Chucri (Chuck) A. Kardous, M.S., P.E.Peter B. Shaw, Ph.D.
U.S. Department of Health and Human ServicesCenters for Disease Control and Prevention
National Institute for Occupational Safety and HealthCincinnati, Ohio
Evaluation of Smartphone Sound Measurement Apps
Disclaimer: The findings and conclusions in this study are those of the authors and do not necessarily represent the views of the National Institute for Occupational Safety and Health
Background Smartphone penetration expected to hit 2 billion in 2015
64% of all mobile phones purchased in U.S. were smartphones > 140 million users
Apple iOS and Google Android platforms account for 93% of smartphones purchased in 2013
Hundreds of sound measurement apps available
Most are free: Either ad-supported or limited features, fee to upgrade to full features. Typical cost ~ $0.99-$3.99 though some sophisticated apps cost more
Crowdsourcing environmental noise! (NoiseWatch www.eyeonearth.org) Real-time data collection and sharing using GPS!
Crowdsourcing environmental noise! (NoiseTube www.noisetube.net) The NoiseTube mobile app extends the current usage of mobile phones by turning them into noise sensors, enabling citizens to measure the sound exposure in their everyday environment. Furthermore each user can participate in creating a collective map of noise pollution by sharing geo-localized measurement data with the NoiseTube community.
Why NIOSH? NIOSH Science Blog on noise at 2012 Super Bowl:
Tweet noise levels!
Requests about accuracy and recommendations
Can they be used in an occupational setting?
NIOSH initiatives: Worker Empowerment and Direct Reading Instruments
Study Considerations Limited number of devices acquired
To calibrate or not calibrate?
Smartphone built-in mics
Standards and occupational guidelines for type 2 sound measurement instruments
App and device selection criteria
Device/App selection Representative selection of devices: 4 different iOS
models, 4 Android models, 2 Windows models
Selection Criteria:- A-weighted & unweighted (C/Z/flat) sound pressure levels- 3-dB and 5-dB exchange rates- Average/equivalent sound level or time-weighted average (Leq/Lavg or TWA)- Calibration adjustment
10 iOS apps (out of 130) and 4 Android apps (out of 62)
2 cross-platforms apps selected
Experimental Setup iOS apps selected and tested
App Developer Features
Adv Decibel Meter Amanda Gates A/C/SPL weighting, Int/Ext Mic, Calibration
Decibel Meter Pro Performance Audio A/C/Z weighting, Calibration
iSPL Pro Colours Lab A/C/SPL weighting, Calibration
Noise Hunter Inter.net2day A/C/SPL weighting, Int/Ext Mic, Calibration
NoiSee IMS Merlini Sistemi A/C/Z weighting, ISO/OSHA Dose, Calibration
Sound Level Meter Mint Muse A/C/SPL weighting, Calibration
SoundMeter Faber Acoustical A/C/SPL weighting, Leq, Int/Ext Mic, Calibration
(Real) SPL Meter BahnTech A/C/SPL weighting, Calibration
SPL Pro Andrew Smith A/C/SPL weighting, Leq, Int/Ext Mic, Calibration
SPLnFFT Fabien Lefebvre A/C/SPL weighting, Leq, Int/Ext Mic, Calibration
Experimental Setup Android apps selected and tested
Two cross-platforms apps NoiseWatch and NoiseTube(non-commercial apps) available on both iOS and Android
App Developer Features
SPL Meter AudioControl A/C weighting, Int/Ext Mic, Calibration
decibel Pro BSB Mobile Solutions A/C/Z weighting, Calibration
db Sound Meter Darren Gates Int/Ext Mic, Calibration
Noise Meter JINASYS A/SPL weighting, Calibration
Experimental Setup Reverberant noise chamber diffuse sound field
Pink noise 65-95 dB (20Hz -20kHz) in 5-dB increments
Reference sound level: Larson-Davis model 2259 random incidence microphone
Noise generation and acquisition: Trident Software by ViAcoustics
Larson-Davis model 831 sound level meter (type 1) and model 706 noise dosimeter (type 2)
Reverberant Noise Chamber
Smartphones and Reference Mic
Reference microphone
Smartphones and SLM/Dosimeter
