Noise Patterns in GPS Trajectories
As any other type of data, GPS traces contain noise, anomaly, and sometimes unexpected values. Normally, researchers and data engineers analysts would start dealing with GPS data by removing those noises and outliers. However, in this work, we take the opposite direction. We focus on analyzing those unexpected values rather than discarding them. Interestingly, we discovered useful findings from an insight look at the noise in GPS trajectories. The intuition behind those discoveries is that when unexpected GPS readings are observed several times around a specific location, we study the nature of that location rather than thrown away those reading. By doing so, we are able to tell the type of area around those readings. For example, we can infer that a driver is passing by a tall building or through a forest based on the pattern of noise in the GPS readings. We are also able to question the quality of the underlying road map. Our findings and discoveries are based on the analysis of real GPS data for the Microsoft shuttles.
2020 21st IEEE International Conference on Mobile Data Management (MDM)
Open Access Status
Hendawi, A., Shen, J., Sabbineni, S. S., Song, Y., Cao, P., Zhang, Z., Krumm, J., & Ali, M. (2020). Noise Patterns in GPS Trajectories. 2020 21st IEEE International Conference on Mobile Data Management (MDM), 178–185. https://doi.org/10.1109/MDM48529.2020.00040