A trajectory data compression algorithm based on spatio-temporal characteristics

ABSTRACT:

Background

With the growth of trajectory data, the large amount of data causes a lot of problems with storage, analysis, mining, etc. Most of the traditional trajectory data compression methods are focused on preserving spatial characteristic information and pay little attention to other temporal information on trajectory data, such as speed change points or stop points.

Methods

A data compression algorithm based on the spatio-temporal characteristics (CASC) of the trajectory data is proposed to solve this problem. This algorithm compresses trajectory data by taking the azimuth difference, velocity difference and time interval as parameters in order to preserve spatial-temporal characteristics. Microsoft’s Geolife1.3 data set was used for a compression test to verify the

SUBMITTER: Zhong Y 

PROVIDER: S-EPMC9575842 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature