Home-Made Simple Experiment to Measure Sound Intensity using Smartphones

Ade Yeti Nuryantini, Rizki Zakwandi, Muhamad Ari Ariayuda

Abstract


The researchers present a simple experimental activity to measure the sound intensity level using an Android-based smartphone to prove the inverse square law and analyze the dependence of the sound intensity to the sound source frequency. The type of this study was quantitative research by conducting level of intensity experiment using a pair of smartphones with one smartphone functioning as the sound source using a tone generator free application (app) and the other smartphone functioning as the detector installed with Physics Toolbox sound meter application to measure the arriving sound intensity level. The smartphone functioning as the sound source was placed at a certain place labeled as the origin point (0.0), while the other smartphone as the detector was placed at various distances on the x-axis. In this study, the frequencies of the tone generator used were 500 Hz, 1000 Hz, and 2000 Hz. Then, the sound intensity level versus distance was analyzed to determine the compatibility between the experimental results using a smartphone and the prevailing theory, namely the inverse square model. The sound intensity level detected by the smartphone from 2,000 Hz resulted in the graph with smaller slope after passing 0.3 meters. The results follow the theorem of which the sound intensity level at the detector depends on the distance between the source and the detector based on the inverse square law. When the frequency of a source was changed (500 Hz, 1000 Hz and 2000), the sound intensity also changed. Higher frequency leads to a larger sound intensity. The experiment can thus be used to assist  high school students and physics undergraduates in understanding the inverse square law of sound or to study environmental noise with a simple and low-cost experiment.

Keywords


Inverse square law; Sound meter; Tone generator

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References


Adnan, M., & Anwar, K. (2020). Online Learning amid the COVID-19 Pandemic: Students’ Perspectives. Online Submission, 2(1), 45–51. https://doi.org/http://www.doi.org/10.33902/JPSP.%202020261309

Ali, W. (2020). Online and remote learning in higher education institutes: A necessity in light of COVID-19 pandemic. Higher Education Studies, 10(3), 16–25. https://doi.org/https://doi.org/10.5539/hes.v10n3p16

Apipah, I. (2016). Distribution profile of sound level intensity with smart chip wt5001 using sound of blaganjur and cengceng. Journal Fisika, 5(6), 354–362. http://journal.student.uny.ac.id/ojs/ojs/index.php/fisika/article/view/3402

Ariz, I. S., Giménez, M. H., Castro-Palacio, J. C., Gómez-Tejedor, J. A., & Monsoriu, J. A. (2017). The smartphone as a sound level meter: Visualizing acoustical beats. Technica Industria, 318, 34–38. http://www.tecnicaindustrial.es/TIFrontal/sumario.aspx?id=108

Churiyah, M., Sholikhan, S., Filianti, F., & Sakdiyyah, D. A. (2020). Indonesia education readiness conducting distance learning in Covid-19 pandemic situation. International Journal of Multicultural and Multireligious Understanding, 7(6), 491–507.

Daniel, J. (2020). Education and the COVID-19 pandemic. Prospects, 49(1), 91–96.

De Mesnard, L. (2013). Pollution models and inverse distance weighting: Some critical remarks. Computers and Geosciences, 52, 459–469. https://doi.org/10.1016/j.cageo.2012.11.002

Dias, M. A., Carvalho, P. S., & Ventura, D. R. (2016). How to study the doppler effect with audacity software. Physics Education, 51(3), 35002. https://doi.org/https://doi.org/10.1088/0031-9120/51/3/035002

Dierecks, G. R., Ojha, S., Infusino, S., Maurer, R., & Hartnick, C. J. (2013). Consistency of voice frequency and perturbation measures in children using cepstral analyses amovement toward increased recording stability. JAMA Otolaryngology-Head & Neck Sur, 139(8), 811–816. https://doi.org/10.1001/jamaoto.2013.3926

Fahy, F., & Thompson, D. (2016). Fundamentals of sound and vibration. CRC Press.

Florea, C. (2019). Brief analysis of sounds using a smartphone. The Physics Teacher, 57(4), 214–215. https://doi.org/10.1119/1.5095371

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). https://doi.org/10.1088/0143-0807/35/2/025006

González, M. Á., Martín, M. E., & Herguedas, M. (2014). Mobile phones for teaching physics : Using applications and sensors. Second International Conference on Technological Ecosystems for Enhancing Multiculturality - TEEM’14, 349–355.

