menu
Information about the author
Contributions
  • A survey-based methodology has been described as one that allows for evaluating the impact of noise pollution data communication on citizens using ICTs exclusively, such as questionnaires and online visualization systems.
  • Possible bias problems have been identified in leisure noise assessment surveys associated with the use of these as tools to show discomfort with municipal management.
  • Differences in annoyance associated with leisure noise have been detected in citizens who are members of associations against noise.
  • The hypothesis is that citizens express their opinions and feelings about noise pollution through online social media sites spontaneously.
  • A methodology has been described that allows the detection of complaints that citizens share about noisy activities in online social networks, as well as a system to classify them by the sound source to which they refer.
  • A taxonomy and vocabulary of terms on sound sources has been developed, based on the results of a previous research study, in which the number of words associated with sound sources present in the vocabulary has been increased from 228 to 4506 terms, using lexicon-hierarchical databases and tools provided by semantic web technologies.
  • The Noytext tool has been developed, which is a web application with the purpose of facilitating and accelerating the process of assigning classes to short text documents that will be used in text mining research applied to environmental acoustics and noise perception.
  • The noise complaint detection and classification models have been incorporated into a proof-of-concept capable of monitoring social networks to automatically identify events that are annoying for citizens due to the noise they generate. Additionally, a system to infer the specific origin of the discomfort within the events detected by semantic analysis has been shown.
  • A methodology has been proposed for the creation of alarm systems capable of detecting specific activities that are annoying to the public because of their noise level, and that also has the potential to predict these situations. The system is built using statistical process control techniques and the time series of complaints detected.
  • A methodology has been proposed to estimate the percentage of the population exposed to different noise levels in a specific area through the use of open data.
  • The relationship between the presence of sound sources, other than the means of transport considered in the noise maps, with cardiovascular diseases associated with noise pollution such as hypertension has been verified. In addition, using data from social media to estimate the presence of these sound sources is a valid method for conducting studies of this nature in the future.
  • Socioeconomic class analysis has shown that noise from traffic and trains in upper-class areas cannot explain the hypertension suffered by its residents. However, information on the presence of sound sources, taken from social media, such as mechanical noises, does explain it partially.