ABSTRACT. This article reviews and advances existing literature concerning real-time predictive and mobile location analytics, convolutional neural and generative adversarial networks, and geospatial mapping and simulation modeling tools furthering extended reality environments. In this research, previous findings were cumulated showing that 3D imaging and display technologies, modeling and forecasting tools, and intelligent sensing networks optimize blockchain-based virtual worlds. Throughout April 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “immersive 3D worlds” + “visual perceptive and blockchain-based decentralized metaverse systems,” “ambient intelligence and digital twin simulation tools,” and “deep learning and virtual mapping algorithms.” As research published in 2022 was inspected, only 143 articles satisfied the eligibility criteria, and 29 sources were selected. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, MMAT, ROBIS, and SRDR.

Keywords: visual; perception; blockchain; metaverse; ambient intelligence; digital twin; simulation; deep learning; virtual mapping; immersive; 3D

How to cite: Kovacova, M., Krulicky, T., and Woodward, B. (2022). “Visual Perceptive and Blockchain-based Decentralized Metaverse Systems, Ambient Intelligence and Digital Twin Simulation Tools, and Deep Learning and Virtual Mapping Algorithms in Immersive 3D Worlds,” Smart Governance 1(2): 7–22. doi: 10.22381/sg1220221.

Received 28 May 2022 • Received in revised form 25 June 2022
Accepted 29 June 2022 • Available online 30 June 2022