Training in virtual reality is becoming increasingly relevant for several target groups. This is especially valid when it comes to simulating a challenging environment that is not or only with drawbacks feasible in a real-life training session, involves too many risks for trainees, or is associated with high setup and/or execution costs. Therefore, a relevant target group for VR training are Law Enforcement Agencies. For the police application domain, VR training offers the possibility to train scenarios in a safe environment, capture, record, and analyze trainee behavior and performance, and measure and visualize physiological signals on trainees state simultaneously. Through this real-time measuring, recording and visualization, it is possible for the trainers to react immediately to the performance (behaviour, physiological condition) of the trainees and to adapt the training. The advantages of this assistance system are usable and quick access to pre-calculated data, and direct options to individualize the scenario to the trainees needs to enhance feedback and learning processes. This work presents how an assistance system can support police trainers in VR training. It also provides Key Performance Indicators of how the assistance system can be applied in the operational police VR training domain.
|Titel||2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE)|
|Publikationsstatus||Veröffentlicht - 2022|
|Veranstaltung||2022 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence, and Neural Engineering (IEEE MetroXRAINE 2022) - |
Dauer: 26 Okt. 2022 → 28 Okt. 2022
|Konferenz||2022 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence, and Neural Engineering (IEEE MetroXRAINE 2022)|
|Zeitraum||26/10/22 → 28/10/22|
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