A Study of the Accuracy of Mobile Technology for Measuring Urban Noise Pollution in Large-scale Participatory Sensing Campaigns

Pierre Aumond, Catherine Lavandier, Carlos Ribeiro, Elisa Gonzalez Boix, Kennedy Kambona, Ellie D'hondt, Pauline Delaitre

Research output: Contribution to journalArticlepeer-review

47 Citations (Scopus)

Abstract

The study reports on the relevancy and accuracy of using mobile phones in participatory noise pollution monitoring studies in an urban context. During one year, 60 participants used the same smartphone model to measure environmental noise at 28 different locations in Paris. All measurements were performed with the same calibrated application. The sound pressure level was recorded from the microphone every second during a 10-min period. The participants frequently measured the evolution of the sound level near two standard monitoring sound stations (in a square and near a boulevard), which enables the assessment of the accuracy and relevancy of collected acoustic measurements. The instantaneous A-weighting sound level, energy indicators such as L A,eq, L A10, L A50 or L A90 and event indicators such as the number of noise events exceeding a certain threshold L α (NNEL ⩾ L α) were measured and compared with reference measurements. The results show that instantaneous sound levels measured with mobile phones correlate very well (r > 0.9, p < 0.05) with sound levels measured with a class 1 reference sound level meter with a root mean square error smaller than 3 dB(A). About 10% of the measurements for the boulevard location (respectively 20% for the square) were inaccurate (r < 0.3, p < 0.05). Nevertheless, mobile phone measurements are in agreement for the L A50 and the L A90 acoustic indicators with the fixed station (4-m high) measurements, with a median deviation smaller than 1.5 dB(A) for the boulevard (respectively 3 dB(A) for the square).

Original languageEnglish
Pages (from-to)219-226
Number of pages8
JournalApplied Acoustics
Volume117
DOIs
Publication statusPublished - Feb 2017

Keywords

  • Crowdsourcing
  • Mobile phones
  • Participatory sensing
  • Sound level monitoring
  • Urban studies

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