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The Digital Twin Paradigm for Smarter Systems and Environments: The Industry Use Cases

  • Book

  • January 2020
  • Elsevier Science and Technology
  • ID: 4829351

The Digital Twin Paradigm for Smarter Systems and Environments: The Industry Use Cases, Volume 117, the latest volume in the Advances in Computers series, presents detailed coverage of new advancements in computer hardware, software, theory, design and applications. Chapters vividly illustrate how the emerging discipline of digital twin is strategically contributing to various digital transformation initiatives. Specific chapters cover Demystifying the Digital Twin Paradigm, Digital Twin Technology for "Smarter Manufacturing", The Fog Computing/ Edge Computing to leverage Digital Twin, The industry use cases for the Digital Twin idea, Enabling Digital Twin at the Edge, The Industrial Internet of Things (IIOT), and much more.

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Table of Contents

1. Stepping into the digitally instrumented and interconnected era Pethuru Raj and Jenn-Wei Lin 2. Digital twin technology for "smart manufacturing" Preetha David and Anandhakumar 3. The fog computing/edge computing to leverage digital twin J. Pushpa and Kalayani 4. The industry use cases for the Digital Twin idea Peter Augustine 5. Digital twin: Empowering edge devices to be intelligent Vidya Hungud and Senthil Kumar Arunachalam 6. The industrial internet of things (IIoT) Sathyan Munirathinam 7. The growing role of integrated and insightful big and real-time data analytics platforms Indrakumari Ranganathan, Poongodi Thangamuthu, Suresh Palanimuthu and Balamurugan Balusamy 8. Air pollution control model using machine learning and IoT techniques Chetan Shetty, B.J. Sowmya, S. Seema and K.G. Srinivasa 9. The human body: A digital twin of the cyber physical systems Janet Barnabas and Pethuru Raj 10. Impact of cloud security in digital twin Susila Nagarajan, Sruthi Anand and Usha Sakthivel 11. Digital twin in consumer choice modeling D. Sudaroli Vijayakumar 12. Digital twin: The industry use cases Pethuru Raj and Chellammal Surianarayanan 13. Machine learning and deep learning algorithms on the Industrial Internet of Things (IIOT) P. Ambika 14. Energy-efficient edge based real-time healthcare support system S. Abirami and P. Chitra