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ABSTRACT. This paper provides a systematic literature review of studies investigating smart city and dynamic routing technologies, virtual sensor networks, edge computing and geospatial analytics tools, and metaverse decentralized governance systems. The analysis highlights that multi-source remote sensing data fusion, Web3 and immersive holographic imaging technologies, spatial cognition and neural network-based recognition algorithms, and predictive analytics modeling and synthetic data tools can further interoperable extended reality environments. Throughout July 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “extended reality environments” + “urban sensing and immersive 3D technologies,” “computer vision and sensor fusion algorithms,” and “smart city digital twins.” As research published between 2022 and 2023 was inspected, only 166 articles satisfied the eligibility criteria, and 21 mainly empirical sources were selected. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: BIBOT, DistillerSR, METAGEAR package for R, PICO Portal, SluRp, and SWIFT-Active Screener.

Keywords: urban sensing; immersive 3D; computer vision; sensor fusion; smart city; digital twin; extended reality environment

How to cite: Sullivan, R. (2023). “Urban Sensing and Immersive 3D Technologies, Computer Vision and Sensor Fusion Algorithms, and Smart City Digital Twins in Extended Reality Environments,” Geopolitics, History, and International Relations 15(2): 54–68. doi: 10.22381/GHIR15220234.

Received 12 August 2023 • Received in revised form 20 October 2023
Accepted 23 October • Available online 30 October 2023

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