An Innovative Approach to Automatically Help Activities Corrections in Remote Laboratories in the Mechatronics Area Using Intelligent Digital Twins

This Innovative Practice research paper describes an intelligent digital twin platform designed to enhance the virtualization of practical activities in the field of mechatronics education. In recent years, the classic concept of digital twins has significantly evolved in academia and industry. In education, especially in engineering, digital twins have brought countless alternatives for building environments close to the reality of students' practical activities. To improve these activities in the mechatronics area, intelligent digital twins will add added resources and technologies that assist the virtualization process. Therefore, a platform was developed to access remote laboratories in the mechatronics area and help correct the experiments offered. This platform will enable teachers to insert practical activities into remote laboratories on the platform. This platform has three central areas: teaching plans, teachers, and students. In teaching plants, it is possible to create a register of plants that provides information on the characteristics necessary to connect with their equipment and the number of plant elements. In the teachers' area, it is essential to create an activity for students to conduct, and this activity must be conducted for the system to capture the data and images to form a correction model. The correction model uses these data to help intelligent digital twins digitize practical activities. In the student area, it is possible to check all available experiments and their virtualizations and automatically correct the practical experiment.

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Publication Details

Published
2024-10-13
DOI
https://doi.org/10.1109/fie61694.2024.10893093
Primary Topic
Experimental Learning in Engineering
Type
article
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article

An Innovative Approach to Automatically Help Activities Corrections in Remote Laboratories in the Mechatronics Area Using Intelligent Digital Twins

Wollace de Souza Picanço, Vicente Ferreira de Lucena, Guido Soprano Machado, C. Silva et al.
Experimental Learning in Engineering
article

An Innovative Approach to Automatically Help Activities Corrections in Remote Laboratories in the Mechatronics Area Using Intelligent Digital Twins

Wollace de Souza Picanço, Vicente Ferreira de Lucena, Guido Soprano Machado, C. Silva, Renan Landau Paiva de Medeiros, Marenice Melo de Carvalho
article en

Abstract

This Innovative Practice research paper describes an intelligent digital twin platform designed to enhance the virtualization of practical activities in the field of mechatronics education. In recent years, the classic concept of digital twins has significantly evolved in academia and industry. In education, especially in engineering, digital twins have brought countless alternatives for building environments close to the reality of students' practical activities. To improve these activities in the mechatronics area, intelligent digital twins will add added resources and technologies that assist the virtualization process. Therefore, a platform was developed to access remote laboratories in the mechatronics area and help correct the experiments offered. This platform will enable teachers to insert practical activities into remote laboratories on the platform. This platform has three central areas: teaching plans, teachers, and students. In teaching plants, it is possible to create a register of plants that provides information on the characteristics necessary to connect with their equipment and the number of plant elements. In the teachers' area, it is essential to create an activity for students to conduct, and this activity must be conducted for the system to capture the data and images to form a correction model. The correction model uses these data to help intelligent digital twins digitize practical activities. In the student area, it is possible to check all available experiments and their virtualizations and automatically correct the practical experiment.

Universidade Federal do Amazonas (BR)
Openalex Percentile: Top 60%
Experimental Learning in Engineering
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