Using GPS-enabled mobile phones to characterize activity patterns for air pollution epidemiological studies

Wednesday Sep 28   05:00 PM to 07:00 PM (2 hours)
GPSTime-Activity PatternsMicroEnvironment ClassificationResamplingAir Pollution Exposure
We assessed the potential of global positioning system (GPS)-equipped mobile phones for health-related studies, particularly, as a means of collecting individuals’ mobility required for personal exposure assessments. The widespread use of mobile phones has enabled investigators to conduct exposure studies in larger populations on an individual level over longer period with low cost. However, significant uncertainties associated with the processing and classifying raw GPS data are present. To address these issues, we proposed two algorithms, namely selective resampler and MEclassifier, for pre-processing and contextualizing of raw GPS data. The application of both algorithms to real-world data demonstrated how the challenges with GPS data processing and automated activity classification algorithm were handled.
University at Buffalo, State University of New York
associate professor

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