An Online Compression Algorithm for Positioning Data Acquisition

Pan Wei, Yao Chunlong, Li Xu, Shen Lan


Positioning data are usually acquired periodically and uploaded to the server via wireless network in
the location data acquisition systems. Huge communication overheads between the terminal and the
server and heavy loads of storage space are needed when a large number of data points are uploaded.
To this end, an online compression algorithm for positioning data acquisition is proposed, which
compresses data by reducing the number of uploaded positioning points. Error threshold can be set
according to users' needs. Feature points are extracted to upload real-timely by considering the
changes of direction and speed. If necessary, an approximation trajectory can be obtained by using the
proposed recovery algorithm based on the feature points on the server. Positioning data in three
different travel modes, including walk, non-walk and mixed mode, are acquired to validate the efficiency
of the algorithm. The experimental results show that the proposed algorithm can get appropriate
compression rate in various road conditions and travel modes, and has better adaptability.

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