As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
Many cities around the world are deploying wireless sensor networks to capture information on different environmental parameters. Noise, as one of the main pollutants with negative effects on health and economy, is monitored through sound pressure level. In this work, the application of unsupervised clustering to sound pressure level data from a wireless acoustic sensors network (WASN) is proposed. Data from a sensor network deployed in the city of Madrid are used to show the usefulness of performing a clustering process with the aim of detecting different patterns of behavior of noise levels. The preliminary results obtained have allowed us to divide the city into several acoustic zones, which help city managers to propose improvement plans.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.