Noisemonitor : A Python Package for Sound Level Monitor Analysis

Authors

  • Valérian Fraisse Schulich School of Music, McGill University, Montreal, CanadaSTMS Ircam-CNRS-SU, Paris, FranceCentre for Interdisciplinary Research in Music Media and Technology, Montreal, Canada, CA

Abstract

Noise exposure represents a major environmental issue and a burden on public health. The measurement and analysis of acoustic parameters through short-term and long-term noise monitoring is required for the identification of excessively noisy areas and planning for corresponding noise abatement measures or soundscape interventions. Major public health organizations such as the World Health Organization set up guidelines on maximum average noise exposure based on acoustic indicators such as Lden and Lnight. We present noisemonitor (https://pypi.org/project/noisemonitor/), a python package for short-term and long-term sound level monitor data analysis. The package allows for the calculation of acoustic indicators including average LAeq, Lden, LA10 or LA90 from short or long-term sound level monitor data in a few lines of code. In addition, it allows to compute and plot weekly and daily rolling averages to observe daily profiles and easily identify trends such as weekly public space use or recurring noise emissions. This python package could save time for professionals of the built environment by providing an easy-to-use tool for sound level monitor data analysis.

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Published

2023-10-09

How to Cite

1.
Fraisse V. Noisemonitor : A Python Package for Sound Level Monitor Analysis. Canadian Acoustics [Internet]. 2023 Oct. 9 [cited 2023 Nov. 30];51(3):168-9. Available from: https://jcaa.caa-aca.ca/index.php/jcaa/article/view/4084

Issue

Vol. 51 No. 3 (2023): Proceedings of Acoustics Week in Canada 2023 Conference

Section

Proceedings of the Acoustics Week in Canada

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