ZARATAMAP: Noise Characterization in the Scope of a Smart City through a Low Cost and Mobile Electronic Embedded System

• Main Authors: Unai Hernandez-Jayo, Amaia Goñi
• Format: Article
• Language: English
• Published: MDPI AG 2021-03-01
• Series: Sensors
• Subjects: Internet of cities; dynamic noise mapping; machine learning; noise characterization
• Online Access: https://www.mdpi.com/1424-8220/21/5/1707

Like other sources of pollution, noise is considered to be one of the main concerns of citizens, due to its invisibility and the potential harm it can cause. Noise pollution could be considered as one of the biggest quality-of-life concerns for urban residents in big cities, mainly due to the high levels of noise to which they may be exposed. Such levels have proven effects on health, such as: sleep disruption, hypertension, heart disease, and hearing loss. In a scenario where the number of people concentrated in cities is increasing, tools are needed to quantify, monitor, characterize, and quantify noise levels. This paper presents the ZARATAMAP project, which combines machine learning techniques with a geo-sensing application so that the authorities can have as much information as possible, using a low-cost embedded and mobile node, that is easy to deploy, develop, and use.