Abstract
Large venues and auditoriums are commonly associated with their astounding architecture. Their acoustic quality is an essential factor in its qualification as a great and functional, or a badly designed place. However, acoustics is often overlooked during the design stage of a building due to the complexity and high cost of the measurements involved. For this reason, it is important to explore more accessible ways to implement acoustics evaluations. The aim of this work is to compare typical experimental measuring methods and the use of mobile devices to assess the acoustic quality of a room. These measurements are contrasted with the software simulation of the same acoustical space. The results show that the mobile system can be used for professional measurements with low restrictions in the frequency range of interest of this study (90 Hz to 4000 Hz).Keywords:
architectural acoustics, acoustical parameters of room, room acoustics, mobile devicesReferences
1. Aumond P. et al. (2017), A study of the accuracy of mobile technology for measuring urban noise pollution in large scale participatory sensing campaigns, Applied Acoustics, 117: 219–226, doi: 10.1016 /j.apacoust.2016.07.011.
2. Bluyssen P.M., Zhang D., Kurvers S., Overtoom M., Ortiz-Sanchez M. (2018), Self-reported health and comfort of school children in 54 classrooms of 21 Dutch school buildings, Building and Environment, 138: 106–123, https://doi.org/10.1016/j.buildenv.2018.04.032
3. Brown R., Evans L. (2011), Acoustics and the smartphone, Proceedings of ACOUSTICS, November 2–4, 2011, Gold Coast, Australia, paper No. 106.
4. Catt acoustics, from https://www.catt.se/
5. Choi Y.J. (2017), Comparison of two types of combined measures, STI and U50, for predicting speech intelligibility in classrooms, Archives of Acoustics, 42(3): 527–532, https://doi.org/10.1515/aoa-2017-0056
6. Choi Y.J. (2018), Effects of the distribution of occupants in partially occupied classrooms, Applied Acoustics, 140: 1–12, https://doi.org/10.1016/j.apacoust.2018.05.015
7. Cowan J.P. (2016), The effects of sound on people, John Wiley & Sons, Inc., New York.
8. Devarakonda S., Sevusu P., Liu H., Liu R., Iftode L., Nath B. (2013), Real-time air quality monitoring through mobile sensing in metropolitan areas, Proceedings of 2nd ACM SIGKDD International workshop on urban computing, Chicago, Illinois, USA, Article No.: 15, 8 pages, https://doi.org/10.1145/2505821.2505834
9. Dick D.A., Vigeant M.C. (2016), A comparison of measured room acoustics metrics using a spherical microphone array and conventional methods, Applied Acoustics, 107: 34–45, https://doi.org/10.1016/j.apacoust.2016.01.008
10. DiMarino C. et al. (2011), Acoustic enhancement of proposed grand lecture hall using computer simulation, Canadian Acoustics, 39(1): 43–48, https://jcaa.caa-aca.ca/index.php/jcaa/article/view/2329/2078
11. D’Orazio D., Rossi E., Garai M. (2018), Comparison of different in situ measurements techniques of intelligibility in an open-plan office, Building Acoustics, 25(2): 111–122, https://doi.org/10.1177/1351010X18776431
12. Dutta P. et al. (2009), Common sense: participatory urban sensing using a network of handheld air quality monitors, [In:] Proceedings of the 7th ACM conference on embedded networked sensor systems, pp. 349–350.
13. Escobar V.G., Morillas J.B. (2015), Analysis of intelligibility and reverberation time recommendations in educational rooms, Applied Acoustics, 96: 1–10, https://doi.org/10.1016/j.apacoust.2015.03.001
14. Fausti P., Farina A. (2000), Acoustic measurements in opera houses: comparison between different techniques and equipment, Journal of Sound and Vibration, 232(1): 213–229, https://doi.org/10.1006/jsvi.1999.2694
15. Gómez-Tejedor J.A., Castro-Palacio J.C., Monsoriu J.A. (2014), The acoustic Doppler effect applied to the study of linear motions, European Journal of Physics, 35(2): 025006, https://doi.org/10.1088/0143-0807/35/2/025006
16. González M.Á., González M.Á. (2016), Smartphones as experimental tools to measure acoustical and mechanical properties of vibrating rods, European Journal of Physics, 37(4): 045701, https://doi.org/10.1088/0143-0807/37/4/045701
17. Hawley S.H., McClain R.E. (2016), Visualizing sound directivity via smartphone sensors, Journal of the Acoustical Society of America, 56(2): 72–74, https://doi.org/10.1119/1.5021430
18. Hodgson M. (1999), Experimental investigation of the acoustical characteristics of university classrooms, Journal of the Acoustical Society of America, 106(4): 1810–1819, https://doi.org/10.1121/1.427931
19. Ibarra D., Ledesma R., Lopez E. (2018), Design and construction of an omnidirectional sound source with inverse filtering approach for optimization, HardwareX, 4: e00033, https://doi.org/10.1016/j.ohx.2018.e00033