Statistical Design Difference between noise levels measured reference
microphone and apps
Determine effect of app, device, and noise level on outcome
Analysis of Variance (ANOVA) on differences between apps and reference in A-weighted and unweighted sound levels
Small difference = Good agreementLarge difference = Poor agreementDifference of zero = Perfect agreement
Results
A-weighted sound levels by app
Results
Unweighted sound levels by app
Results
A-weighted sound levels by device
Results
Unweighted sound levels by device
Results
Unweighted sound levels by Android app
AppSound Level (dB)
Samsung S3 HTC One X
Motorola Droid
Samsung Note
SPL Meter 70 62.5 2.5 72.4 2 73.6 2.5 66.7 1.2
80 83.4 1.8 76.6 1.7 85 3 75.6 1.8
90 91.2 2.2 85.4 1.5 93.6 2.8 92 1.6
deciBel Pro (dBA) 70 69.8 1.5 71 0.8 81 0.6 68.5 1.2
80 76.1 1.5 79 1 84.9 0.8 75.8 1
90 87.2 1.5 85 1.2 82 0.6 86.5 1.5
dB Sound Meter 70 711 80 1.5 66 0.5 69 1
80 781 91 1.3 80 0.7 77 1
90 87 1 92 1.2 93 0.4 86 1
Noise Meter 70 61 0.8 63 1.2 66 0.9 60.6 0.6
80 68.5 1.2 71 1 75.6 0.6 69 1.1
90 77.8 1 80.2 1.4 82.2 1 78.6 1.2
Results
NoiseWatch: cross-platform app
Discussion iOS Apps SoundMeter had best agreement in A-weighted sound
levels (mean difference of -0.52 dBA from reference)
SPLnFFT had best agreement in un-weighted sound levels (mean difference of 0.07 dB from reference)
Noise Hunter, NoiSee, and SoundMeter had mean differences within 2 dBA
NoiSee, SoundMeter, and SPLnFFT had mean differences within 2 dB
Discussion iOS devicesFor Devices
iPhone 3Gs had best agreement with mean difference of 0.44 dB and -0.71 dBA
New microphone supplier for iPhone 5 and iPad 4th gen
iOS 6 allows developers to bypass speech filters and input gain control
Discussion Android Apps/Devices Open ecosystem, many manufacturers, many suppliers
No statistical significance can be established
Same app not consistent across different devices (different manufacturers)
Different apps not consistent on same device (developers access to different devices)
Android users expectations for free or low priced apps
Android developers expectations for lower revenues
Occupational Relevancy ANSI S1.4 (specification for sound level meters) states
the following: the expected total allowable error for a sound level meter measuring steady broadband noise in a reverberant sound field is approximately 1.5 dB for a type 1 instrument and 2.3 dB for a type 2 instrument.
OSHA noise standard [29 CFR 1910.95] considers type 2 instruments to have an accuracy of 2 dBA.
Several apps and devices were within 2 dBA!
Crowdsourcing of Occupational Noise?Many challenges remain:
Accuracy
Privacy
Dealing with bad or corrupted data
Mechanisms for storing and accessing data
Motivation to participate in studies
Calibration standard
Future Research Testing with calibrated devices
Using external microphones MicW i436 (type 2 compliant)
Occupational noise app, freely distributed
Occupational noise exposure database
Contact information
Chuck Kardous
National Institute for Occupational Safety and Health4676 Columbia Parkway, C27
Cincinnati, Ohio 45226513-533-8146
[email protected]
NIOSH science blog: http://blogs.cdc.gov/niosh-science-blog/
Kardous CA, Shaw PB [2014]. Evaluation of smartphone sound measurement applications, J. Acou. Soc. Am., 135 (3).
Source DF ANOVA SS Mean Square F Value Pr > Fblock 5 170.46133 34.09227
noise 6 999.94133 166.65689 139.40
App Mean Standard Error N Tukey GroupingSound Level Meter 3.6083 0.27926 168 A
SPL Pro 2.4863 0.11935 168 B
SoundMeter -0.5185 0.12852 168 C
NoiSee -1.1280 0.25253 168 D
Noise Hunter -1.9280 0.27227 168 E
SPLnFFT -2.2744 0.25715 168 F E
iSPL Pro -2.5792 0.25884 168 F
Adv Decibel Meter -5.0464 0.27668 168 G
Real SPL Meter -13.1327 0.27929 168 H
Decibel Meter pro -13.1708 0.27644 168 H
Multiple pairwise comparisons (Tukey) of the mean differences in dBA for the ten apps
