VALIDATION OF PREDICTIVE ALGORITHMS FOR THE ESTIMATION OF THE NUMBER OF PEOPLE IN A CANTEEN

Giulia Calia, Giuseppina Emma Puglisi, Louena Shtrepi, Fabrizio Riente, Pasquale Bottalico, Dario D'Orazio, Arianna Astolfi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study aims to estimate the number of people in a canteen from the babble noise level in the room. Noise levels were measured in the CIRCOOP canteen of the Politecnico di Torino across 4 days during the COVID pandemic, while three people counters, based on IR sensors, were located at the entrance and at the exit of the canteen. Reverberation time was also measured to calibrate the acoustic model in Odeon 16 and Grasshopper application of Rhinoceros 7 was used to calculate some parameters needed for the application of two prediction algorithms. The former assumes a diffuse field while the latter does not, and instead, it considers the rate of spatial decay per distance doubling and the interpersonal distance. Besides the acoustical parameters of the room, the models need as input the group size g and the Lombard slope c, which strongly depend on human context. In the case of this canteen, the best matching was obtained with g=8 and c=0.5 for both the models. Our results showed that the prediction of the number of people from the babble noise is possible only for noise levels lower than 70 dB(A).

Original languageEnglish (US)
Title of host publicationForum Acusticum 2023 - 10th Convention of the European Acoustics Association, EAA 2023
PublisherEuropean Acoustics Association, EAA
ISBN (Electronic)9788888942674
StatePublished - 2023
Event10th Convention of the European Acoustics Association, EAA 2023 - Torino, Italy
Duration: Sep 11 2023Sep 15 2023

Publication series

NameProceedings of Forum Acusticum
ISSN (Print)2221-3767

Conference

Conference10th Convention of the European Acoustics Association, EAA 2023
Country/TerritoryItaly
CityTorino
Period9/11/239/15/23

Keywords

  • anthropic noise
  • babble noise
  • Canteen
  • Lombard slope
  • number of people
  • prediction algorithm

ASJC Scopus subject areas

  • Acoustics and Ultrasonics

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