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Digital Twin Conceptual Model within the Context of Internet of Things

Author

Listed:
  • A. R. Al-Ali

    (Department of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, UAE)

  • Ragini Gupta

    (Department of Computer Science, Missouri University of Science and Technology, Rolla, MO 65409, USA)

  • Tasneem Zaman Batool

    (Department of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, UAE)

  • Taha Landolsi

    (Department of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, UAE)

  • Fadi Aloul

    (Department of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, UAE)

  • Ahmad Al Nabulsi

    (Department of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, UAE)

Abstract

As the Internet of Things (IoT) is gaining ground and becoming increasingly popular in smart city applications such as smart energy, smart buildings, smart factories, smart transportation, smart farming, and smart healthcare, the digital twin concept is evolving as complementary to its counter physical part. While an object is on the move, its operational and surrounding environmental parameters are collected by an edge computing device for local decision. A virtual replica of such object (digital twin) is based in the cloud computing platform and hosts the real-time physical object data, 2D and 3D models, historical data, and bill of materials (BOM) for further processing, analytics, and visualization. This paper proposes an end-to-end digital twin conceptual model that represents its complementary physical object from the ground to the cloud. The paper presents the proposed digital twin model’s multi-layers, namely, physical, communication, virtual space, data analytic and visualization, and application as well as the overlapping security layer. The hardware and software technologies that are used in building such a model will be explained in detail. A use case will be presented to show how the layers collect, exchange, and process the physical object data from the ground to the cloud.

Suggested Citation

  • A. R. Al-Ali & Ragini Gupta & Tasneem Zaman Batool & Taha Landolsi & Fadi Aloul & Ahmad Al Nabulsi, 2020. "Digital Twin Conceptual Model within the Context of Internet of Things," Future Internet, MDPI, vol. 12(10), pages 1-15, September.
    • Handle: RePEc:gam:jftint:v:12:y:2020:i:10:p:163-:d:420126
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    Citations

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    Cited by:

    1. João Vieira & João Poças Martins & Nuno Marques de Almeida & Hugo Patrício & João Gomes Morgado, 2022. "Towards Resilient and Sustainable Rail and Road Networks: A Systematic Literature Review on Digital Twins," Sustainability, MDPI, vol. 14(12), pages 1-23, June.
    2. Milena Kajba & Borut Jereb & Tina Cvahte Ojsteršek, 2023. "Exploring Digital Twins in the Transport and Energy Fields: A Bibliometrics and Literature Review Approach," Energies, MDPI, vol. 16(9), pages 1-23, May.
    3. Hazrathosseini, Arman & Moradi Afrapoli, Ali, 2023. "The advent of digital twins in surface mining: Its time has finally arrived," Resources Policy, Elsevier, vol. 80(C).
    4. Roberta Avanzato & Francesco Beritelli & Alfio Lombardo & Carmelo Ricci, 2023. "Heart DT: Monitoring and Preventing Cardiac Pathologies Using AI and IoT Sensors," Future Internet, MDPI, vol. 15(7), pages 1-16, June.
    5. Viktor Rjabtšikov & Anton Rassõlkin & Karolina Kudelina & Ants Kallaste & Toomas Vaimann, 2023. "Review of Electric Vehicle Testing Procedures for Digital Twin Development: A Comprehensive Analysis," Energies, MDPI, vol. 16(19), pages 1-17, October.

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