Detección de eventos de contaminación acústica : almacenamiento, procesamiento de eventos acústicos.

Abstract

This study presents the process carried out to classify quantitative data with a continuous level of measurement such as noise, temperature, and humidity, which are located in a digital repository (Opendatasoft), for this purpose information technologies are used and machine learning algorithms. The first chapter of the Curriculum Integration Work presents the theoretical foundation that will be useful for the development of the component, so that information is focused on: describing the parameters that will be used in the classification, investigating international standards of reference to the parameters, describe the machine learning models that are going to be implemented, make a description of the database, present the programming language that is going to be used to generate the code and finally the method to process data. In the second chapter, the process carried out for data classification will be fully discussed, which is why it has been divided into stages according to what is presented in the theoretical foundation. Finally, the last chapter deals with the performance tests, conclusions and recommendations that were reached once the entire component was completed.