ZARATAMAP: Noise characterization in the scope of a smart city through a low cost and mobile electronic embedded system
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Fecha
2021-03-02
Autores
Hernández Jayo, Unai
Goñi, Amaia
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Editor
MDPI AG
Resumen
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.
Palabras clave
Dynamic noise mapping
Internet of cities
Machine learning
Noise characterization
Internet of cities
Machine learning
Noise characterization
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Materias
Cita
Hernandez-Jayo, U., & Goñi, A. (2021). ZARATAMAP: Noise characterization in the scope of a smart city through a low cost and mobile electronic embedded system. Sensors, 21(5). https://doi.org/10.3390/S21051707