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Advanced Noise Indicator Mapping Relying on a City Microphone Network

Sensors, ISSN: 1424-8220, Vol: 23, Issue: 13
2023
  • 3
    Citations
  • 0
    Usage
  • 8
    Captures
  • 2
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    3
  • Captures
    8
  • Mentions
    2
    • Blog Mentions
      1
      • Blog
        1
    • News Mentions
      1
      • News
        1

Most Recent News

Ghent University Researcher Updates Understanding of Sensor Research (Advanced Noise Indicator Mapping Relying on a City Microphone Network)

2023 JUL 06 (NewsRx) -- By a News Reporter-Staff News Editor at Tech Daily News -- Investigators publish new report on sensor research. According to

Article Description

In this work, a methodology is presented for city-wide road traffic noise indicator mapping. The need for direct access to traffic data is bypassed by relying on street categorization and a city microphone network. The starting point for the deterministic modeling is a previously developed but simplified dynamic traffic model, the latter necessary to predict statistical and dynamic noise indicators and to estimate the number of noise events. The sound propagation module combines aspects of the CNOSSOS and QSIDE models. In the next step, a machine learning technique—an artificial neural network in this work—is used to weigh the outcomes of the deterministic predictions of various traffic parameter scenarios (linked to street categories) to approach the measured indicators from the microphone network. Application to the city of Barcelona showed that the differences between predictions and measurements typically lie within 2–3 dB, which should be positioned relative to the 3 dB variation in street-side measurements when microphone positioning relative to the façade is not fixed. The number of events is predicted with 30% accuracy. Indicators can be predicted as averages over day, evening and night periods, but also at an hourly scale; shorter time periods do not seem to negatively affect modeling accuracy. The current methodology opens the way to include a broad set of noise indicators in city-wide environmental noise impact assessment.

Bibliographic Details

Van Renterghem, Timothy; Le Bescond, Valentin; Dekoninck, Luc; Botteldooren, Dick

MDPI AG

Chemistry; Computer Science; Physics and Astronomy; Biochemistry, Genetics and Molecular Biology; Engineering

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