A Comparison of Trajectory Compression Algorithms Over AIS Data

Today’s industry is flooded with tracking data originating from vessels across the globe that transmit their position at frequent intervals. These voluminous and high-speed streams of has led researchers to develop novel ways compress them in order speed-up processing without losing valuable information. To this end, several algorithms have been developed try vessel compromising spatio-temporal kinematic features. In paper, we present a wide range well-known trajectory compression evaluate performance on trajectories. Trajectory included research are suitable for either historical (offline compression) or real-time (online compression). The evaluation three-fold each algorithm evaluated terms ratio, execution speed information loss. Experiments demonstrated its own benefits limitations choice application-dependent. Finally, considering all assessed aspects, Dead-Reckoning not only presented best performance, but it also works over streaming data, which constitutes an important criterion maritime surveillance.