A commentary on the role of noise measurement uncertainty in the industrial context

This commentary highlights the importance of uncertainty and estimation associated with the measurement of noise levels in the industrial field. For example, evaluating noise workers' exposure in a workplace has to take into account levels of uncertainty. The authors investigated the effect of the variability of the measurand with respect to the uncertainty of the measurement and proposed a novel data-driven sampling approach that consists of three phases. Firstly, because the reliability of the noise indicators assessment depends significantly on the temporal variability of the noise, a statistic procedure is proposed to locate a corresponding minimum number of sound pressure levels necessary for having the statistical significance of the initial data set. Next, a numerical algorithm finds and deletes the anomalous values (outliers) from a population of real data. Finally, the inherent variability of the uncertainty of acoustic noise is calculated using the normal bootstrap method.