Correcting Air-Pressure Data Collected by MEMS Sensors in Smartphones

We present a novel correction method for air-pressure data collected by microelectromechanical pressure sensors embedded in android-based smartphones,in order to render them usable as meteorological data. the first step of the proposed correction method involves removing the mechanically derived outliers existing beyond the physical limits and those existing outside 3σ,as well as a reduction to the mean sea level pressure using the altitude data from digital elevation models. the second correction step involves classifying data by location and linear-regression analysis utilizing the temperature and humidity sensed by the smartphone to reduce correction errors by performing the analysis according to personalized settings. air-pressure data obtained from smartphones is subject to several influential factors,depending on the users' external environment. however,once corrected for spatial location,temperature,and humidity and for individual users after a comprehensive quality control,the corrected air-pressure data was highly reliable as an auxiliary resource for automatic weather stations. © 2015 na-young kim et al.