Automatic construction and multi-level visualization of semantic trajectories

With the prevalence of GPS-embedded mobile devices, enormous amounts of mobility data are being collected in the form of trajectory - a stream of (x,y,t) points. Such trajectories are of heterogeneous entities - vehicles, people, animals, parcels etc. Most applications primarily analyze raw trajectory data and extract geometric patterns. Real-life applications however, need a far more comprehensive, semantic representation of trajectories. This paper demonstrates the automatic construction and visualization capabilities of SeMiTri - a system we built that exploits 3rd party information sources containing geographic information, to semantically enrich trajectories. The construction stack encapsulates several spatio-temporal data integration and mining techniques to automatically compute and annotate all meaningful parts of heterogeneous trajectories. The visualization e exhibits different levels of data abstraction, from low-level raw trajectories (i.e. the initial GPS trace) to highl...

• Type: Journal
• Year: 2010
• Where: GIS
• Authors: Zhixian Yan, Lazar Spremic, Dipanjan Chakraborty, Christine Parent, Stefano Spaccapietra, Karl Aberer
• Keywords: Automated Reasoning, GIS 2010, Raw Trajectory Data, Trajectories, Trajectory