ABSTRACT. Despite the relevance of synthetic biometric data, human digital twin and haptic object recognition systems, and real-time 3D rendering and visual immersion technologies, only limited research has been conducted on this topic. In this article, I cumulate previous research findings indicating that interactional and contextual data, digital twin and tactile sensing technologies, and behavioral predictive and geospatial big data analytics configure the decentralized and interconnected metaverse. Throughout May 2023, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “the decentralized and interconnected metaverse” + “brain-inspired artificial intelligence and machine learning-based navigation algorithms,” “spatial data visualization and digital twin modeling tools,” and “emotion detection and recognition technologies.” As I inspected research published between 2022 and 2023, only 179 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 30, 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, Distiller SR, and MMAT.

Keywords: brain-inspired artificial intelligence; machine learning; navigation algorithms; spatial data visualization; digital twin modeling tools; emotion detection and recognition technologies; decentralized and interconnected metaverse

How to cite: Bratu, S. (2023). “Brain-inspired Artificial Intelligence and Machine Learning-based Navigation Algorithms, Spatial Data Visualization and Digital Twin Modeling Tools, and Emotion Detection and Recognition Technologies in the Decentralized and Interconnected Metaverse,” Review of Contemporary Philosophy 21: 51–67. doi: 10.22381/RCP2220233.

Received 26 June 2023 • Received in revised form 24 August 2023
Accepted 28 August 2023 • Available online 30 August 2023

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