ABSTRACT. The objective of this paper is to systematically review immersive visualization and cognitive computing systems in a fully connected metaverse. The findings and analyses highlight that blockchain and geospatial mapping technologies, deep learning and predictive maintenance algorithms, and simulation modeling and automated speech recognition tools are instrumental in immersive virtual worlds. Throughout February 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “the virtual economy of the metaverse” + “geospatial big data management and computer vision algorithms,” “remote sensing and image recognition technologies,” and “event modeling and forecasting tools.” As research published between 2022 and 2023 was inspected, only 188 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 35 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Dedoose, Distiller SR, and SRDR.

Keywords: geospatial big data management; computer vision algorithms; remote sensing and image recognition technologies; event modeling and forecasting tools; metaverse

How to cite: Nica, E., and Vahancik, J. (2023). “Geospatial Big Data Management and Computer Vision Algorithms, Remote Sensing and Image Recognition Technologies, and Event Modeling and Forecasting Tools in the Virtual Economy of the Metaverse,” Linguistic and Philosophical Investigations 22: 9–25. doi: 10.22381/lpi2220231.

Received 24 March 2023 • Received in revised form 22 May 2023
Accepted 28 May 2023 • Available online 30 May 2023