Mid Sweden University

This commentary highlights the importance of uncertainty and estimation associated with the measurement of noise levels in the industrial field. As 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 which 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 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 uncertainty of acoustic noise is calculated using the normal bootstrap method. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.