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.
The goal of this book is to examine problems, concerns, and solutions for supporting digital twins with Big Data and Artificial Intelligence (AI). The book also explains how to stream real-time big data on an IoT platform using various ways and strategies.
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
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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