ABSTRACT. The objective of this paper is to systematically review geospatial mapping and 3D virtual space networking tools, visual object tracking and deep learning algorithms, and cloud computing and cognitive artificial intelligence technologies. The findings and analyses highlight that extended reality environments require sensor fusion and 3D path planning algorithms, synthetic biometric data, and ontology-based semantic and 3D immersive virtual reality technologies. Throughout April 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “the blockchain-based metaverse” + “context awareness and deep learning algorithms,” “immersive visualization and autonomous cognitive systems,” and “natural language processing and digital twin modeling tools.” As research published in 2022 and 2023 was in- spected, only 181 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, I selected 30 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: context awareness; deep learning algorithms; immersive visualization; autonomous cognitive systems; natural language processing; digital twin modeling tools; blockchain-based metaverse

How to cite: Barker, M. (2023). “Context Awareness and Deep Learning Algorithms, Immersive Visualization and Autonomous Cognitive Systems, and Natural Language Processing and Digital Twin Modeling Tools in the Blockchain-based Metaverse,” Review of Contemporary Philosophy 21: 102–118. doi: 10.22381/RCP2220236.

Received 20 May 2023 • Received in revised form 23 August 2023
Accepted 26 August 2023 • Available online 30 August 2023

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