Sistema de Detección de Control de Estudiantes  Universitarios Basado en Machine Learning e Inteligencia Artificial

Joseph Lopez-Carreño; Cristhian Calvo-Lavado; Eliseo Zarate-Perez

doi:10.18687/LEIRD2022.1.1.178

Sistema de Detección de Control de Estudiantes Universitarios Basado en Machine Learning e Inteligencia Artificial

Translated title of the contribution: University Student Control Detection System Based on Machine Learning and Artificial Intelligence

Joseph Lopez-Carreño
, Cristhian Calvo-Lavado
, Eliseo Zarate-Perez

Universidad Privada del Norte

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

The objective of this study was to program a school assistant based on artificial intelligence and integrated with surveillance cameras and loudspeakers in a university classroom. This was done to complement the supervision carried out by university teachers to identify student distractions, guarantee the proper use of masks, and evaluate student behaviors in class. The virtual assistant was developed using Python to generate audio warnings through a graphical interface built in the PyCharm environment. The results demonstrated the desired functionality of the virtual assistant, its ability to meet the requirements of a university classroom, and thereby the effectiveness of the YOLO v5 network and PyCharm used for the training, execution, construction, and implementation of the system.

Translated title of the contribution	University Student Control Detection System Based on Machine Learning and Artificial Intelligence
Original language	Spanish
Title of host publication	Proceedings of the 2nd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development
Subtitle of host publication	Exponential Technologies and Global Challenges: Moving Toward a New Culture of Entrepreneurship and Innovation for Sustainable Development, LEIRD 2022
Editors	Maria M. Larrondo Petrie, Jose Texier, Rodolfo Andres Rivas Matta
ISBN (Electronic)	9786289520736
DOIs	https://doi.org/10.18687/LEIRD2022.1.1.178
State	Published - 2022
Event	2nd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development, LEIRD 2022 - Virtual, Online, Colombia Duration: 6 Dec 2022 → 7 Dec 2022

Publication series

Name	Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volume	2022-December
ISSN (Electronic)	2414-6390

Conference

Conference	2nd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development, LEIRD 2022
Country/Territory	Colombia
City	Virtual, Online
Period	6/12/22 → 7/12/22

Access to Document

10.18687/LEIRD2022.1.1.178

Cite this

Lopez-Carreño, J., Calvo-Lavado, C., & Zarate-Perez, E. (2022). Sistema de Detección de Control de Estudiantes Universitarios Basado en Machine Learning e Inteligencia Artificial. In M. M. Larrondo Petrie, J. Texier, & R. A. R. Matta (Eds.), Proceedings of the 2nd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development: Exponential Technologies and Global Challenges: Moving Toward a New Culture of Entrepreneurship and Innovation for Sustainable Development, LEIRD 2022 (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology; Vol. 2022-December). https://doi.org/10.18687/LEIRD2022.1.1.178

Lopez-Carreño, Joseph ; Calvo-Lavado, Cristhian ; Zarate-Perez, Eliseo. / Sistema de Detección de Control de Estudiantes Universitarios Basado en Machine Learning e Inteligencia Artificial. Proceedings of the 2nd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development: Exponential Technologies and Global Challenges: Moving Toward a New Culture of Entrepreneurship and Innovation for Sustainable Development, LEIRD 2022. editor / Maria M. Larrondo Petrie ; Jose Texier ; Rodolfo Andres Rivas Matta. 2022. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology).

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title = "Sistema de Detecci{\'o}n de Control de Estudiantes Universitarios Basado en Machine Learning e Inteligencia Artificial",

abstract = "The objective of this study was to program a school assistant based on artificial intelligence and integrated with surveillance cameras and loudspeakers in a university classroom. This was done to complement the supervision carried out by university teachers to identify student distractions, guarantee the proper use of masks, and evaluate student behaviors in class. The virtual assistant was developed using Python to generate audio warnings through a graphical interface built in the PyCharm environment. The results demonstrated the desired functionality of the virtual assistant, its ability to meet the requirements of a university classroom, and thereby the effectiveness of the YOLO v5 network and PyCharm used for the training, execution, construction, and implementation of the system.",

keywords = "Artificial intelligence, School assistant, Student monitoring, Teaching assistant, University education",

