Development of a mobile application for the registration and attendance control of university students based on Machine Learning

Abstract

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."