DO SMARTPHONE
APPS PROVIDE ACCURATE NOISE MEASUREMENT?
Can smartphone apps, costing anywhere from $1 to $20,
provide accurate occupational noise measurements? A new study provides the
answer.
The answer is, “Yes,” but only four apps that were
tested measure up.
The National Institute for Occupational Safety and
Health (NIOSH) evaluated the
apps at its acoustic testing lab. The tests also compared results
for i-Phones and Android phones.
OSHA requires noise measurement instruments to have an
accuracy of +/- 2 decibels (dB).
For unweighted sound level measurements, NoiSee,
SoundMeter and SPLnFFT had mean differences within the +/- 2dB of the reference
measurement.
For A-weighted sound level measurements, Noise Hunter,
NoiSee and SoundMeter had mean differences within +/- 2 dBA (A-weighted
decibels) of the reference measurement. Out of these three, SoundMeter had the
best results.
NIOSH says these four apps may be considered adequate
for certain occupational noise assessments when used on iPhones.
Yep, that’s the catch: Because several manufacturers
make Android phones, there was a wide variance among the same app measurements
on difference devices. Therefore, NIOSH could not recommend a particular app
for the Android platform. No Windows phone noise apps met NIOSH’s standards
either.
Newer iPhones allow users to connect external
microphones through the headset jack when using these apps.
NIOSH says external microphones such as the MicW i436
omni-directional measurement microphone comply with the sound meter standard.
The agency plans on extending this study to examine the effect of external
microphones on the overall accuracy of sound measurement apps.
What are the benefits of having these apps on
smartphones? It’s to make employees more aware of the noise in their workplace
(or, for that matter, while using power tools at home or when attending a
concert).
And then there’s cost. Noise measurement devices can
cost $80 and up. The cost of the four apps (rounded up to the nearest dollar):
NoiSee, $1
Noise Hunter, $6
SoundMeter, $20, and
SPLnFFT, $4.
___________\\
Categories:
Hearing Loss, Technology
April
9th, 2014 11:35 am ET - Chucri A. Kardous, MS, PE and Peter
B. Shaw, Ph.D.
Figure
1. The SoundMeter app on the iPhone 5 (L) and iPhone 4S (R) compared to ½”
Larson-Davis 2559 random incidence type 1 microphone (C).
As
of June 2013, 60% of all mobile subscribers use smartphones—that’s more than
140 million devices. Apple iOS and Google Android platforms account for 93% of
those devices [Nielsen, 2013]. Smartphone developers now offer many sound
measurement applications (apps) using the devices’ built-in microphone (or
through an external microphone for more sophisticated applications). The use of
smartphone sound measurement apps can have a tremendous and far-reaching impact
in the areas of noise research and noise control in the workplace as every
smartphone can be potentially turned into a dosimeter or a sound level meter
[Maisonneuve et al., 2010; Williams and Sukara, 2013]. However, in order for
smartphone apps to gain acceptance in the occupational environment, the apps
must meet certain minimal criteria for functionality, accuracy, and relevancy
to the users in general and the worker in particular.
Video: CAPT
Kardous testing mobile sound-meter apps in the lab
NIOSH
noise researchers received numerous requests from stakeholders, safety
professionals, and the public to address the accuracy of the many sound
measurement applications available for smartphones and whether they can be
relied upon to provide an accurate assessment of the ambient environment. As a
result, we conducted a pilot study to select and characterize the functionality
and accuracy of these apps as an initial step in a broader effort to determine
whether these apps can be relied on to conduct participatory noise monitoring
studies in the workplace [Kardous and Shaw, 2014]. The resulting paper, Evaluation of smartphone sound measurement application
, was published in
the Journal of the Acoustical Society of America.
, was published in
the Journal of the Acoustical Society of America.
We
selected and acquired a representative sample of the popular smartphones and
tablets on the market as of June 2013. Smartphone apps were selected based on
their ability to measure occupationally relevant sound level values. A total of
130 iOS apps were examined and downloaded from the iTunes store*, of those, 10
apps met our selection criteria. A total of 62 Android apps were examined and
downloaded, however, only 4 apps partially met our criteria and were selected for
additional testing. As a result, a comprehensive experimental design and
analysis similar to the iOS devices and apps study above was not possible.