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note = "Publisher Copyright: {\textcopyright} 2022 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.; 2nd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development, LEIRD 2022 ; Conference date: 06-12-2022 Through 07-12-2022",

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doi = "10.18687/LEIRD2022.1.1.178",

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series = "Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology",

editor = "\{Larrondo Petrie\}, \{Maria M.\} and Jose Texier and Matta, \{Rodolfo Andres Rivas\}",

booktitle = "Proceedings of the 2nd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development",

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Lopez-Carreño, J, Calvo-Lavado, C & Zarate-Perez, E 2022, Sistema de Detección de Control de Estudiantes Universitarios Basado en Machine Learning e Inteligencia Artificial. in MM Larrondo Petrie, J Texier & RAR Matta (eds), Proceedings of the 2nd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development: Exponential Technologies and Global Challenges: Moving Toward a New Culture of Entrepreneurship and Innovation for Sustainable Development, LEIRD 2022. Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology, vol. 2022-December, 2nd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development, LEIRD 2022, Virtual, Online, Colombia, 6/12/22. https://doi.org/10.18687/LEIRD2022.1.1.178

Sistema de Detección de Control de Estudiantes Universitarios Basado en Machine Learning e Inteligencia Artificial. / Lopez-Carreño, Joseph; Calvo-Lavado, Cristhian; Zarate-Perez, Eliseo.
Proceedings of the 2nd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development: Exponential Technologies and Global Challenges: Moving Toward a New Culture of Entrepreneurship and Innovation for Sustainable Development, LEIRD 2022. ed. / Maria M. Larrondo Petrie; Jose Texier; Rodolfo Andres Rivas Matta. 2022. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology; Vol. 2022-December).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Sistema de Detección de Control de Estudiantes Universitarios Basado en Machine Learning e Inteligencia Artificial

AU - Lopez-Carreño, Joseph

AU - Calvo-Lavado, Cristhian

AU - Zarate-Perez, Eliseo

PY - 2022

Y1 - 2022

N2 - The objective of this study was to program a school assistant based on artificial intelligence and integrated with surveillance cameras and loudspeakers in a university classroom. This was done to complement the supervision carried out by university teachers to identify student distractions, guarantee the proper use of masks, and evaluate student behaviors in class. The virtual assistant was developed using Python to generate audio warnings through a graphical interface built in the PyCharm environment. The results demonstrated the desired functionality of the virtual assistant, its ability to meet the requirements of a university classroom, and thereby the effectiveness of the YOLO v5 network and PyCharm used for the training, execution, construction, and implementation of the system.

AB - The objective of this study was to program a school assistant based on artificial intelligence and integrated with surveillance cameras and loudspeakers in a university classroom. This was done to complement the supervision carried out by university teachers to identify student distractions, guarantee the proper use of masks, and evaluate student behaviors in class. The virtual assistant was developed using Python to generate audio warnings through a graphical interface built in the PyCharm environment. The results demonstrated the desired functionality of the virtual assistant, its ability to meet the requirements of a university classroom, and thereby the effectiveness of the YOLO v5 network and PyCharm used for the training, execution, construction, and implementation of the system.

KW - Artificial intelligence

KW - School assistant

KW - Student monitoring

KW - Teaching assistant

KW - University education

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M3 - Contribución a la conferencia

AN - SCOPUS:85150700942

T3 - Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology

BT - Proceedings of the 2nd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development

A2 - Larrondo Petrie, Maria M.

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ER -

Lopez-Carreño J, Calvo-Lavado C, Zarate-Perez E. Sistema de Detección de Control de Estudiantes Universitarios Basado en Machine Learning e Inteligencia Artificial. In Larrondo Petrie MM, Texier J, Matta RAR, editors, Proceedings of the 2nd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development: Exponential Technologies and Global Challenges: Moving Toward a New Culture of Entrepreneurship and Innovation for Sustainable Development, LEIRD 2022. 2022. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology). doi: 10.18687/LEIRD2022.1.1.178