TY - GEN
T1 - Desarrollo de una aplicación móvil para la registro y control de asistencia de la universidad estudiantes basados en Machine Learning
AU - Silva, Nicolás Caytuiro
AU - Samayani, Denilson Ala
AU - Alejandro, Jackeline Peña
AU - Carnero, Manuel Zúñiga
AU - Sulla-Torres, José
N1 - Publisher Copyright:
© 2022 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.
PY - 2022
Y1 - 2022
N2 - This research aims to develop an Android mobile application that allows registration and control of attendance in educational institutions based on Machine Learning and Cloud Computing technology. For this, the project management methodology XP (EXtreme Programming) is used, in whose phases the entire process of implementation of the application and the launch are detailed; likewise, Firebase is used as a service for database management. The application tests were carried out on the students of the seventh semester of the Professional School of Systems Engineering of the University of Peru. The attendance control system was connected to a database that stores student information and attendance records. To implement the QR code attendance record functionality, the Firebase Machine Learning kit was used to Validate the student attendance record. In addition, the user interface displays the attendance records from an attractive, intuitive approach that is easy for teachers and students to manage. The results of the research show that the use of the application by teachers and students reduces and optimize the time invested in the attendance registration process compared to traditional methods, according to the satisfaction and acceptance criteria of the mobile application called “ASYS.”
AB - This research aims to develop an Android mobile application that allows registration and control of attendance in educational institutions based on Machine Learning and Cloud Computing technology. For this, the project management methodology XP (EXtreme Programming) is used, in whose phases the entire process of implementation of the application and the launch are detailed; likewise, Firebase is used as a service for database management. The application tests were carried out on the students of the seventh semester of the Professional School of Systems Engineering of the University of Peru. The attendance control system was connected to a database that stores student information and attendance records. To implement the QR code attendance record functionality, the Firebase Machine Learning kit was used to Validate the student attendance record. In addition, the user interface displays the attendance records from an attractive, intuitive approach that is easy for teachers and students to manage. The results of the research show that the use of the application by teachers and students reduces and optimize the time invested in the attendance registration process compared to traditional methods, according to the satisfaction and acceptance criteria of the mobile application called “ASYS.”
KW - Android
KW - Assistance system
KW - Machine Learning
KW - Mobile application
KW - XP Methodology
UR - http://www.scopus.com/inward/record.url?scp=85150745696&partnerID=8YFLogxK
U2 - 10.18687/LEIRD2022.1.1.8
DO - 10.18687/LEIRD2022.1.1.8
M3 - Contribución a la conferencia
AN - SCOPUS:85150745696
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.
A2 - Texier, Jose
A2 - Matta, Rodolfo Andres Rivas
PB - Latin American and Caribbean Consortium of Engineering Institutions
T2 - 2nd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development, LEIRD 2022
Y2 - 6 December 2022 through 7 December 2022
ER -