Comparison of Environment Noise Intensity Using Ios and Android Based Sound Measurement Applications and Commercial Sound Measurement Devices and Obtaining the Measurement Uncertainty
Öz
In this study, sound measurement between ios and android operating system based mobile phones (Soundmeter, Decibel X) and commercial sound measurement devices (Cem dt8852, Svantek sv104) was tested. Sound measurement intensities and energies were determined, measurement uncertainties of ios and android devices according to the application were determined. Measurements were carried out at the same time in the indoor and outdoor environment. Iphone 7+ (Ios operation system) and Samsung note 8 (Andorid operation system) used. Significant sound measurement differences were obtained between the two different mobile phone applications. There was no significant difference between commercial measurement devices. Commercial measuring devices were calibrated and can be used as reference devices. Using these devices, it was observed that ios and android-based applications receive faulty measurements on average between 10-20%. As a result of the measurements taken with the applications, it was determined that the measurement uncertainty is in the range of approximately 4-5dB.
Anahtar Kelimeler
Android,, ios, Commercial devices, Mobile application, Sound intensity,, Uncertainty
Kaynakça
- ANSI S1.4-1983. (2007). Specification for Sound Level Meters (American National Standards Institute), New York.
- D’Hondt, E., Stevens, M., Jacobs, A. (2013). Participatory noise mapping works! An evaluation of participatory sensing as an alternative to standard techniques for environmental monitoring. Pervasive Mobile Computing, 9, 681–94. doi.org/10.1016/j.pmcj.2012.09.002
- Expression of the Uncertainty of Measurement in Calibration. EA-European Co-operation for Accreditation, EA-4/0. (2013). https://european-accreditation.org/wp-content/uploads/2018/10/ea-4-02-m-rev01-september-2013.pdf (accessed at 25.01.2021).
- European environment agency report. (2013). Environmental indicator report. http://www.eea.europa.eu/publications#c7=en&c11=5&c14=&c12=&b_start=0 (accessed at 25.01.2021).
- Kanhere, S.S. (2013). Participatory sensing: Crowdsourcing data from mobile smartphones in urban space. Distributed computing and internet technology; Springer. pp19-26.
- Kanjo, E. (2010). NoiseSPY: A Real-Time Mobile Phone Platform for Urban Noise Monitoring and Mapping. Mobile networks and applications, 15, 562–574. doi.org/10.1007/s11036-009-0217-y
- Kardousb, C.A., Shaw P.B., (2014). Evaluation of smartphone sound measurement applications. The journal of the acoustical society of America, 135 (4), ELI186. doi.org/10.1121/1.4865269
- Maisonneuve, N., Mathias, N., Ochab, B. (2010). Participatory noise pollution monitoring using mobile phones. Information polity, 15, 51-71. Doi.org/10.3233/IP-2010-0200
- Maisonnuve, N., Mattias, S., et.al. (2009). Citizen noise pollution monitoring. Proceedings of the 10th annual international conference on digital government research: social networks. Digital government society of north America, 96-103. doi.org/ 10.5555/1556176.1556198
- May, J.J. (2000). Occupational hearing loss. American journal of industrial medicine , 37(1), 112-20. doi.org/10.1002/(SICI)1097-0274(200001)37:1<112::AID-AJIM9>3.0.CO;2-%23