Por favor, use este identificador para citar o enlazar este ítem: https://repositorio.uti.edu.ec//handle/123456789/5431
Título : Real-Time Monitoring Tool for SNN Hardware Architecture
Autor : Zapata, Mireya
Vargas, Vanessa
Cagua, Ariel
Álvarez, Daniela
Vallejo, Bernando
Madrenas, Jordi
Fecha de publicación : 2023
Editorial : Lecture Notes in Networks and Systems. Volume 678 LNNS, Pages 478 - 493. International Conference on Computer Science, Electronics, and Industrial Engineering, CSEI 2022
Resumen : One of the main objectives of virtual reality (VR) is to simplify human resource interactions with equipment once a process is in operation, especially in the case of techniques that are related and whose devices communicate with each other. VR allows operators to become familiar with the production environment and the process in a tangible way during training, making them aware of the context where they will be working, both the physical space and the contingencies that may arise. This paper presents an immersive training module for detecting and correcting faults in induction motors. Two groups were considered for testing the effectiveness of the developed system: a control group and an experimental group. The tests showed that with this technology, the teaching-learning process time is optimized by more than 50%. In addition, with a p-value lower than the selected alpha level, it was confirmed that the use of VR, in this case, is more efficient than the use of conventional training methodologies. Finally, the usability of the proposal was evaluated, concluding that, although the system has several areas for improvement, it is beneficial for the industry
URI : https://link.springer.com/chapter/10.1007/978-3-031-31183-3_24
https://repositorio.uti.edu.ec//handle/123456789/5431
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