Digital Twins for Healthcare: Design, Challenges and Solutions establishes the state-of-art in the specification, design, creation, deployment and exploitation of digital twins' technologies for healthcare and wellbeing. A digital twin is a digital replication of a living or non-living physical entity. When data is transmitted seamlessly, it bridges the physical and virtual worlds, thus allowing the virtual entity to exist simultaneously with the physical entity. A digital twin facilitates the means to understand, monitor, and optimize the functions of the physical entity and provide continuous feedback. It can be used to improve citizens' quality of life and wellbeing in smart cities and the virtualization of industrial processes.
Abdulmotaleb El Saddik is a full professor at MBZUAI and Distinguished University Professor in the School of Electrical Engineering and Computer Science at the University of Ottawa. His research focus is on the establishment of Digital Twins to facilitate the wellbeing of citizens using AI, AR/VR, and Tactile Internet, hence allowing people to interact in real-time with one another, as well as with their digital representation. He has authored and coauthored 10 books and more than 550 publications, and chaired more than 50 conferences and workshop. He has received research grants and contracts totaling more than $20M and has supervised more than 150 researchers. He is a Fellow of the Royal Society of Canada, Fellow of IEEE, Fellow of the Canadian Academy of Engineering, and Fellow of the Engineering Institute of Canada. He is an ACM Distinguished Scientist and has received several awards, including the Friedrich Wilhelm Bessel Award from the German Humboldt Foundation, as well as the IEEE Instrumentation and Measurement Society Technical Achievement Award. He also received IEEE Canada C.C. Gotlieb (Computer) Medal and A.G.L. McNaughton Gold Medal for important contributions to the field of computer engineering and science and the IEEE TCSC Achievement Award for Excellence in Scalable Computing.
Title: Digital Twin for Healthcare: Design, Challenges, and Solutions
Author:
ISBN: 9780323991636
Binding:
Publisher: Elsevier Science & Technology
Publication Date: 2022-11-23
Number of Pages: 378
Weight: 0.5842 kg