Hasan, W. L., Wijayanto, I., & Susatio, E. (2016). Design and implementation of audio meter based in android. E-Proceedings of Engineering, 3(3), 4371-4378

Hawley, S. H., & McClain, R. E. (2018). Visualizing sound directivity via smartphone sensors. The Physics Teacher, 56(2), 72–74. https://doi.org/10.1119/1.5021430

Hellesund, S. (2019). Measuring the speed of sound in air using a smartphone and a cardboard tube. Physics Education, 54(3). https://doi.org/10.1088/1361-6552/ab0e21

Hirth, M., Kuhn, J., & Muller, A. (2015). Measurement of sound velocity made easy using harmonic resonant frequencies with everyday mobile technology. The Physics Teacher, 53(120). https://doi.org/10.1119/1.4905819

Kasper, L., Vogt, P., & Strohmeyer, C. (2015). Stationary waves in tubes and the speed of sound. The Physics Teacher, 53(1), 52–53. https://doi.org/10.1119/1.4904249

Kuhn, J., & Vogt, P. (2013). Analyzing acoustic phenomena with a smartphone microphone. The Physics Teacher, 51(118), 2–4. https://doi.org/10.1119/1.4775539

Kumar, N. (2001). A laboratory and field study of the attenuation of sound intensity using a whistle as the sonic generator. New Jersey Institute of Technology.

Kuruvilla-Mathew, A., Purdy, S. C., & Welch, D. (2015). Cortical encoding of speech acoustics: Effects of noise and amplification. International Journal of Audiology, 54(11), 852–864. https://doi.org/http://doi.org/https://doi.org/10.3109/14992027.2015.1055838

Li, L., & Gong, Q. (2016). The early component of middle latency auditory-evoked potentials in the process of deviance detection. NeuroReport, 27(10), 769–773. https://doi.org/http://doi.org/10.1097/WNR.0000000000000611

Meitei, S. N., Borah, K., & Chatterjee, S. (2020). Modelling of acoustic wave propagation due to partial discharge and its detection and localization in an oil-filled distribution transformer. Frequenz, 74(1–2), 73–81. https://doi.org/https://doi.org/10.1515/freq-2019-0050

Odenwald, S. (2020). Smartphone sensors for citizen science applications: Light and sound. Citizen Science: Theory and Practice, 5(1). https://doi.org/http://doi.org/10.5334/cstp.254

Olsson, J., & Linderholt, A. (2019). Force to sound pressure frequency response measurements using a modified tapping machine on timber floor structures. Engineering Structures, 196, 109343. https://doi.org/10.1016/j.engstruct.2019.109343

Osario, M., Pereyra, C. J., Gau, D. L., & Laguarda, A. (2017). Measuring and characterizing beat phenomena with a smartphone. European Journal of Physics, 39(2), 1–12. https://doi.org/10.1088/1361-6404/aa9034 Manuscript

Parolin, S. O., & Pezzi, G. (2015). Kundt’s tube experiment using smartphones. Physics Education, 50(4), 443–447. https://doi.org/10.1088/0031-9120/50/4/443

Pereira da Silva, W., Precker, J. W., e Silva, D. D. P. S., & e Silva, C. D. P. S. (2005). The speed of sound in air: An at-home experiment. The Physics Teacher, 43(4), 219–221. https://doi.org/10.1119/1.1888080

Pili, U. B. (2020). Sound-based measurement of g using a door alarm and a smartphone: Listening to the simple pendulum. Physics Education, 55(3). https://doi.org/10.1088/1361-6552/ab6e00

Puspitasari, K. A., & Oetoyo, B. (2018). Successful students in an open and distance learning system. Turkish Online Journal of Distance Education, 19(2), 189–200. https://doi.org/https://doi.org/10.17718/tojde.415837

Serway, R. A., & Jewett, J. W. (2018). Physics for scientists and engineers. Cengage learning.

Staacks, S., Heinke, H., & Stampfer, C. (2019). Simple time-of-flight measurement of the speed of sound using smartphones. The Physics Teacher, 57(112). https://doi.org/10.1119/1.5088474

Thees, M., Hochberg, K., Kuhn, J., & Aeschlimann, M. (2017). Adaptation of acoustic model experiments of STM via smartphones and tablets. The Physics Teacher, 55(7), 436–437. https://doi.org/10.1119/1.5003749

Tipler, P. A., & Mosca, G. P. (2010). Physics for scientists and engineers: With modern physics. Wh Freeman.

Trinh, V. (1994). Measurement of sound intensity and sound power. In DSTOMaterials Research Laboratory.

Tsiatis, N. E. (2015). Understanding distance shooting and the type of rearm from the analysis of gunshot sounds. European Police Science and Research Bulletin, 15, 93–107.

Vogt, P., Hirth, M., & Kuhn, J. (2014). Analyzing the acoustic beat with mobile devices. The Physics Teacher, 52, 248–250. https://doi.org/10.1119/1.4868948

Wisman, R. F., Spahn, G., & Forinash, K. (2018). Time measurements with a mobile device using sound. Physics Education, 52, 035012.

Yafuz, A. (2015). Measuring the speed of sound in water. Physics Education, 50(6), 727–732. https://doi.org/10.1088/0031-9120/50/6/727

Yavuz, A., & Temiz, B. K. (2016). Detecting interferences with iOS applications to measure speed of sound. Physics Education, 51(1). https://doi.org/10.1088/0031-9120/51/1/015009




DOI: http://dx.doi.org/10.24042/jipfalbiruni.v10i1.8180

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