ABSTRACT. In this article, I cumulate previous research findings indicating that virtual sensor modeling and simulation systems, realistic 3D digital twins, and industrial data semantics assist immersive hyper-connected virtual spaces. I contribute to the literature on deep reinforcement learning and simulated augmented reality technologies, digital twin data modeling and visualization, and 6G-enabled edge artificial intelligence by showing that intelligent simulation environments necessitate cognitive and behavioral algorithms, 3D capture and virtual twin technologies, and operational modeling and intelligent data processing tools. Throughout January 2023, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “the industrial metaverse” + “cognitive artificial intelligence and remote sensing algorithms,” “virtual immersive and spatial computing technologies,” and “3D image modeling and digital twin simulation tools.” As I inspected research published between 2022 and 2023, only 140 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 25, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, ROBIS, and SRDR.
JEL codes: D53; E22; E32; E44; G01; G41

Keywords: cognitive artificial intelligence; remote sensing algorithms; virtual immersive and spatial computing technologies; 3D image modeling; digital twin simulation tools; industrial metaverse

How to cite: Stevens, A. (2023). “Cognitive Artificial Intelligence and Remote Sensing Algorithms, Virtual Immersive and Spatial Computing Technologies, and 3D Image Modeling and Digital Twin Simulation Tools in the Industrial Metaverse,” Economics, Management, and Financial Markets 18(1): 73–88. doi: 10.22381/emfm18120235.

Received 20 January 2023 • Received in revised form 22 March 2023
Accepted 26 March 2023 • Available online 30 March 2023