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

Judicaël Picaut1, Ayoub Boumchich1, Erwan Bocher2

  • 1Centre for Studies on Risks, The Environment, Mobility and Urban Planning (CEREMA), Research Unit in Environmental Acoustics (UMRAE), French Institute of Science and Technology for Transport, Development and Networks (IFSTTAR), University Gustave Eiffel, F-44344 Bouguenais, France.

International Journal of Environmental Research and Public Health
|August 7, 2021
PubMed
Summary
This summary is machine-generated.

Noise pollution impacts health, making assessment crucial. This study details the NoiseCapture app

Keywords:
crowd-sourcingdata analysisenvironmental noisesmartphone application

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Area of Science:

  • Environmental Science
  • Public Health
  • Acoustics

Background:

  • Noise pollution poses significant health risks, necessitating effective assessment methods.
  • Traditional noise assessment tools have limitations, driving the need for innovative approaches.
  • Collaborative noise measurement using smartphones offers a promising alternative.

Purpose of the Study:

  • To provide comprehensive information on the quality, consistency, and completeness of data collected by the NoiseCapture application.
  • To empower the scientific community to fully utilize the NoiseCapture database for sound environment analysis.
  • To address the intrinsic limitations of smartphone-based noise measurements.

Main Methods:

  • Utilizing the NoiseCapture application, a crowdsourced mobile tool for noise data collection.
  • Leveraging an open science framework to provide free access to a substantial dataset.
  • Analyzing collected data considering factors like measurement protocols, smartphone technicalities, and data anomalies.

Main Results:

  • The NoiseCapture application has amassed a considerable volume of noise data over three years.
  • The study identifies inherent limitations in smartphone-collected noise data, including calibration absence and anomalies.
  • The database offers valuable insights for spatial and temporal noise analysis.

Conclusions:

  • The NoiseCapture database is a valuable resource for understanding sound environments.
  • Understanding data limitations is essential for accurate exploitation of crowdsourced acoustic data.
  • This work facilitates informed use of the NoiseCapture database by researchers.