Arquitectura para sistemas IoT: estudio de las alternativas que permitan mejorar el rendimiento académico de estudiantes universitarios, a través del monitoreo del ambiente de estudio, utilizando aplicaciones IoT.

Abstract

There are several factors in the study environment that affect the academic performance of young university students, among these factors are noise and lighting. Therefore, it’s important to analyze alternatives to work on these two variables to improve student performance. In this context, an investigation of a case study is carried out that has as main goal noise and lighting parameters. With this, information such as machine learning algorithms used is extracted, together with the performance metrics to evaluate, sensors and tools used in the research, as well as the factors considered to establish an adequate environment in terms of noise and lighting. Subsequently, an alternative mobile application to apply in the future is proposed that makes use of students’ smartphones as an IoT device, to capture illumination and noise levels and thereby, determine the comfort level perceived by the student. This study is divided into three chapters. The first one details the factors that influence academic performance, indicators to measure it, basic concepts of noise, lighting, IoT systems, smartphones’ sensors, and algorithms of machine learning. In the second chapter, there is a review of some articles focused on the analyses of illumination and noise, moreover, it proposes a mobile application to monitor the environment of study. The third chapter makes a comparison of the articles at the level of machine learning logarithms, evaluation metrics and factors that determine the comfort level of the study environment, so finally present the conclusions and recommendations obtained.