Emini, Naile and Veljanovski, Konstantin and Rendevski, Nikola (2023) VR as a tool for EVs maintenance training. In: 13th International Conference on Applied Internet and Information Technologies AIIT2023, October 13th, Bitola, Rebublic North Macedonia.
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Abstract
The fast adoption of electric vehicles (EVs) into the automotive scene requires the development of novel maintenance training approaches. Due to its ability to create immersive and interactive learning environments, virtual reality (VR) is a powerful training tool across various domains. Trainees can visually interact with various components of an EV, practice maintenance methods, and replicate real-world scenarios in a risk-free environment by using VR’s capabilities. The main benefits of using VR for EV maintenance training include hands- on practice, the capacity to replicate complicated EV systems, scalability for educating several personnel at the same time, and the possibility of interactive and adaptable learning modules. VR may provide a new sensory experience by merging haptic input and realistic visual and auditory cues, boosting trainees’ spatial knowledge. The research also underlines the potential benefits of VR training, such as increased engagement, cost-effectiveness, scalability, and the ability to standardize training content. This study calls for the use of VR technology as a teaching tool for EV repair, emphasizing its potential to alter the way personnel are trained and skilled in this changing automotive scene. The findings highlight the importance of preparing a skilled workforce capable of meeting the demands of sustainable mobility.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Scientific Fields (Frascati) > Natural sciences > Computer and information sciences Scientific Fields (Frascati) > Engineering and Technology > Electrical engineering, electronic engineering,information engineering |
| Divisions: | Faculty of Information and Communication Technologies |
| Depositing User: | Prof. d-r. Nikola Rendevski |
| Date Deposited: | 11 Dec 2023 17:22 |
| Last Modified: | 11 Dec 2023 17:22 |
| URI: | https://eprints.uklo.edu.mk/id/eprint/9391 |
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