A Smartphone-Based Crowd-Sourced Database for Environmental Noise Assessment

• Main Authors: Judicaël Picaut, Ayoub Boumchich, Erwan Bocher, Nicolas Fortin, Gwendall Petit, Pierre Aumond
• Format: Article
• Language: English
• Published: MDPI AG 2021-07-01
• Series: International Journal of Environmental Research and Public Health
• Subjects: environmental noise; crowd-sourcing; smartphone application; data analysis
• Online Access: https://www.mdpi.com/1660-4601/18/15/7777

Noise is a major source of pollution with a strong impact on health. Noise assessment is therefore a very important issue to reduce its impact on humans. To overcome the limitations of the classical method of noise assessment (such as simulation tools or noise observatories), alternative approaches have been developed, among which is collaborative noise measurement via a smartphone. Following this approach, the NoiseCapture application was proposed, in an open science framework, providing free access to a considerable amount of information and offering interesting perspectives of spatial and temporal noise analysis for the scientific community. After more than 3 years of operation, the amount of collected data is considerable. Its exploitation for a sound environment analysis, however, requires one to consider the intrinsic limits of each collected information, defined, for example, by the very nature of the data, the measurement protocol, the technical performance of the smartphone, the absence of calibration, the presence of anomalies in the collected data, etc. The purpose of this article is thus to provide enough information, in terms of quality, consistency, and completeness of the data, so that everyone can exploit the database, in full control.