ABSTRACT. Based on an in-depth survey of the literature, the purpose of the paper is to explore geospatial big data analytics, asset maintenance simulations, smart city digital twins, and artificial intelligence-driven computer vision and environment map- ping algorithms. Throughout July 2024, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “collaborative digital twin-based extended reality environments” + “smart city and virtual simulation algorithms,” “Artificial Intelligence of Things-based and location-aware networked systems,” and “real-time object detection and operational modeling tools.” As research published in 2022 and 2023 was inspected, only 152 articles satisfied the eligibility criteria, and 20 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: JBI SUMARI, Litstream, Rayyan, ROBIS, SRDR+, and Systematic Review Accelerator.

Keywords: smart city; virtual simulation; Artificial Intelligence of Things; real-time object detection; collaborative digital twin; extended reality

How to cite: Pârvu, I. A., Emek, M. L., Adilbekova, K., Dumitrescu, C-O., and Satnoianu, B. M. (2024). “Smart City and Virtual Simulation Algorithms, Artificial Intelligence of Things-based and Location-Aware Networked Systems, and Real-Time Object Detection and Operational Modeling Tools in Collaborative Digital Twin-based Extended Reality Environments,” Geopolitics, History, and International Relations 16(2): 82–96. doi: 10.22381/GHIR16220244.

Received 11 August 2024 • Received in revised form 19 December 2024
Accepted 25 December 2024 • Available online 30 December 2024