Abstract
There has been a significant increase in the amount of available trajectory data due to the widespread use of mobile devices equipped with the global positioning system. The increase in trajectory data, however, comes with problems, such as increased storage costs and difficulty in analyzing the data. These issues can be addressed by using compression methods. In this study, we propose an offline compression method that preserves the features of the trajectory data, such as stay points and trajectory shapes. When users stay at a particular location for a certain period, such as waiting at traffic lights or bus stops, the recorded positioning points are redundant. The proposed method compresses the trajectory data using the stay point information. We evaluated the performance of the proposed method using experimental results and a trajectory dataset.
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Acknowledgment
This work was supported by JSPS KAKENHI Grant Number JP19K20418 and Grant for Promotion of OUS Research Project (OUS-RP-20-3).
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Iiyama, S., Oda, T., Hirota, M. (2022). An Algorithm for GPS Trajectory Compression Preserving Stay Points. In: Barolli, L., Kulla, E., Ikeda, M. (eds) Advances in Internet, Data & Web Technologies. EIDWT 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 118. Springer, Cham. https://doi.org/10.1007/978-3-030-95903-6_12
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DOI: https://doi.org/10.1007/978-3-030-95903-6_12
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