Evaluating the Accuracy of Android Applications in Monitoring Environmental Noise Levels

Area of Science:

• Occupational Health and Safety
• Acoustics and Noise Measurement
• Mobile Technology Applications

Background:

• Environmental noise assessment is crucial for occupational health.
• Traditional noise measurement devices can be expensive.
• Smartphone applications offer a potentially accessible alternative for noise monitoring.

Purpose of the Study:

• To evaluate the accuracy of free Android applications for measuring environmental noise levels.
• To assess the suitability of these apps for occupational health assessments.
• To compare app performance against a calibrated professional sound level meter.

Main Methods:

• Tested the top 10 free, highly-rated Android noise measurement apps on a Samsung Galaxy A54 smartphone.
• Used pure tones at 100 Hz, 2000 Hz, and 4000 Hz across noise levels of 25 dB, 40 dB, and 85 dB.
• Compared app measurements to a calibrated Precision Gold N09AQ environment meter in a controlled setting, analyzing data with linear regression (R² values).

Main Results:

• The calibrated control meter achieved the highest accuracy (R² = 0.99).
• Two apps, SPL Meter dB and Sound Meter (KTW apps), and Sound Meter (Pony AI Inc.), demonstrated strong performance (R² = 0.98).
• App accuracy decreased at higher noise levels (85 dB), with Sound Meter (ABC Apps) showing the lowest accuracy (R² = 0.85). User ratings did not consistently predict performance.

Conclusions:

• Certain Android applications show promise as cost-effective tools for noise level measurement, particularly at lower decibel ranges.
• Limitations include reduced accuracy at higher noise levels and the absence of A-weighting, which is necessary for regulatory compliance in professional settings.
• Further research and real-world validation are required to enhance the utility of these apps for occupational health applications.