Digital Twin Technology and Applications

ISBN 10: 1032430591 / ISBN 13: 9781032430591

Editore: Auerbach Publications, 2024

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Dati bibliografici

• Titolo: Digital Twin Technology and Applications
• Editore: Auerbach Publications
• Data di pubblicazione: 2024
• Lingua: Inglese
• ISBN 10: 1032430591
• ISBN 13: 9781032430591
• Rilegatura: hardcover
• Condizione: Very Good

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Riassunto

The Fourth Industrial Revolution is being accelerated by the digital twin technological revolution, which converges intelligent technologies and defines the connectivity between physical and digital items. The Internet of Things (IoT) connects the real and digital worlds, allowing connected items to deliver a vast array of services to internet users. IoT devices create large amounts of data that may be fed into AI systems for decision- making. In a decentralized architecture, digital twin technology may be utilized to protect platforms and create smart contracts. Digital twins decentralized ledger, immutability, self- sovereign identification, and consensus procedures hold a lot of promise for improving AI algorithms. Furthermore, leveraging smart contracts in a digital twin system to facilitate user interaction via IoT might have a big influence, and this integrated platform is expected to revolutionize many fields.

Digital Twin Technology and Applications examines the problems, issues, and solutions for using big data to enable streaming services using IoT and AI with digital twin technology. The IoT network concept is the key to success, and to establish a solid IoT platform on which large data transmission may take place, it must handle protocol, standards, and architecture. The book provides insight into the principles and techniques of IoT and AI. It explores the idea of using blockchain to provide security in a variety of sectors. The book also covers the application of integrated technologies to strengthen data models, improve insights and discoveries, innovate audit systems, as well as digital twin technology application to intelligent forecasting, smart finance, smart retail, global verification, and transparent governance.

Informazioni sull?autore

A. Daniel is an Associate Professor in the School of Computing Science and Engineering, Galgotias University, India He has 12 years of experience in academics.

Srinivasan Sriramulu is a professor in the School of Computing Science and Engineering, Galgotias University, India. He has more than 22 years of experience of teaching. He is expertise in image processing, Big Data, cloud, IoT and Artificial Intelligence.

N Partheeban is a professor at the School of Computing Science and Engineering, Galgotias University.

Santhosh Jayagopalan is with the Faculty in Computer Science, British Applied College, Umm Al Qwain, United Arab Emirates.