Digital Twin Technology and Applications

Author:   A. Daniel ,  Srinivasan Sriramulu ,  N. Partheeban ,  SANTHOSH JAYAGOPALAN
Publisher:   Taylor & Francis Ltd
ISBN:  

9781032745176


Pages:   390
Publication Date:   21 May 2026
Format:   Paperback
Availability:   Not yet available   Availability explained
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Digital Twin Technology and Applications


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Full Product Details

Author:   A. Daniel ,  Srinivasan Sriramulu ,  N. Partheeban ,  SANTHOSH JAYAGOPALAN
Publisher:   Taylor & Francis Ltd
Imprint:   Auerbach
ISBN:  

9781032745176


ISBN 10:   1032745177
Pages:   390
Publication Date:   21 May 2026
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Forthcoming
Availability:   Not yet available   Availability explained
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

Table of Contents

1. Digital Twin Past, Present and Future 2. Digital Twin Types and Design 3. Real Issues, Opportunities, and Open Investigations in Digital Twins 4. Twin Technology: Exploring Types and Applications of Digital Twins 5. The Convergence of Data Analytics, Digital Twins, and the IoT/IIoT: A New Era of Data-Driven Decision Making 6. Simulation Strategies for Analyzing of Data 7. Navigating the Complexities of Digital Twin Implementation: Challenges and Strategies for Success 8. Using Improved Finite Element Modelling to Combat Cardiovascular Disease: A Review of a Developing Area at the Intersection of Several Disciplines 9. Comprehensive Study of Digital Twin in Smart and Customized Healthcare 10. Sustainable Organic Farming in Indian Rural Areas with Aid of Internet of Things (IoT) 11. Predictive Analysis of Toxic Ions and Water Quality Based on Sensor Data Using LSTM and ARIMA Models 12. Digital Representation of Agriculture Forms 13. Accelerators for Clustering Applications in Machine Learning 14. Design of a Smart Healthcare Environment with Digital Twinning and Machine Learning 15. FloodWatch: Suggesting an IoT-Driven Flood Monitoring and Early Warning System for the Flood-Prone Cuddalore District in the Indian State of Tamilnadu

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Author Information

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.

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