Urban noise

Abstract

People in urban areas are exposed to high noise levels, leading to an increased number of health issues. A mobile phone application called Auditive, was developed to allow the user to report health history, sound level annoyance, and record sound levels on their mobile phones. This allows for real-time sound level data to be directly correlated with the annoyance response. The data recorded with the auditive app provides opportunities for researchers to find correlations between noise exposure, health, and annoyance. A major concern with mobile phone recorded noise is the accuracy of the absolute sound levels without calibration. This study is focused on calibrating mobile phones to provide more accurate data. Two methods for calibration were considered. Technique one calibrates, using the same correction for each type of phone. MATLAB was used to generate pink noise at different sound levels to test a variety of iPhone models. The correction for each frequency level ranging from 63 Hz to 8000 Hz, was determined. Technique two calibrated individual phones. We tested consistent sounds that allow Auditive users to calibrate their phones. These two different techniques will be compared, to establish the best way to calibrate different mobile phones.