Generation of linguistic descriptions for daily noise pollution in urban areas

Abstract

One of the major problems of concern to the nowadays society is pollution, which can be of many types: acoustic, environmental, thermal, etc. Among these, noise pollution causes serious problems for citizens because it is continuous for a large part of the day, due to the fact that it is mostly caused by traffic. On the other hand, large cities provide a large amount of data obtained daily thanks to the sensorisation resulting from the concept of “smart cities”, which makes it possible to display information from the sensorised areas and to alert the institutions of the problems and, for citizens, to know the situation of noise pollution based on data in order to be able to make the relevant complaints and denunciations to the institutions. A universally understandable way of displaying the information contained in the captured data is the generation of linguistic descriptions that synthesise the information residing in the data. This paper presents a method for generating linguistic descriptions based on the noise pollution data captured by noise measurement stations. A method for generating descriptions of a day will be presented that considers the daily periods in which the data taken from the stations are structured (daytime, evening, night-time and full day). In order to test the proposed method, available data from the city of Madrid have been used to generate descriptions that allow the influence of Covid-19 on noise pollution to be analysed.