20. ISO 3382-1: 2009: Acoustics – Measurement of room acoustic parameters – Part 1: Performance spaces.
21. Kanjo E. (2010), Noisespy: A real-time mobile phone platform for urban noise monitoring and mapping, Mobile Networks and Applications, 15(4), 562–574, https://doi.org/10.1007/s11036-009-0217-y
22. Khan S.I., Jawarkar N.P., Ahmed V. (2012), Cell phone based remote early detection of respiratory disorders for rural children using modified stethoscope, International Conference on Communication Systems and Network Technologies, pp. 936–940, Rajkot, India, https://doi.org/10.1109/CSNT.2012.199
23. Klein P., Hirth M., Gröber S., Kuhn J., Müller A. (2014), Classical experiments revisited: smartphones and tablet PCs as experimental tools in acoustics and optics, Physics Education, 49(4): 412–418, https://doi.org/10.1088/0031-9120/49/4/412
24. Kuhn J., Vogt P. (2013), Analyzing acoustic phenomena with a smartphone microphone, The Physics Teacher, 51(2): 118–119, https://doi.org/10.1119/1.4775539
25. Maisonneuve N., Stevens M., Niessen M.E., Steels L. (2009), NoiseTube: Measuring and mapping noise pollution with mobile phones, [in:] Information technologies in environmental engineering, Athanasiadis I., Mitkas P., Rizzoli A., Marx J. [Eds], pp. 215–228, Springer, Berlin–Heidelberg, https://doi.org/10.1007/978-3-540-88351-7_16
26. Nam Y., Kong Y., Reyes B., Reljin N., Chon K.H. (2016), Monitoring of heart and breathing rates using dual cameras on a smartphone, PloS one, 11(3): e0151013, https://doi.org/10.1371/journal.pone.0151013
27. Nowoświat A., Olechowska M. (2016), Investigation studies on the application of reverberation time, Archives of Acoustics, 41(1): 15–26, https://doi.org/10.1515/aoa-2016-0002
28. Nowoświat A., Olechowska M. (2017), Estimation of reverberation time in classrooms using the residual minimization method, Archives of Acoustics, 42(4): 609–617, https://doi.org/10.1515/aoa-2017-0065
29. Rana R.K., Chou C.T., Kanhere S.S., Bulusu N., Hu W. (2010), Ear-phone: an end-to-end participatory urban noise mapping system, Proceedings of 9th ACM/IEEE International Conference on Information Processing in Sensor Networks, pp. 105–116, Stockholm, Sweden, https://doi.org/10.1145/1791212.1791226
30. Reddy S., Parker A., Hyman J., Burke J., Estrin D., Hansen M. (2007), Image browsing, processing, and clustering for participatory sensing, Proceedings of the 4th Workshop on Embedded Networked Sensors, pp. 13–17, Cork, Ireland, https://doi.org/10.1145/1278972.1278975
31. Reyes B., Reljin N., Chon K. (2014), Tracheal sounds acquisition using smartphones, Sensors, 14(8): 13830–13850, https://doi.org/10.3390/s140813830
32. Rizzi L., Ghelfi G., Campanini S., Rosati A. (2015), Rapid room acoustics parameters measurements with smartphones, 22nd International Congress on Sound & Vibration, pp. 1–8, Florence, Italy.
