ABSTRACT. This paper provides a systematic literature review of studies investigating how data-driven planning technologies, Internet of Things sensing infrastructures, and urban intelligence shape digital twin cities. The analysis highlights that digital twin cities require data visualization tools, virtual modeling technology, and Internet of Things-based decision support systems. Throughout March 2022, we performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “immersive 3D environments” + “digital twin simulation and modeling tools,” “computer vision algorithms,” and “urban sensing technologies.” As we inspected research published in 2022, only 186 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, we decided upon 34, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, MMAT, and ROBIS.

Keywords: digital twin; urban; computer vision; simulation; modeling; sensor

How to cite: Kliestik, T., Poliak, M., and Popescu, G. H. (2022). “Digital Twin Simulation and Modeling Tools, Computer Vision Algorithms, and Urban Sensing Technologies in Immersive 3D Environments,” Geopolitics, History, and International Relations 14(1): 9–25. doi: 10.22381/GHIR14120221.

Received 23 March 2022 • Received in revised form 26 June 2022
Accepted 28 June 2022 • Available online 30 June 2022