1st Edition
Digital Twin Technology and Applications
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.
1. Digital Twin Past, Present and Future
A.M. SERMAKANI, R. RADHIKA, AND V. SUJATHA
2. Digital Twin Types and Design
Pallavi Jain, Sunil Kumar Boran, Bhairvee Singh, and Pankaj Singh
3. Real Issues, Opportunities, and Open Investigations in Digital Twins
V. Sheeja Kumari, T. Manikandan, M.J. Carmel Mary Belinda, A. Selva Kumar, and K. Prabu
4. Twin Technology: Exploring Types and Applications of Digital Twins
S.Dinesh Krishnan, K.V. Mahalakshmi, Dyagala Naga Sudha, V. Sathya Priya, and A. Daniel
5. The Convergence of Data Analytics, Digital Twins, and the IoT/IIoT: A New Era of Data-Driven Decision Making
S. Geerthik, N. Vel Murugesh Kumar, P.V. Gopirajan, and B. Jaison
6. Simulation Strategies for Analyzing of Data
S.S. Darly and D. Kadhiravan
7. Navigating the Complexities of Digital Twin Implementation: Challenges and Strategies for Success
M. Arvindhan, S. Nivetha, Raghvendra Ajay Mishra, and A. Daniel
8. Using Improved Finite Element Modelling to Combat Cardiovascular Disease: A Review of a Developing Area at the Intersection of Several Disciplines
V. Sheeja Kumari, T. Manikandan, A. Selva Kumar, S. Ponmaniraj, and K. Prabu
9. Comprehensive Study of Digital Twin in Smart and Customized Healthcare
Salna Joy, R. Baby Chithra, and Ajay Sudhir Bale
10. Sustainable Organic Farming in Indian Rural Areas with Aid of the Internet of Things
R. Rajesh, S. Sivakumar, and S. Premkumar
11. Predictive Analysis of Toxic Ions and Water Quality Based on Sensor Data using LSTM and ARIMA Models
Vallidevi Krishnamurthy, P.R. Joe Dhanith, R. Sujithra Kanmani, Surendiran Balasubramanian, and N. Rekha
12. Digital Representation of Agriculture Forms
K. Rajasathiya
13. Accelerators for Clustering Applications in Machine Learning
Mrinalika Durairaju, Mrinalini Durairaju, Vallidevi Krishnamurthy, Sakthivel V, and Surendiran Balasubramanian
14. Design of a Smart Healthcare Environment with Digital Twinning and Machine Learning
S. Geetha, J. Madhusudanan, and V. Prasanna Venkatesan
15. FloodWatch: Suggesting an IoT-Driven Flood Monitoring and Early Warning System for the Flood-Prone Cuddalore District in the Indian State of Tamilnadu
R. Indrakumari, S. Srinivasan, N. Partheeban, and Rajkumar Rajavel
Biography
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.
