ABSTRACT. The purpose of this study is to examine generative artificial intelligence and extensive vision data processing tools, wearable augmented reality devices, and interconnected virtual simulations. Throughout May 2024, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “immersive work environments” + “wearable augmented reality and 3D virtual simulation technologies,” “contextual awareness and spatial data mining tools,” and “generative artificial intelligence and workplace tracking systems.” As research published in 2022 and 2023 was inspected, only 181 articles satisfied the eligibility criteria, and 35 mainly empirical sources were selected. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Colandr, Eppi-Reviewer, JBI SUMARI, Litstream, and MMAT.
JEL codes: E24; J21; J54; J64

Keywords: wearable augmented reality; contextual awareness; spatial data mining; generative artificial intelligence; workplace tracking; immersive work environment

How to cite: Manole, C., Vasic, M., Petrescu, I.-E., and Melenciuc, M. (2024). “Wearable Augmented Reality and 3D Virtual Simulation Technologies, Contextual Awareness and Spatial Data Mining Tools, and Generative Artificial Intelligence and Workplace Tracking Systems in Immersive Work Environments,” Psychosociological Issues in Human Resource Management 12(2): 67–82. doi: 10.22381/pihrm12220244.

Received 25 June 2024 • Received in revised form 22 November 2024
Accepted 26 November 2024 • Available online 29 November 2024