  The proliferation of low-cost sensors in smartphones has facilitated numerous
applications; however, large-scale deployments often encounter performance
issues. Sensing heterogeneity, which refers to varying data quality due to
factors such as device differences and user behaviors, presents a significant
challenge. In this research, we perform an extensive analysis of 3-axis
accelerometer data from the MyShake system, a global seismic network utilizing
smartphones. We systematically evaluate the quality of approximately 22 million
3-axis acceleration waveforms from over 81 thousand smartphone devices
worldwide, using metrics that represent sampling rate and noise level. We
explore a broad range of factors influencing accelerometer data quality,
including smartphone and accelerometer manufacturers, phone specifications
(release year, RAM, battery), geolocation, and time. Our findings indicate that
multiple factors affect data quality, with accelerometer model and smartphone
specifications being the most critical. Additionally, we examine the influence
of data quality on earthquake parameter estimation and show that removing
low-quality accelerometer data enhances the accuracy of earthquake magnitude
estimation.
