Abstract
The Virtual Electrician Training (VET) system, designed to provide effective and innovative technical training in a virtual reality (VR) environment, allows trainees to practice operational tasks safely and realistically on an electrical grid. By integrating advanced VR technology with flexible tools for managing training content, the VET system offers immersive and interactive simulations that enhance skill acquisition and operational proficiency. Trainees engage with detailed 3D models and scenarios of electrical infrastructure, including transformers and switchgear, enabling them to perform complex procedures such as circuit switching and live-line work in a controlled and risk-free setting. The system employs a semantic database managed by Apache Fuseki, which seamlessly links 3D models, scenes, and training scenarios, facilitating efficient content creation, modification, and updates. Key components include a central server, stationary and mobile training stations equipped with VR headsets and controllers, and auxiliary equipment like motion sensors and communication devices. The VET system’s architecture supports easy scalability and adaptability, ensuring that training programs remain current with industry standards and evolving operational requirements. This comprehensive training tool significantly improves safety, reduces training costs, and enhances the overall quality and efficiency of technical training in the dynamic energy sector.
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Acknowledgments
The presented research was co-funded by ENEA Operator Sp. z o.o. and the National Center for Research and Development under grant number LIDER/55/0287/L- 12/20/NCBR/2021.
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Gałązkiewicz, A. (2024). Managing Training Scenarios in a Distributed Virtual Electrician Training System. In: De Paolis, L.T., Arpaia, P., Sacco, M. (eds) Extended Reality. XR Salento 2024. Lecture Notes in Computer Science, vol 15029. Springer, Cham. https://doi.org/10.1007/978-3-031-71710-9_12
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