The
measurements were conducted in a diffuse sound field at a reverberant noise
chamber at the NIOSH acoustics testing laboratory. For our experimental setup,
we generated pink noise with a 20Hz ‒ 20kHz frequency range, at levels from 65
dB to 95 dB in 5-dB increments (7 different noise levels. Reference sound level
measurements were obtained using a ½-inch Larson-Davis (DePew, NY) model 2559
random incidence microphone. Additionally, a Larson-Davis Model 831 type 1
sound level meter was used to verify sound pressure levels. Smartphones were
set up on a stand in the middle of the chamber at a height of 4 feet and
approximately 6 inches from the reference microphone as shown in Figure 1.
Overall,
the results in Figure 2 show that for A-weighted sound level measurements three
apps had mean differences within ± 2dBA of the reference measurements. For
un-weighted sound level measurements three apps had mean differences within the
± 2 dB of the reference measurement. Since national standards and occupational
guidelines specify that type 2 sound measurement instruments have an accuracy
of ± 2dBA, some of the above-mentioned apps could potentially be used in the
occupational setting, especially if they’re used in conjunction with a type 2
external microphone such as the MicW i436.
Android-based
apps lacked the features and functionalities found in iOS apps. This is likely
due to the iOS advanced audio capabilities compared to other platforms, the
open ecosystem of the Android platform, and having so many different Android
device manufacturers using different suppliers and components.
Challenges
remain with using smartphones to collect and document noise exposure data. Some
of the main issues encountered in recent studies relate to privacy and
collection of personal data, sustained motivation to participate in such
studies, bad or corrupted data, and mechanisms for storing and accessing such
data. Most of these issues are being carefully studied and addressed [Drosatos
et al., 2012; Huang et al. 2010].
In
conclusion, smartphone sound apps can serve to empower workers and help them
make educated decisions about their work environments. They may be useful for
industrial hygienists and OS&H managers to make quick spot measurements to
determine if noise levels exist in a workplace that can harm workers’ hearing.
The ubiquity of smartphones and the availability of these sound measurement
apps may also present new research opportunities for occupational hearing
scientists and researchers.
Chucri
A. Kardous, MS, PE and Peter B. Shaw, Ph.D.
CAPT Kardous
is a research engineer in the NIOSH Division of Applied Research and
Technology.
Dr.
Shaw is a statistician in the NIOSH Division of Applied Research and
Technology.
*References
to products, services, or apps do not constitute an endorsement by NIOSH or the
U.S. government.
References
Drosatos,
G., Efraimidis, P. S., Athanasiadis, I. N., D’Hondt, E., & Stevens, M.
[2012]. A privacy-preserving cloud computing system for creating participatory
noise maps. In Computer Software and Applications Conference (COMPSAC), 2012
IEEE 36th Annual (pp. 581-586). IEEE.
Huang,
K. L., Kanhere, S. S., & Hu, W. [2010]. Are you contributing trustworthy
data? the case for a reputation system in participatory sensing. In Proceedings
of the 13th ACM international conference on Modeling, analysis, and simulation
of wireless and mobile systems (pp. 14-22). ACM.
Kardous,
C. A., & Shaw, P. B. (2014). Evaluation of smartphone sound measurement
applications. The Journal of the Acoustical Society of America, 135(4), EL186-EL192.
Maisonneuve
N., Matthias N. [2010]. Participatory noise pollution monitoring using mobile
phones. Information Polity, 51-71.
Nielsen
[2013]. Mobile Majority: U.S. Smartphone ownership tops 60%. Retrieved June 23,
2013, from http://www.nielsen.com/us/en/newswire/2013/mobile-majority–u-s–smartphone-ownership-tops-60-.html
Williams
W. and Sukara Z. [2013]. Simplified noise labelling for plant or equipment used
in workplaces. Journal of Health and Safety, Research and Practice, Vol. 5 (2),
18-22.