Metaconstructs: The Evolution of Digital Twins in the Metaverse Era - Couverture souple

Couverture souple

ISBN 10 : 0443406782 ISBN 13 : 9780443406782

Editeur : Elsevier - Health Sciences Division, 2026

Synopsis

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.

A propos du livre

À propos des auteurs

Dr. Chiranji Lal Chowdhary is an Associate Professor at the School of Computer Science Engineering and Information Systems, within the
Vellore Institute of Technology, Vellore in India.

Dr. Abhishek Ranjan is Deputy Vice Chancellor at Botho University, Gaborone in Botswana.

Jyotir Moy Chatterjee is currently an Assistant Professor in Department of Computer Science and Engineering at Graphic Era (Deemed to be University), in Dehradun, India. He also serves as a Visiting Faculty member in Information Technology at Lord Buddha Education Foundation, which is affiliated with the Asia Pacific University of Technology & Innovation in Kathmandu, Nepal. His research interests focus on advancements in Machine Learning and Deep Learning.

Dr. Pawan Lingras, is a Professor in the Department of Math and Computing Science, Saint Mary's University, Halifax, Nova Scotia, in Canada.

Détails de l'édition

• Éditeur: Elsevier - Health Sciences Division
• Date d'édition: 2026
• Langue: anglais
• ISBN 10: 0443406782
• ISBN 13: 9780443406782
• Reliure: Broché
• Nombre de pages: 306
• Éditeur: Chowdhary PhD Chiranji Lal, Ranjan Dr Abhishek, Moy Chatterjee PhD Jyotir, Lingras PhD Pawan
• Coordonnées du fabricant: ELSEVIER; https://www.elsevier.com/es-es; ; Mooswaldallee 6; Freiburg; 79108; Allemagne