Combating Counterfeit Products in Smart Cities with Digital Twin Technology

  • Muhammad Saad
  • , Mustaqeem Khan
  • , Muhammad Saeed
  • , Abdulmotaleb El Saddik
  • , Wail Gueaieb

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Digital twins are rapidly emerging as a new foundation for building smarter cities. This technology allows for the creation of virtual replicas of physical objects and systems, enabling real-time monitoring and analysis. Counterfeit products have become a major concern in the global market, especially in smart cities. This paper takes a 5-dimensional digital twin model approach to examine and summarize commonly used enabling technologies and tools for digital twin applications to address this issue. A 5-dimensional digital twin model is an advanced representation of a physical object or system encompassing different dimensions. In the context of digital twin technology, dimensions refer to different aspects or attributes that can be captured and simulated for a more comprehensive understanding of the object or system. By doing so, it aims to provide a comprehensive reference for implementing digital twins in the future.

Original languageEnglish
Title of host publicationProceedings of 2023 IEEE International Smart Cities Conference, ISC2 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350397758
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event9th IEEE International Smart Cities Conference, ISC2 2023 - Bucharest, Romania
Duration: Sept 24 2023Sept 27 2023

Publication series

NameProceedings of 2023 IEEE International Smart Cities Conference, ISC2 2023

Conference

Conference9th IEEE International Smart Cities Conference, ISC2 2023
Country/TerritoryRomania
CityBucharest
Period9/24/239/27/23

Keywords

  • 3D models
  • Artificial intelligence
  • Cloud
  • Digital twin
  • Smart city

ASJC Scopus subject areas

  • Computer Science Applications
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Communication
  • Urban Studies

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