33. ODEON – Room Acoustics Simulations and Measurements, from: https://odeon.dk/
34. Rubel P. et al.(2005), Toward personal eHealth in cardiology. Results from the EPI-MEDICS telemedicine project, Journal of Electrocardiology, 38(4, Supplement): 100–106, https://doi.org/10.1016/j.jelectrocard.2005.06.011
35. Saba M.M., da S. Rosa R.A. (2003), The Doppler effect of a sound source moving in a circle, The Physics Teacher, 41(2): 89–91, https://doi.org/10.1119/1.1542044
36. Sans J.A., Manjón F.J., Pereira A.L.J., Gómez-Tejedor J.A., Monsoriu J.A. (2013), Oscillations studied with the smartphone ambient light sensor, European Journal of Physics, 34(6): 1349–1354, https://doi.org/10.1088/0143-0807/34/6/1349
37. Satoh F., Sakagami K., Omoto A. (2016), Application of a smartphone for introductory teaching of sound environment: Validation of the precision of the devices and examples of students' work, Acoustical Science and Technology, 37(4): 165–172, https://doi.org/10.1250/ast.37.165
38. Scherr D., Zweiker R., Kollmann A., Kastner P., Schreier G., Fruhwald F.M. (2006), Mobile phone-based surveillance of cardiac patients at home, Journal of Telemedicine and Telecare, 12(5): 255–261, https://doi.org/10.1258/135763306777889046
39. Scully C.G. et al. (2012), Physiological parameter monitoring from optical recordings with a mobile phone, IEEE Transactions on Biomedical Engineering, 59(2): 303–306, https://doi.org/10.1109/TBME.2011.2163157
40. Schroeder M.R. (1965), New method of measuring reverberation time, Journal of the Acoustical Society of America, 37(3): 409–412, https://doi.org/10.1121/1.1909343
41. Software – EASE – Enhanced Acoustic Simulator for Engineers, from: https://ease.afmg.eu/
42. SoundCity : a mobile application for understanding your exposure to noise pollution – Inria, from: https://www.inria.fr/en/centre/paris/news/launch-of-soundcity-mobile-application
43. SoundPrint – Find your quiet place, from: https://www.soundprint.co/
44. Stansfeld S.A., Matheson M.P. (2003), Noise pollution: non-auditory effects on health, British Medical Bulletin, 68(1): 243–257, https://doi.org/10.1093/bmb/ldg033
45. Ventola C.L. (2014), Social media and health care professionals: benefits, risks, and best practices, Pharmacy and Therapeutics, 39(7): 491–520, https://www.ncbi.nlm.nih.gov/pubmed/25083128
46. Wong A.C., Ryan A.F. (2015), Mechanisms of sensorineural cell damage, death and survival in the cochlea, Frontiers in Aging Neuroscience, 7: article 58, https://doi.org/10.3389/fnagi.2015.00058
47. Zannin P.H.T., Zwirtes D.P.Z. (2009), Evaluation of the acoustic performance of classrooms in public schools, Applied Acoustics, 70(4): 626–635, https://doi.org/10.1016/j.apacoust.2008.06.007
2. Bluyssen P.M., Zhang D., Kurvers S., Overtoom M., Ortiz-Sanchez M. (2018), Self-reported health and comfort of school children in 54 classrooms of 21 Dutch school buildings, Building and Environment, 138: 106–123, https://doi.org/10.1016/j.buildenv.2018.04.032
3. Brown R., Evans L. (2011), Acoustics and the smartphone, Proceedings of ACOUSTICS, November 2–4, 2011, Gold Coast, Australia, paper No. 106.
4. Catt acoustics, from https://www.catt.se/
5. Choi Y.J. (2017), Comparison of two types of combined measures, STI and U50, for predicting speech intelligibility in classrooms, Archives of Acoustics, 42(3): 527–532, https://doi.org/10.1515/aoa-2017-0056
6. Choi Y.J. (2018), Effects of the distribution of occupants in partially occupied classrooms, Applied Acoustics, 140: 1–12, https://doi.org/10.1016/j.apacoust.2018.05.015
