Towards Artificial Intelligence Driven Immersive Environments in Virtual Reality for Industrial Applications

Alsaleh, Saleh; Tepljakov, Aleksei; Tamre, Mart; Petlenkov, Eduard

doi:10.1109/tsp52935.2021.9522676

Cited by 4 publications

(3 citation statements)

References 14 publications

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“…Thus, all critical mechanical components and the frame have been faithfully recreated, while the wires, DC motors, encoders, pulleys and belts were ignored. It was confirmed through initial experiments that as long as the recreated components had the correct scale and behaved exactly as expected, the 3D model would be convincing enough for immersion to occur [58]. In the future, the other components can be recreated as well, but the additional complexity may not necessarily benefit the present digital twin.…”

Section: A 3d Model Of the Overhead Cranementioning

confidence: 71%

“…• An interaction is designed for the supporting components of the XR experience (such as using the information panels). Mathematical models of these interactions are, at first glance, not needed; however, if one considers the concept of intelligent immersive virtual environments (IIVEs), useful intelligent mechanics can be employed as well [58].…”

Section: ) Interaction Designmentioning

confidence: 99%

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ReImagine Lab: Bridging the Gap Between Hands-On, Virtual and Remote Control Engineering Laboratories Using Digital Twins and Extended Reality

et al. 2022

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Practical work is one of the most important instructional tools in control engineering. To address concerns linked to the cost and space requirements of traditional hands-on laboratories, technology-enabled laboratory modes, such as virtual, remote, and take-home laboratory modes are proposed. Each of these alliterative laboratory modes has its own set of benefits and emphasizes a distinct learning goal. Furthermore, due to lockdown and physical proximity restrictions imposed by policies in response to the COVID-19 pandemic, the employment of these alliterative laboratory modes has been quickly increasing. The laboratories' development, operation, and maintenance become more fragmented as a result of these many possibilities. In this study, we propose "ReImagine Lab" as a framework for leveraging digital twins and extended reality technologies to streamline the development and operation of hands-on, virtual, and distant laboratories. By increasing the level of interaction, immersion, and collaboration in technologyenabled laboratory forms, this framework intends to boost student engagement. The benefits of this framework are demonstrated by examining several use cases, and a 37-person "system usability study" is conducted to assess the usability of virtual laboratories employing desktop computers and immersive virtual reality.

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Section: A 3d Model Of the Overhead Cranementioning

confidence: 71%

Section: ) Interaction Designmentioning

confidence: 99%

ReImagine Lab: Bridging the Gap Between Hands-On, Virtual and Remote Control Engineering Laboratories Using Digital Twins and Extended Reality

et al. 2022

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“…For effective ML model training, large-scale datasets that include a range of emotional states and virtual scenarios must be gathered and labeled. Additionally, by combining different sources of emotional cues, such as voice, physiological signals, and facial expressions, multimodal data fusion can improve the precision and resilience of emotion identification systems [9]. The integration of ML with VR presents intriguing possibilities for improving emotion recognition in virtual settings.…”

Section: Introductionmentioning

confidence: 99%

Enhancing the Potential of Machine Learning for Immersive Emotion Recognition in Virtual Environment

2024

ICST Transactions on Scalable Information Systems

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Emotion recognition is an immense challenge for immersive technology. In order to detect the emotions of the user, we use machine learning methods and techniques to use the potential of the Virtual Environment and to improve the user Experience. Emotion recognition plays an important role in developing realistic and emotionally immersive experiences in augmented reality (AR) and virtual reality (VR) settings by instantly adjusting interactions, content, and visuals based on the accurate detection and interpretation of users’ emotions. Immersive systems can enhance user experience through various machine learning algorithms and methods used for emotion recognition, which are examined in this article. Upon novel idea, challenges and potential applications of incorporating emotion recognition in immersive virtual environments with Machine Learning (ML) Techniques and the benefits of tailoring powerful immersive experiences with ML methods were highlighted, and also the study discusses potential advancements in identifying the user’s emotion recognition in the future by modeling an Architecture, as well as how the ML techniques were enhanced for virtual environment is discussed.

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Artificial Intelligence-Driven Industry Applications

Moro-Visconti

2024

Artificial Intelligence Valuation

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Towards Artificial Intelligence Driven Immersive Environments in Virtual Reality for Industrial Applications

Cited by 4 publications

References 14 publications

ReImagine Lab: Bridging the Gap Between Hands-On, Virtual and Remote Control Engineering Laboratories Using Digital Twins and Extended Reality

ReImagine Lab: Bridging the Gap Between Hands-On, Virtual and Remote Control Engineering Laboratories Using Digital Twins and Extended Reality

Enhancing the Potential of Machine Learning for Immersive Emotion Recognition in Virtual Environment

Artificial Intelligence-Driven Industry Applications

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