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A Smartphone-Based Crowd-Sourced Database for Environmental Noise Assessment
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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8345695/ https://www.ncbi.nlm.nih.gov/pubmed/34360073 http://dx.doi.org/10.3390/ijerph18157777 |
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author | Picaut, Judicaël Boumchich, Ayoub Bocher, Erwan Fortin, Nicolas Petit, Gwendall Aumond, Pierre |
author_facet | Picaut, Judicaël Boumchich, Ayoub Bocher, Erwan Fortin, Nicolas Petit, Gwendall Aumond, Pierre |
author_sort | Picaut, Judicaël |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8345695 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83456952021-08-07 A Smartphone-Based Crowd-Sourced Database for Environmental Noise Assessment Picaut, Judicaël Boumchich, Ayoub Bocher, Erwan Fortin, Nicolas Petit, Gwendall Aumond, Pierre Int J Environ Res Public Health Article 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. MDPI 2021-07-22 /pmc/articles/PMC8345695/ /pubmed/34360073 http://dx.doi.org/10.3390/ijerph18157777 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Picaut, Judicaël Boumchich, Ayoub Bocher, Erwan Fortin, Nicolas Petit, Gwendall Aumond, Pierre A Smartphone-Based Crowd-Sourced Database for Environmental Noise Assessment |
title | A Smartphone-Based Crowd-Sourced Database for Environmental Noise Assessment |
title_full | A Smartphone-Based Crowd-Sourced Database for Environmental Noise Assessment |
title_fullStr | A Smartphone-Based Crowd-Sourced Database for Environmental Noise Assessment |
title_full_unstemmed | A Smartphone-Based Crowd-Sourced Database for Environmental Noise Assessment |
title_short | A Smartphone-Based Crowd-Sourced Database for Environmental Noise Assessment |
title_sort | smartphone-based crowd-sourced database for environmental noise assessment |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8345695/ https://www.ncbi.nlm.nih.gov/pubmed/34360073 http://dx.doi.org/10.3390/ijerph18157777 |
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