ABSTRACT. The present study systematically reviews the existing research on 3D immersive virtual reality and spatial computing technologies, real-time data tracking and machine learning-based image recognition tools, and virtual mapping and computer vision algorithms configuring the blockchain-based virtual economy. The findings indicate that visual immersion and remote sensing technologies, computational intelligence and data modeling tools, and user behavior data mining enable blockchain-based metaverse platforms. The contribution to the literature is by clarifying that interconnected digital realms require 3D modeling and socio-spatial analytics tools, hyper-realistic immersive 3D simulations, and virtual personas and identities. Throughout April 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “the decentralized metaverse” + “3D immersive virtual reality and spatial computing technologies,” “real-time data tracking and machine learning-based image recognition tools,” and “brain-inspired artificial intelligence and data stream clustering algorithms.” As research published in 2022 was inspected, only 151 articles satisfied the eligibility criteria, and 28 sources were selected. 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: 3D; immersive; virtual reality; spatial computing; real-time data tracking; machine learning; image recognition; brain-inspired; artificial intelligence; data stream clustering; metaverse

How to cite: Goodman, C. (2022). “3D Immersive Virtual Reality and Spatial Computing Technologies, Real-Time Data Tracking and Machine Learning-based Image Recognition Tools, and Brain-inspired Artificial Intelligence and Data Stream Clustering Algorithms in the Decentralized Metaverse,” Smart Governance 1(3): 39–54. doi: 10.22381/sg1320223.

Received 20 May 2022 • Received in revised form 22 September 2022
Accepted 26 September 2022 • Available online 30 September 2022