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  • Please use this identifier to cite or link to this item: https://repositorio.uti.edu.ec//handle/123456789/5431
    Title: Real-Time Monitoring Tool for SNN Hardware Architecture
    Authors: Zapata, Mireya
    Vargas, Vanessa
    Cagua, Ariel
    Álvarez, Daniela
    Vallejo, Bernando
    Madrenas, Jordi
    Issue Date: 2023
    Publisher: Lecture Notes in Networks and Systems. Volume 678 LNNS, Pages 478 - 493. International Conference on Computer Science, Electronics, and Industrial Engineering, CSEI 2022
    Abstract: 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
    Appears in Collections:Artículos Científicos Indexados

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