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Elsevier

Federated Learning for the Metaverse

Applications in Virtual Environments

  • 1st Edition - March 1, 2027
  • Latest edition
  • Editors: Noor Zaman Jhanjhi, Mamoona Humayun, Faizan Ahmed, Momina Shaheen
  • Language: English

Federated Learning for the Metaverse: Applications in Virtual Environments provides readers with insights into how federated learning, a decentralized machine learning paradi… Read more

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Description

Federated Learning for the Metaverse: Applications in Virtual Environments provides readers with insights into how federated learning, a decentralized machine learning paradigm, can be strategically applied to address critical aspects of the metaverse. The book covers a wide range of topics, including privacy-preserving personalization, security, collaboration, adaptive learning environments, real-time communication, decentralized governance, language understanding, immersive learning experiences, avatar customization, and dynamic scene rendering.

Key features

  • Explores practical applications of federated learning within the metaverse, examining real-world scenarios and showcasing successful implementations
  • Offers diverse perspectives from experts in the fields of federated learning, virtual reality, augmented reality, and immersive technologies
  • Provides practical guidance on implementing federated learning techniques within metaverse applications, accompanied by code snippets and case studies
  • Addresses the ethical considerations and implications of utilizing federated learning in the metaverse, including privacy concerns and data governance
  • Discusses emerging trends at the intersection of federated learning and the metaverse

Readership

Researchers and academics in federated learning, machine learning, artificial intelligence, metaverse and virtual reality. Industry professionals working in the fields of immersive technologies, augmented reality, and virtual reality

Table of contents

1. Introduction to Federated Learning and the Metaverse

2. Federated Learning Models and algorithms for privacy-preserving personalization in Metaverse

3. Privacy-Preserving Personalization in the Metaverse

4. Security and Threat Detection in Virtual Environments

5. Cross-Platform Collaboration and Consistency

6. Adaptive and Immersive Learning Experiences with Federated Learning

7. Real-Time Communication Enhancement

8. Decentralized Governance and Regulation

9. Localized Language Understanding in a Multilingual Metaverse

10. Content Creation and Customization for Enhanced Experiences

11. Federated Learning for Metaverse: A Comprehensive Survey

12. Ethical Considerations and Future Trends

Product details

  • Edition: 1
  • Latest edition
  • Published: March 1, 2027
  • Language: English

About the editors

NJ

Noor Zaman Jhanjhi

Prof. Jhanjhi is Professor of Computer Science (Cybersecurity) and Program Director for Postgraduate Research Degree Programmes at the School of Computer Science, Taylor’s University, Malaysia. His research focuses on cybersecurity, IoT security, wireless security, data science, software engineering, and unmanned aerial systems. He has led and contributed to a wide range of international research and innovation activities, including patented technologies and collaborative projects. Prof. Jhanjhi has extensive experience supervising postgraduate researchers and has supported the successful completion of numerous doctoral and master’s studies. He serves on the editorial boards of several international journals and has held editorial leadership roles across the computing and engineering fields. He is also a frequent invited speaker and session chair at international conferences, contributing to global research communities and interdisciplinary collaboration in cybersecurity and related disciplines.
Affiliations and expertise
Taylor's University, Malaysia

MH

Mamoona Humayun

Dr. Mamoona is currently working as a Senior Lecturer with the Department of computing, School of Arts Humanities and Social Sciences, University of Roehampton, London, SW15 5PJ, United Kingdom. She has highly indexed publications in WoS/ISI/SCI/Scopus, and her collective research Impact factor is more than 200 plus points. Her Google Scholar H index is 38, and I-10 Index is 110 plus, with more than 200 publications on her credit. She has several international Patents on her account, including UK and Japanese. She edited/authored several research books published by world-class publishers. She has excellent experience of supervising and co-supervising postgraduate students, and a good number of Postgraduate scholars graduated under her supervision. Dr. Mamoona serves as a reviewer for several reputable journals. She has completed several funded research grants successfully. She has served as a Keynote/Invited speaker for many international conferences and workshops. She has vast experience in academic qualifications, including ABET, and NCAAA. Her research areas include Cyber Security, Wireless Sensor Networks (WSN), the Internet of Things (IoT), Requirement Engineering, Global Software Development, and Knowledge Management.

Affiliations and expertise
School of Arts Humanities and Social Sciences, University of Roehampton, London, UK

FA

Faizan Ahmed

Dr. Faizan Ahmed is a faculty member in the Department of Mechanical Engineering at Prince Mohammad Bin Fahd University, Al Khobar, Saudi Arabia, with over 10 years of teaching and research experience. His research focuses on enhancing the efficiency and sustainability of thermal systems for desalination through experimental investigations, energy and exergy analysis, mathematical modeling, and performance optimization using Response Surface Methodology. He has explored solar distillers, flash desalination systems, refrigeration systems, and various heat exchangers, including plate-type, concentric tube-type, and radiators. His recent work examines the interacting effects of process parameters such as salinity, flow rate, feed temperature, and vacuum pressure on desalination productivity. Dr. Ahmed has published more than 30 articles in peer-reviewed, Scopus-indexed journals and has been granted US patents for his innovative research on desalination systems.
Affiliations and expertise
Department of Mechanical Engineering, Prince Mohammad Bin Fahd University, Al Khobar, Saudi Arabia

MS

Momina Shaheen

Momina Shaheen is Lecturer of Computing, in University of Roehampton, London, United Kingdom. She has more than 6+ years of experience in research and academia. She has 10 journal and 3 conference publications. She is a Ph.D. Scholar of University of Management and Technology, Lahore, Pakistan. She earned her master’s in software engineering from Bahria University Islamabad Campus in 2016. She has supervised and initiated several projects in her career. She has led different project in Machine Learning, Data Science, Artificial Intelligence, Federated Learning, Agent-based Modelling, Cognitive Sciences and Distributed Systems.
Affiliations and expertise
Lecturer of Computing, Roehampton University, UK