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Digital Twin Modeling, Multi-Sensor Fusion Technology, and Data Mining Algorithms in Cloud and Edge Computing-based Smart City Environments

Digital Twin Modeling, Multi-Sensor Fusion Technology, and Data Mining Algorithms in Cloud and... This article reviews and advances existing literature concerning digital twin modeling, multi-sensor fusion technology, and data mining algorithms in cloud and edge computing-based smart city environments. In this research, previous findings were cumulated showing that virtual and augmented reality technologies, machine learning techniques, and data visualization tools are pivotal for urban processes and systems, and we contribute to the literature by indicating that smart city sensing technologies, computer vision algorithms, and mobile social networks articulate immersive virtual worlds. Throughout April 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “cloud and edge computing-based smart city environments” + “digital twin modeling,” “multi-sensor fusion technology,” and “data mining algorithms.” As research published in 2022 was inspected, only 177 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/ irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 32 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, MMAT, ROBIS, and SRDR. Keywords: digital twin modeling; smart city; sensor data; cloud and edge computing http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Geopolitics, History, and International Relations Addleton Academic Publishers

Digital Twin Modeling, Multi-Sensor Fusion Technology, and Data Mining Algorithms in Cloud and Edge Computing-based Smart City Environments

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Publisher
Addleton Academic Publishers
Copyright
© 2009 Addleton Academic Publishers
ISSN
1948-9145
eISSN
2374-4383
Publisher site
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Abstract

This article reviews and advances existing literature concerning digital twin modeling, multi-sensor fusion technology, and data mining algorithms in cloud and edge computing-based smart city environments. In this research, previous findings were cumulated showing that virtual and augmented reality technologies, machine learning techniques, and data visualization tools are pivotal for urban processes and systems, and we contribute to the literature by indicating that smart city sensing technologies, computer vision algorithms, and mobile social networks articulate immersive virtual worlds. Throughout April 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “cloud and edge computing-based smart city environments” + “digital twin modeling,” “multi-sensor fusion technology,” and “data mining algorithms.” As research published in 2022 was inspected, only 177 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/ irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 32 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, MMAT, ROBIS, and SRDR. Keywords: digital twin modeling; smart city; sensor data; cloud and edge computing

Journal

Geopolitics, History, and International Relations – Addleton Academic Publishers

Published: Jan 1, 2022

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