Research output: Contribution to journal › Article › peer-review
Generative Artificial Intelligence and Movement and Behavior Tracking Tools, Remote Sensing and Cognitive Computing Systems, and Immersive Audiovisual Content in Virtually Simulated Workspace Environments. / Деньгов, Виктор Вениаминович; Zvarikova, Katarina; Balica, Raluca-Ștefania (Author and editor).
In: Analysis and Metaphysics, No. 22, 12.2023, p. 274-293.Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Generative Artificial Intelligence and Movement and Behavior Tracking Tools, Remote Sensing and Cognitive Computing Systems, and Immersive Audiovisual Content in Virtually Simulated Workspace Environments
AU - Деньгов, Виктор Вениаминович
AU - Zvarikova, Katarina
A2 - Balica, Raluca-Ștefania
PY - 2023/12
Y1 - 2023/12
N2 - The purpose of this study is to examine generative artificial intelligence and ambient scene detection tools deploying mobile biometric and sentiment data, realistic movement simulations, and real-time predictive analytics in virtual work environments. In this article, previous research findings were cumulated indicating that generative artificial intelligence and deep learning computer vision algorithms can shape predictive workflows, tailored job upskilling, and meaningful performance management. Throughout August 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “generative artificial intelligence and movement and behavior tracking tools” + “remote sensing and cognitive computing systems,” “immersive audiovisual content,” and “virtually simulated workspace environments.” As research published in 2023 was inspected, only 173 articles satisfied the eligibility criteria, and 50 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, Dedoose, MMAT, and SRDR.
AB - The purpose of this study is to examine generative artificial intelligence and ambient scene detection tools deploying mobile biometric and sentiment data, realistic movement simulations, and real-time predictive analytics in virtual work environments. In this article, previous research findings were cumulated indicating that generative artificial intelligence and deep learning computer vision algorithms can shape predictive workflows, tailored job upskilling, and meaningful performance management. Throughout August 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “generative artificial intelligence and movement and behavior tracking tools” + “remote sensing and cognitive computing systems,” “immersive audiovisual content,” and “virtually simulated workspace environments.” As research published in 2023 was inspected, only 173 articles satisfied the eligibility criteria, and 50 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, Dedoose, MMAT, and SRDR.
KW - generative artificial intelligence; movement and behavior tracking tools; remote sensing; cognitive computing; immersive audiovisual content; virtual; simulation; workspace
UR - https://www.addletonacademicpublishers.com/search-in-am#catid2700
U2 - 10.22381/am22202315
DO - 10.22381/am22202315
M3 - Article
SP - 274
EP - 293
JO - Analysis and Metaphysics
JF - Analysis and Metaphysics
SN - 1584-8574
IS - 22
ER -
ID: 116810819