TY - GEN
T1 - VALIDATION OF PREDICTIVE ALGORITHMS FOR THE ESTIMATION OF THE NUMBER OF PEOPLE IN A CANTEEN
AU - Calia, Giulia
AU - Puglisi, Giuseppina Emma
AU - Shtrepi, Louena
AU - Riente, Fabrizio
AU - Bottalico, Pasquale
AU - D'Orazio, Dario
AU - Astolfi, Arianna
N1 - Publisher Copyright:
© 2023 First author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2023
Y1 - 2023
N2 - 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).
AB - 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).
KW - Canteen
KW - Lombard slope
KW - anthropic noise
KW - babble noise
KW - number of people
KW - prediction algorithm
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M3 - Conference contribution
AN - SCOPUS:85191229432
T3 - Proceedings of Forum Acusticum
BT - Forum Acusticum 2023 - 10th Convention of the European Acoustics Association, EAA 2023
PB - European Acoustics Association, EAA
T2 - 10th Convention of the European Acoustics Association, EAA 2023
Y2 - 11 September 2023 through 15 September 2023
ER -