7. Cowan J.P. (2016), The effects of sound on people, John Wiley & Sons, Inc., New York.
8. Devarakonda S., Sevusu P., Liu H., Liu R., Iftode L., Nath B. (2013), Real-time air quality monitoring through mobile sensing in metropolitan areas, Proceedings of 2nd ACM SIGKDD International workshop on urban computing, Chicago, Illinois, USA, Article No.: 15, 8 pages, https://doi.org/10.1145/2505821.2505834
9. Dick D.A., Vigeant M.C. (2016), A comparison of measured room acoustics metrics using a spherical microphone array and conventional methods, Applied Acoustics, 107: 34–45, https://doi.org/10.1016/j.apacoust.2016.01.008
10. DiMarino C. et al. (2011), Acoustic enhancement of proposed grand lecture hall using computer simulation, Canadian Acoustics, 39(1): 43–48, https://jcaa.caa-aca.ca/index.php/jcaa/article/view/2329/2078
11. D’Orazio D., Rossi E., Garai M. (2018), Comparison of different in situ measurements techniques of intelligibility in an open-plan office, Building Acoustics, 25(2): 111–122, https://doi.org/10.1177/1351010X18776431
12. Dutta P. et al. (2009), Common sense: participatory urban sensing using a network of handheld air quality monitors, [In:] Proceedings of the 7th ACM conference on embedded networked sensor systems, pp. 349–350.
13. Escobar V.G., Morillas J.B. (2015), Analysis of intelligibility and reverberation time recommendations in educational rooms, Applied Acoustics, 96: 1–10, https://doi.org/10.1016/j.apacoust.2015.03.001
14. Fausti P., Farina A. (2000), Acoustic measurements in opera houses: comparison between different techniques and equipment, Journal of Sound and Vibration, 232(1): 213–229, https://doi.org/10.1006/jsvi.1999.2694
15. Gómez-Tejedor J.A., Castro-Palacio J.C., Monsoriu J.A. (2014), The acoustic Doppler effect applied to the study of linear motions, European Journal of Physics, 35(2): 025006, https://doi.org/10.1088/0143-0807/35/2/025006
16. González M.Á., González M.Á. (2016), Smartphones as experimental tools to measure acoustical and mechanical properties of vibrating rods, European Journal of Physics, 37(4): 045701, https://doi.org/10.1088/0143-0807/37/4/045701
17. Hawley S.H., McClain R.E. (2016), Visualizing sound directivity via smartphone sensors, Journal of the Acoustical Society of America, 56(2): 72–74, https://doi.org/10.1119/1.5021430
18. Hodgson M. (1999), Experimental investigation of the acoustical characteristics of university classrooms, Journal of the Acoustical Society of America, 106(4): 1810–1819, https://doi.org/10.1121/1.427931
19. Ibarra D., Ledesma R., Lopez E. (2018), Design and construction of an omnidirectional sound source with inverse filtering approach for optimization, HardwareX, 4: e00033, https://doi.org/10.1016/j.ohx.2018.e00033
20. ISO 3382-1: 2009: Acoustics – Measurement of room acoustic parameters – Part 1: Performance spaces.
21. Kanjo E. (2010), Noisespy: A real-time mobile phone platform for urban noise monitoring and mapping, Mobile Networks and Applications, 15(4), 562–574, https://doi.org/10.1007/s11036-009-0217-y
22. Khan S.I., Jawarkar N.P., Ahmed V. (2012), Cell phone based remote early detection of respiratory disorders for rural children using modified stethoscope, International Conference on Communication Systems and Network Technologies, pp. 936–940, Rajkot, India, https://doi.org/10.1109/CSNT.2012.199
23. Klein P., Hirth M., Gröber S., Kuhn J., Müller A. (2014), Classical experiments revisited: smartphones and tablet PCs as experimental tools in acoustics and optics, Physics Education, 49(4): 412–418, https://doi.org/10.1088/0031-9120/49/4/412
24. Kuhn J., Vogt P. (2013), Analyzing acoustic phenomena with a smartphone microphone, The Physics Teacher, 51(2): 118–119, https://doi.org/10.1119/1.4775539
25. Maisonneuve N., Stevens M., Niessen M.E., Steels L. (2009), NoiseTube: Measuring and mapping noise pollution with mobile phones, [in:] Information technologies in environmental engineering, Athanasiadis I., Mitkas P., Rizzoli A., Marx J. [Eds], pp. 215–228, Springer, Berlin–Heidelberg, https://doi.org/10.1007/978-3-540-88351-7_16
26. Nam Y., Kong Y., Reyes B., Reljin N., Chon K.H. (2016), Monitoring of heart and breathing rates using dual cameras on a smartphone, PloS one, 11(3): e0151013, https://doi.org/10.1371/journal.pone.0151013
27. Nowoświat A., Olechowska M. (2016), Investigation studies on the application of reverberation time, Archives of Acoustics, 41(1): 15–26, https://doi.org/10.1515/aoa-2016-0002
28. Nowoświat A., Olechowska M. (2017), Estimation of reverberation time in classrooms using the residual minimization method, Archives of Acoustics, 42(4): 609–617, https://doi.org/10.1515/aoa-2017-0065
29. Rana R.K., Chou C.T., Kanhere S.S., Bulusu N., Hu W. (2010), Ear-phone: an end-to-end participatory urban noise mapping system, Proceedings of 9th ACM/IEEE International Conference on Information Processing in Sensor Networks, pp. 105–116, Stockholm, Sweden, https://doi.org/10.1145/1791212.1791226
30. Reddy S., Parker A., Hyman J., Burke J., Estrin D., Hansen M. (2007), Image browsing, processing, and clustering for participatory sensing, Proceedings of the 4th Workshop on Embedded Networked Sensors, pp. 13–17, Cork, Ireland, https://doi.org/10.1145/1278972.1278975
31. Reyes B., Reljin N., Chon K. (2014), Tracheal sounds acquisition using smartphones, Sensors, 14(8): 13830–13850, https://doi.org/10.3390/s140813830
32. Rizzi L., Ghelfi G., Campanini S., Rosati A. (2015), Rapid room acoustics parameters measurements with smartphones, 22nd International Congress on Sound & Vibration, pp. 1–8, Florence, Italy.
