Digital Twin represents the indistinguishable digital counterpart of the physical object to simulate, monitor and test with real time synchronization. This book presents the framework and important key aspects of digital twins including various technologies with coverage of the digital twins in various industry and business applications. It gives the background in modeling and simulation, computer, sensor technology, and other areas required creating the next wave of digital twins.
Features:
- Presents exclusive material on industrial and business applications of Digital Twins.
- Includes diversified digital twin applications with use cases.
- Focusses on Tools and methods for Digital twin, platforms and application domain & industries.
- Emphasizes the advances and cutting-edge technologies throughout.
- Reviews Artificial Intelligence, fog/edge computing, industrial automation, blockchain and IoT.
This book is aimed at researchers and graduate students in Cloud Computing, Simulation, and IoT including computer engineering.
This book presents the framework and important key aspects of digital twins including various technologies with coverage of the digital twins in various industry and business applications. It gives the background in modeling and simulation, computer, sensor technology, and other areas required creating the next wave of digital twins.
Part
1. Concepts and Architecture.
1. A Perspective on Digital Twins as an Emerging Technology.
2. Architecture of Digital Twin and Applications.
3. Unlocking Business Potential with Human Digital Twins: A Journey Towards Human-Centricity, Sustainability, and Resilience.
4. Digital Platforms for Business Applications. Part
2. Technologies.
5. Digital Twin and Artificial Intelligence.
6. Blockchain Empowered Digital Twins: A Comprehensive Review of Integration and Innovation.
7. Big Data and Digital Twin.
8. Unlocking Value: Big Data, Digital Twins, exploring the future Digital Transformation and its Trends. Part 3 Applications.
9. Digital Twin in Industry 4.0 Automation.
10. Leveraging Digital Twins for Optimal Automation and Smart Decision-Making in Industry 4.0: Revolutionizing Automation and Efficiency.
11. Digital Twin for Smart Manufacturing.
12. Digital Twin for an Irrigation System.
13. Diagnostics, Treatment, and Patient Care in the Age of Digital Twins: A Game-Changer in Healthcare. Part 4 Case Study and Challenges.
14. Digital Twin in Industry 5.0: Some Challenges and Future Directions.
15. Researching Trends on Smart Tourism Technology using Bibliometric Analysis.
16. Customised Cancer Care using Digital Twins - The Case of Breast Cancer in Women.
17. Digital Twin in Water Utilization: A Case Study to Estimate the Prediction of Water Usage.
Saravanan Krishnan is Associate Professor in the Department of Computer Science & Engineering at the College of Engineering, Guindy, Anna University, Chennai, Tamil Nadu. He has done an ME in Software Engineering and a PhD in Computer Science Engineering. His research interests include cloud computing, software engineering, the Internet of Things (IoT), and smart cities. He has published papers in 14 international conferences and 30 international journals. He has also written 16 book chapters and edited eight books with international publishers. He has done numerous consultancy work for municipal corporations and smart city schemes. He is an active researcher and academic. He is also a reviewer for many reputed journals. He is a member of the ISTE, IEI, ISCA, ACM and others.
A. Jose Anand is Professor in the Department of Electronics and Communication Engineering, KCG College of Technology, Chennai, Tamil Nadu. He has one year of industrial experience and 24 years of teaching experience. He has presented several papers at national and international conferences. He has published several papers in national and international journals, as well as books on polytechnic and engineering subjects. He is a member of the CSI, IEI, IET, IETE, ISTE, INS, QCFI and EWB. His current research interest is in wireless sensor networks, embedded systems, IoT, machine learning and image processing.
S. Sendhilkumar is Professor in the Department of Information Science and Technology, CEG, Anna University, with 18 years of teaching experience in data mining, machine learning, data science and social network analytics. His research interests include personalized information retrieval, bibliometrics and social network mining. He has authored the book Concepts, Techniques and Applications. He received the CTS Best Faculty Award for 2018 and was awarded with Visvesvaraya Young Faculty Research Fellowship by the Ministry of Electronics and Information Technology (MeitY), Government of India, for 2019 2021. He has authored/ coauthored textbooks on the fundamentals of computing and machine learning. He has developed e-content (40 modules with all four quadrants) for the course on data analytics for the E-Pathsala project of MHRD-UGC under its national mission on education through ICT. He has delivered live cast lecture series Edusat Programme on Artificial Intelligence for the engineering colleges affiliated with Anna University.
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