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Metaconstructs

The Evolution of Digital Twins in the Metaverse

  • 1st Edition - March 1, 2026
  • Editors: Chiranji Lal Chowdhary, Abhishek Ranjan, Jyotir Moy Chatterjee, Pawan Lingras
  • Language: English
  • Paperback ISBN:
    9 7 8 - 0 - 4 4 3 - 4 0 6 7 8 - 2
  • eBook ISBN:
    9 7 8 - 0 - 4 4 3 - 4 0 6 7 9 - 9

Digital twins integrate IoT, artificial intelligence, machine learning, and analytics with a graphic and/or spatial representation to make animate digital simulation models that… Read more

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Digital twins integrate IoT, artificial intelligence, machine learning, and analytics with a graphic and/or spatial representation to make animate digital simulation models that can change and develop as their physical counterpart does. A digital twin learns and updates itself continuously using real-time data from sensors on the physical asset to represent operating, environmental, and working conditions in near real-time.

The metaverse technology represents a comprehensive virtual world, where everything and everyone interacts similarly to what we would do in the real world. The concept of metaverse has gained a lot of prominence after several cryptocurrency networks adopted the technology. With the metaverse technology, a virtual reality becomes a persistent virtual environment that exists even when you are not engaging with it.

The digital twin in IoT (Internet of things) and the metaverse are the next big step in our technological evolution as these two technologies continue to shorten the gap between the human and the digital world. MetaConstructs: The Evolution of Digital Twins in the Metaverse Era provides information on emerging fields of next-generation digital twins with a special emphasis on emerging developments and applications of the metaverse, IoT, artificial intelligence, deep learning techniques, virtual reality, augmented reality, internet of medical things (IoMT), optimization techniques, decision making, and cloud computing.

The book provides a conceptual framework and roadmap for decision-makers for this transformation. It can be useful for undergraduate and postgraduate students who have studied artificial intelligence, federated learning, ML/DL, computational intelligence, IoT, cloud computing, and genetic algorithms in their academic curriculum. This book will be useful for students to develop and deploy their skills to achieve a thorough knowledge of analytics and in-depth education experience to focus on their unique interests. Acknowledging the huge demands of professionals in the industry today, this book has been designed to create trained Computer Science graduates to fulfil the requirements of the industry.

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