基于智能手机的声级计的评估

Trinity Cheng
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引用次数: 2

摘要

免费的、广泛使用的基于智能手机的声级计已被用于在短时间内收集大量分布式数据,以有效地创建众包噪声地图。然而,正如之前的研究表明的那样,这些应用程序的准确性可能会有很大差异。在这项研究中,测试了四个基于智能手机的声级计来评估它们的一致性。研究人员进行了四项实验,以测试不同应用程序、操作系统、智能手机硬件和麦克风在不同声级下对应用程序测量的影响。测试中使用了四个应用程序、四个智能手机、两个操作系统和两种麦克风类型,以及一个基于硬件的声级计。采用均方根误差和线性度两种评价方法对误差进行评价。实验结果表明,对于相同的输入刺激,所有的应用程序都会产生不同的读数。换句话说,每个应用程序、操作系统、智能手机硬件和外部麦克风都会影响基于智能手机的声级计的准确性。由于测量结果的差异很大,使用未经校准的智能手机声级计进行严重的噪音评估似乎是不可接受的。然而,一些应用程序显示的高线性度表明通过专业级仪器校准提高精度的潜力。
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Evaluation of Smartphone-based Sound Level Meters
Free, widely-available smartphone-based sound level meters have been utilized to collect large quantities of distributed data in short time periods for the efficient creation of crowd-sourced noise maps. However, the accuracy of these apps can vary greatly as previous studies have shown. In this study, four smartphone-based sound level meters were tested to evaluate their agreement. Four experiments were conducted to test the impact of different apps, operating systems, smartphone hardware, and microphones on app measurements at different sound levels. A combination of four apps, four smartphones, two operating systems, and two microphone types were used in the tests, as well as a hardware-based sound level meter. Errors were evaluated based on two evaluation methods— root mean square error and linearity. The experiment results show that all of the apps produced different readings with respect to the same input stimulus. In other words, each of the apps, operating systems, smartphone hardware, and external microphones influenced the accuracy of smartphone-based sound level meters. Due to the wide variation in measurements, the usage of uncalibrated smartphone-based sound level meters seems to be unacceptable for serious noise assessments. However, the high linearity displayed by some apps indicates the potential for increased accuracy through calibration by professional-grade instruments.
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