1. Chucri (Chuck) A. Kardous, M.S., P.E. Peter B. Shaw, Ph.D. William J. Murphy, Ph.D. U.S. Department of Health and Human Services Centers for Disease Control and Prevention National Institute for Occupational Safety and Health Cincinnati, Ohio Evaluation of Smartphone Sound Measurement Applications using External Microphones – A Follow-up Study 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

2. Background  22 million people exposed to hazardous noise in excess of 85 dB(A) each year (NIOSH)  360 million have disabling hearing loss (WHO)  2 billion smartphones  Hundreds of sound measurement apps available  NIOSH tested 192 iOS and Android apps, only 10 met selection criteria  4 apps of the 10 met measurement criteria (within ± 2 dB of reference type 1 system/sound level meter)

3. Results of original study  NIOSH tested 192 iOS and Android apps, only 10 met selection criteria  4 iOS apps of the 10 met measurement criteria  Mean difference between smartphone measurements and reference were within ± 2 dB  SoundMeter, SPLnFFT, SPL Pro, NoiSee  After introduction of iOS6, Apple allowed developers to bypass speech filter and input gain control  Built-in MEMS microphone is the main weakness

4. Android Apps/Devices  Open ecosystem, many manufacturers, many suppliers  Same app not consistent across different devices (different manufacturers)  Different apps not consistent on same device (developers access to different devices)  As a result, no quantitative comparisons were possible  Android users 'expectations for free/low priced apps and Android developers’ expectations for lower revenues continue to hinder quality of apps

5. Sound Measurement Apps  Four iOS apps from previous study  NoiSee (EA LAB)  SoundMeter (Faber Acoustical)  SPLnFFT (Fabien Lefebvre)  SPL Pro (Studio Six Digital)  Two external Microphones  i436 (MicW)  iMM-6 (Dayton Audio)

6. External Microphones  MicW-i436 (~$150)  “complies with IEC 61672 Class 2 sound level standard.”  Omnidirectional Electret Condenser  Frequency Response: 20 Hz – 20 kHz  Sensitivity: 6.3 mV/Pa  S/N > 62dB  Max SPL: 128 dB  Dayton Audio iMM-6 (~$15)  Omnidirectional Electret Condenser  Frequency Response 18 Hz – 20 kHz  Sensitivity: 10 mv/Pa  S/N: 70 dB  Max SPL: 127 dB

7. Reverberant Noise Chamber

8. Smartphones Setup

9. Smartphones and Reference Mic Reference microphone

10. Calibration

11. Statistical Design  Difference between noise levels measured reference microphone and apps  Determine effect of app and sound level on outcome  Analysis of Variance (ANOVA) on differences between apps and reference Small difference = Good agreement Large difference = Poor agreement Difference of zero = Perfect agreement

12. Test Criteria  IEC 61672 – 1 and ANSI S1.4 for Sound Level Meters Specify a host of acoustical and electrical tests  This study examines one aspect, from ANSI S1.4: “ the expected total allowable error for 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”  Test not representative of the intended purpose for the general use of sound level meter

13. Results

16. Main findings  Improved accuracy and precision, most apps produced readings between ±1-2 dB of reference  No significant difference between external microphones  MicW i436 better constructed (metal vs. plastic for iMM-6), better fit w/ Acoustical Calibrator  Users need to balance between price and performance  Other apps (both iOS and Android) should perform better w/ external, calibrated, microphones

17. Discussion  Calibration is key to accurate measurements  Acoustical calibrators are expensive, not readily available  Developers are including pre-defined profiles for external microphones into their apps  Sensitivity of external mics varies b/t manufacturers and b/t same model of mics, so without access to a calibrator, entering correct sensitivity values are key to accurate measurements

18. Future Impact  Adoption of more smartphones = A noise meter in every pocket  Constant connectivity, GIS features, Interactivity w/user offer distinct advantages  Better worksite management and occupational safety and health staff involvement  Residents’ and citizens’ awareness of noise pollution leads to better involvement of city planners and regulators.  Buying and using quieter equipment

19. Challenges Many challenges remain:  Privacy issues relating to users sharing noise data  Dealing with bad or corrupted data  Mechanisms for accessing and sharing data  Calibration standard  Full compliance with national/international sound level meter standards

20. -Kardous CA, Shaw PB [2014]. Evaluation of smartphone sound measurement applications, J. Acou. Soc. Am., 135 (4). -Report: http://www.cdc.gov/niosh/surveyreports/pdfs/349-12a.pdfhttp://www.cdc.gov/niosh/surveyreports/pdfs/349-12a.pdf -NIOSH science blog: http://blogs.cdc.gov/niosh-science-blog/http://blogs.cdc.gov/niosh-science-blog/ -Follow us for updates on @NIOSHNoise -Email: ckardous@cdc.gov More Information