical image fusion.- Chapter 8. Communication-Efficient Federated Learning in Wireless-Edge Architecture.- Chapter 9. Towards Ubiquitous AI in 6G with Federated Learning.- Chapter 10. Federated Learning using Tensor Flow.- Chapter 11. Cyber Security and privacy of Connected and Automated Vehicles (CAVs) based Federated Learning: Challenges, Opportunities and Open Issues.- Chapter 12. Security Issues & Solutions for Healthcare Informatics.- Chapter 13. Federated Learning: Challenges, Methods, and Future Directions.- Chapter 14. Quantum Federated Learning for Wireless Communications.- Chapter 15. Federated machine learning with data mining in health care.- Chapter 16. Federated Learning for data mining in Healthcare.Autoren-Porträt
Satya Prakash Yadav is currently the faculty of the Information Technology Department, ABES Institute of Technology (ABESIT), Ghaziabad (India). He has awarded his Ph.D. degree entitled "Fusion of Medical Images in Wavelet Domain" to Dr. A.P.J. Abdul Kalam Technical University (AKTU) (formerly UPTU). A seasoned academician having more than 13 years of experience, he has published three books (Programming in C, Programming in C++ and Blockchain and Cryptocurrency) under I.K. International Publishing House Pvt. Ltd. He has undergone industrial training programs during which he was involved in live projects with companies in the areas of SAP, Railway Traffic Management Systems, and Visual Vehicles Counter and Classification (used in the Metro rail network design). He is an alumnus of Netaji Subhas Institute of Technology (NSIT), Delhi University. A prolific writer, Dr. Satya Prakash Yadav has published two patents and authored many research papers in web of science indexed journals. Additionally, he has presented research papers at many conferences in the areas of Image Processing,Information Retrieval, Feature Extracction and Programming, such C, Data Structure, C++, C# and Java. Also, he is a lead editor in Science Publishing Group,(U.S.A), and Eureka Journals , Pune ( India).Dr.Bhoopesh Singh Bhati is an Assistant Professor in Ambedkar Institute of Advanced Communication Technologies & Research Govt. of N.C.T Delhi, Geeta colony, Delhi, India. He received his Ph.D (Computer Science and Engineering) from the University School of Information Communication and Technology, Guru Gobind Singh Indraprastha University, Delhi. He has obtained his M.tech (Information Security) and B.tech.(Computer Science and Engineering) from Guru Gobind Singh Indraprastha University, Delhi, in 2009 and 2012 respectively. Dr.Bhatihas published various research papers in highly reputed, SSCI/SCI/SCIE- Indexed Journals including Elsevier, Wiley, Springer, Inderscience, etc. He is a
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reviewer of various reputed journals of Elsevier, Wiley, Springer, etc. Dr.Bhati has also participated and presented paper in Springer International Conference (RICE 2019) held in Vietnam. His current research area Intrusion Detection, Information Security, Data Science and IOT.
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Bibliographische Angaben
- 2022, 1st ed. 2022, VIII, 265 Seiten, 59 farbige Abbildungen, Masse: 15,5 x 23,5 cm, Gebunden, Englisch
- Herausgegeben: Satya Prakash Yadav, Bhoopesh Singh Bhati, Dharmendra Prasad Mahato, Sachin Kumar
- Verlag: Springer, Berlin
- ISBN-10: 3030855589
- ISBN-13: 9783030855581
Sprache:
Englisch
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