ABSTRACT. This paper provides a systematic literature review of studies investigating movement and behavior tracking tools, ambient sound recognition software, and cognitive artificial intelligence and spatial computing technologies. The analysis highlights that deep learning-based sensing and virtual modeling technologies, movement and behavior tracking tools, and metaverse engagement metrics further photorealistic 3D environments. Throughout April 2023, we performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “interactive digital worlds” + “immersive metaverse and digital twin technologies,” “deep learning-based image processing and motion planning algorithms,” and “3D virtual space networking and data visualization tools.” As we inspected research published in 2022 and 2023, only 184 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, we decided upon 37, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, MMAT, and ROBIS.

Keywords: immersive metaverse; digital twin technologies; deep learning; image processing; motion planning algorithms; 3D virtual space networking; data visualization tools; interactive digital worlds

How to cite: Pera, A., and Rashid, M. (2023). “Immersive Metaverse and Digital Twin Technologies, Deep Learning-based Image Processing and Motion Planning Algorithms, and 3D Virtual Space Networking and Data Visualization Tools in Interactive Digital Worlds,” Review of Contemporary Philosophy 21: 172–189. doi: 10.22381/RCP22202310.

Received 28 May 2023 • Received in revised form 23 August 2023
Accepted 29 August 2023 • Available online 30 August 2023