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Digital Twin Driven Intelligent Systems and Emerging Metaverse

  • Book
  • © 2023

Overview

  • Covers the application of Digital Twin in many fields
  • Explains the application potential of Digital Twin and its examples in different fields
  • Demonstrates the importance and application options of the Digital Twin to scientists and industry professionals

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Table of contents (17 chapters)

  1. Digital Twin Fundamentals

  2. Digital Twin Use Cases

Keywords

About this book

This book covers the notion of the digital twin, which has the potential to alter the way systems are governed and manufactured. It also addresses the metaverse as an emerging technology with its roots in literature, cross-platform avatars, and artificial intelligence-oriented cybersecurity issues. The untapped potential of the metaverse and digital twins as enabling technologies for the next-generation industries is emphasized in various chapters.

 

Digital twin technology enables manufacturers to comprehend their products throughout product design better, integrate simulation, tracking, and optimization in real-time, and appropriately analyze operations. Especially for complicated products or systems, testing on a digital twin is more efficient (more accessible, quicker, less error-prone, and less expensive). The product is examined in its virtual version before it is displayed in the actual world. Additionally, the digital twin minimizes operational expensesand increases the longevity of equipment and assets. By prolonging the life of the thing, they represent and enhance its working efficiency; it may minimize operating costs and prospective capital spending. The digital twin idea is becoming a reality as it has begun to be used in several industries, including energy, manufacturing, construction, transportation, aerospace, smart cities, healthcare, cyber security, finance, and agriculture. Academic and industrial experts highlighted the most compelling use cases of digital twins and metaverses and the challenges inherent in their implementation. Readers who want to make more effective systems will find the book useful. Also, people who want to get an idea and vision of how technology will change our lives will benefit from this book.

Editors and Affiliations

  • MSKU Metaverse Lab, Department of Computer Engineering, Faculty of Engineering, Mugla Sitki Kocman University, Mugla, Türkiye

    Enis Karaarslan

  • Department of Electrical and Electronics Engineering, Faculty of Engineering, Manisa Celal Bayar University, Manisa, Türkiye

    Ömer Aydin

  • Department of Electric Power Engineering, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology, Trondheim, Norway

    Ümit Cali

  • Department of Computer Science, University of Antwerp and Flanders Make Strategic Research Center, Flanders, Belgium

    Moharram Challenger

About the editors

Enis Karaarslan, Assist. Prof. Dr., Mugla Sitki Kocman University (MSKU), Department of Computer Engineering, Mugla, Türkiye

He is one of the founders of the Artificial Intelligence and Cyber ​​Security disciplines at MSKU. His research areas are; computer networks, cybersecurity, blockchain, data science, digital twin, and Metaverse. He provides consultancy to companies and research projects in the industry. He founded NetSecLab and the Metaverse research labs. He is the chief editor of the "Journal of Metaverse''. He formed MSKU Blockchain Research Group (MSKU BcRG) and has been working on the potential of blockchain since 2017. He has given various seminars and training on blockchain technology at multiple events. He taught blockchain courses at the graduate and undergraduate levels and acted as a thesis advisor. He has several publications and a patent on decentralized technologies. He founded MSKU Metaverse Research Group (MSKU MvRG) and has been conducting interdisciplinary studies there since 2021.

 

Ömer AYDIN, Assoc. Prof. Dr., Manisa Celal Bayar University, Manisa, Türkiye

Ömer Aydın received the B.S. degree in Computer Engineering from Istanbul Technical University of Turkey in 2007. He received the M.S. degree in Electrical and Electronics Engineering from Dumlupınar University, Kütahya, Turkey, in 2014 and Ph.D. degree in Computer Engineering from Dokuz Eylül University, Izmir, Turkey, in 2019. He has been an associate professor in the Department of Electrical and Electronics Engineering at Manisa Celal Bayar University, Manisa, Turkey. His research interests include random number generation, lightweight authentication protocols, cryptography, digital twin, cyber-physical systems, security of RFID systems, and other lightweight devices. He is a member of Dokuz Eylul University Security Research Group and the founder of the Izmir Academy Association. Assoc. Prof. Ömer Aydın is also a member of the Association for Information Systems (AIS).

 

Umit Cali, Assoc. Prof. Dr., Norwegian University of Science and Technology, Norway

Dr. Umit Cali has more than 20 years international experience in the fields of energy systems, data science, blockchain technologies, ICT, energy markets, and economics as a professor, an entrepreneur, a researcher, and a CTO. Dr. Cali is also the co-founder of US (NSF SBIR funded) and Europe-based technology startup companies which are active in advanced energy informatics and blockchain. He is working as an associate professor of Energy Informatics (AI & Blockchain) in the Norwegian University of Science and Technology. He is serving as the vice chair of IEEE Blockchain in Energy Standards WG (P2418.5), the chair of IEEE TEMS Special Interest Group on Energy DLT, and an IEEE senior member. Umit is the leading author of the “Digitalization of Power Markets and Systems using Energy Informatics” book.

 

Moharram Challenger, Assist. Prof. Dr., University of Antwerp, Antwerpen, Belgium

Prof. Moharram Challenger received his Ph.D. in IT from International Computer Institute at Ege University (Turkey) in Feb 2016. He also received his B.Sc. and M.Sc. degrees in computer engineering and software engineering in 2001 and 2005, respectively. From 2005 to 2009, he has been a faculty member, and a lecturer, in the computer engineering department at IAU-Shabestar University. From 2010 to 2013, he was a researcher and a team leader of a bilateral project between Slovenia and Turkey (TUBITAK). From 2012 to 2016, he was the R&D director of UNIT IT Ltd. involved in one national project funded by TUBITAK and two international software-intensive projects in Europe called ITEA ModelWriter and ITEA Assume. In 2017 and 2018, he was a faculty member as an assistant professor at Ege University. From January 2019 to July 2020, he was a postdoc researcher at the University of Antwerp, working on a Flanders Make projects called PACo and DTDesign. He is currently a tenure-track assistant professor in the Department of Computer Science at the University of Antwerp. He is also the core laboratory manager of AnSyMo/Cosys core laboratory of Flanders Make Strategic Research Center at the University of Antwerp. His research interests include domain-specific modeling languages, multi-agent systems, cyber-physical systems, the Internet of Things, and digital twins. Prof. Challenger is also a member of the IEEE and ACM.


Bibliographic Information

  • Book Title: Digital Twin Driven Intelligent Systems and Emerging Metaverse

  • Editors: Enis Karaarslan, Ömer Aydin, Ümit Cali, Moharram Challenger

  • DOI: https://doi.org/10.1007/978-981-99-0252-1

  • Publisher: Springer Singapore

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023

  • Hardcover ISBN: 978-981-99-0251-4Published: 09 April 2023

  • Softcover ISBN: 978-981-99-0254-5Published: 10 April 2024

  • eBook ISBN: 978-981-99-0252-1Published: 08 April 2023

  • Edition Number: 1

  • Number of Pages: VIII, 349

  • Number of Illustrations: 11 b/w illustrations, 77 illustrations in colour

  • Topics: Industrial and Production Engineering, Simulation and Modeling, Machine Learning, Artificial Intelligence, Computer Applications

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