ABSTRACT. The present study systematically reviews the existing research on image generation and object recognition algorithms, spatial computing and holographic interactive technologies, digital twin modeling and simulation tools, and Internet of Things-based connected and 3D imaging sensor devices. Throughout June 2024, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “Internet of Things-enabled smart city governance” + “3D image modeling and deep learning-based ambient sound processing tools,” “multi-sensor data fusion simulation and computer vision algorithms,” and “3D reconstruction and digital twin technologies.” As research published in 2022 and 2023 was inspected, only 174 articles satisfied the eligibility criteria, and 29 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: Abstrackr, CADIMA, DistillerSR, METAGEAR package for R, Rayyan, and SluRp.

Keywords: 3D image modeling; ambient sound processing; multi-sensor data fusion; computer vision; digital twin; smart city

How to cite: Ciurlău, C. F., Pantovic, D. (D.), Ćurčić, N., Nistoroiu, B.-N., and Radulica, M. I. (2024). “3D Image Modeling and Deep Learning-based Ambient Sound Processing Tools, Multi-Sensor Data Fusion Simulation and Computer Vision Algorithms, and 3D Reconstruction and Digital Twin Technologies in Internet of Things-enabled Smart City Governance,” Geopolitics, History, and International Relations 16(1): 67–82. doi: 10.22381/GHIR16120244.

Received 9 July 2024 • Received in revised form 25 October 2024
Accepted 27 October 2024 • Available online 30 October 2024