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Knowledge-based wireless sensors using sound pressure level for noise pollution monitoring

Authors: J. A. Mariscal-Ramirez; Jose-Ángel Fernández-Prieto; Manuel A. Gadeo Martos; Joaquín Cañada Bago;

Knowledge-based wireless sensors using sound pressure level for noise pollution monitoring

Abstract

Over the last few years, there is a growing interest in monitoring noise pollution in urban areas and some recent studies have proposed the deployment of Wireless Sensor Networks for this task. Although the noise indicators defined by European Union directive 2002/49/EC can be calculated by sensor nodes, the noise perception is affected by subjective factors and there is not a direct correlation between the indicators and the subjective perception of noise. In this work, we present a mathematic algorithm for calculating the sound pressure level in a sensor node and a Fuzzy Noise Indicator that allows sensor nodes to infer the degree of subjective noise annoyance. Each sensor node executes an adapted Fuzzy Rule-Based System which has two inputs: a) the A-weighting equivalent noise level value and b) its persistence in time. The results show that the use of this Fuzzy Indicator helps to distinguish between situations with noise annoyance and other situations less annoying.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Top 10%
Average
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