33. ODEON – Room Acoustics Simulations and Measurements, from: https://odeon.dk/
34. Rubel P. et al.(2005), Toward personal eHealth in cardiology. Results from the EPI-MEDICS telemedicine project, Journal of Electrocardiology, 38(4, Supplement): 100–106, https://doi.org/10.1016/j.jelectrocard.2005.06.011
35. Saba M.M., da S. Rosa R.A. (2003), The Doppler effect of a sound source moving in a circle, The Physics Teacher, 41(2): 89–91, https://doi.org/10.1119/1.1542044
36. Sans J.A., Manjón F.J., Pereira A.L.J., Gómez-Tejedor J.A., Monsoriu J.A. (2013), Oscillations studied with the smartphone ambient light sensor, European Journal of Physics, 34(6): 1349–1354, https://doi.org/10.1088/0143-0807/34/6/1349
37. Satoh F., Sakagami K., Omoto A. (2016), Application of a smartphone for introductory teaching of sound environment: Validation of the precision of the devices and examples of students' work, Acoustical Science and Technology, 37(4): 165–172, https://doi.org/10.1250/ast.37.165
38. Scherr D., Zweiker R., Kollmann A., Kastner P., Schreier G., Fruhwald F.M. (2006), Mobile phone-based surveillance of cardiac patients at home, Journal of Telemedicine and Telecare, 12(5): 255–261, https://doi.org/10.1258/135763306777889046
39. Scully C.G. et al. (2012), Physiological parameter monitoring from optical recordings with a mobile phone, IEEE Transactions on Biomedical Engineering, 59(2): 303–306, https://doi.org/10.1109/TBME.2011.2163157
40. Schroeder M.R. (1965), New method of measuring reverberation time, Journal of the Acoustical Society of America, 37(3): 409–412, https://doi.org/10.1121/1.1909343
41. Software – EASE – Enhanced Acoustic Simulator for Engineers, from: https://ease.afmg.eu/
42. SoundCity : a mobile application for understanding your exposure to noise pollution – Inria, from: https://www.inria.fr/en/centre/paris/news/launch-of-soundcity-mobile-application
43. SoundPrint – Find your quiet place, from: https://www.soundprint.co/
44. Stansfeld S.A., Matheson M.P. (2003), Noise pollution: non-auditory effects on health, British Medical Bulletin, 68(1): 243–257, https://doi.org/10.1093/bmb/ldg033
45. Ventola C.L. (2014), Social media and health care professionals: benefits, risks, and best practices, Pharmacy and Therapeutics, 39(7): 491–520, https://www.ncbi.nlm.nih.gov/pubmed/25083128
46. Wong A.C., Ryan A.F. (2015), Mechanisms of sensorineural cell damage, death and survival in the cochlea, Frontiers in Aging Neuroscience, 7: article 58, https://doi.org/10.3389/fnagi.2015.00058
47. Zannin P.H.T., Zwirtes D.P.Z. (2009), Evaluation of the acoustic performance of classrooms in public schools, Applied Acoustics, 70(4): 626–635, https://doi.org/10.1016/j.apacoust.2008.06.007
