Digital Twin Technologies and Smart Cities

Maryam Farsi (Editor), Alireza Daneshkhah (Editor), Amin Hosseinian-Far (Editor), Hamid Jahankhani (Editor)

    Research output: Book/ReportBookpeer-review


    This book provides a holistic perspective on Digital Twin (DT) technologies, and presents cutting-edge research in the field. It assesses the opportunities that DT can offer for smart cities, and covers the requirements for ensuring secure, safe and sustainable smart cities. Further, the book demonstrates that DT and its benefits with regard to:

    data visualisation, real-time data analytics, and learning leading to improved confidence in decision making; reasoning, monitoring and warning to support accurate diagnostics and prognostics; acting using edge control and what-ifanalysis; and connection with back-end business applications hold significant potential for applications in smart cities, by employing a wide range of sensory and data-acquisition systems in various parts of the urban infrastructure.

    The contributing authors reveal how and why DT technologies that are used for monitoring, visualising, diagnosing and predicting in real-time are vital to cities’ sustainability and efficiency. The concepts outlined in the book represents a city together with all of its infrastructure elements, which communicate with each other in a complex manner. Moreover, securing Internet of Things (IoT) which is one of the key enablers of DT’s is discussed in details and from various perspectives.

    The book offers an outstanding reference guide for practitioners and researchers in manufacturing, operations research and communications, who are considering digitising some of their assets and related services. It is also a valuable asset for graduate students and academics who are looking to identify research gaps and develop their own proposals for further research.
    Original languageEnglish
    Number of pages212
    ISBN (Electronic)978-3-030-18732-3
    ISBN (Print)978-3-030-18731-6
    Publication statusPublished - 2020


    • Visualization solution for smart cities
    • Predicting efficiency of cities
    • Digital Twins
    • internet of things
    • smart cities
    • Asset Management
    • Artificial intelligence
    • Digital Twin visualization
    • Diagnosing sustainability of cities
    • Digital twin city
    • Real-time analysis of city data


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