The improvement of the quality of life in the framework of the smart-city paradigm cannot be limited to measuring objective environmental factors but should also consider the assessment of the citizens’ health. Road traffic noise has been widely studied in terms of citizens’ annoyance and its impact on health, but other types of urban noise are usually out of those analysis. Each node of a wireless acoustic sensor network can pick up street noise, and can even record specific sounds that reach a higher equivalent level for study, but the most important thing for administration is whether certain types of noise annoy the citizen. In this work, we present the analysis and the selection of several audio samples collected by a wireless acoustic sensor network in an urban environment in order to conduct perceptive tests by several users. This a first approximation to the evaluation of the real perception of citizens’ annoyance of the urban noise collected by a low-cost wireless acoustic sensor network.
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I am not surprised about the results. Indeed sharpness of a noise is a predictor of annoyance and with a sharp noise the sharper the worse. But if a noise is not sharp, i.e. high frequency sounds are not dominating, other characteristics of that noise are more important. For example also a dominance of low frequency sounds is annoying. In a noise dominated by low frequencies, if you increase sharpness and keep loudness constant, you are bound to reduce the low frequency component. Therefore I would expect a U-shaped sharpness-annoyance function.
Even more difficult will be your task with loudness. What you really want to show is that loudness is a better predictor of annoyance than other measures of intensity, especially A-weighted sound-pressure level. But when you compare only noises of similar sources, the different measures of intensity will be highly correlated with each other. So you will not be able to show the superiority of one above the other.