Semantic trajectory analysis for identifying locations of interest of moving objects
Anurag Nishad, Sajimon Abraham · 2017
The upsurge in the use of Context Aware Devices in various gadgets has led to the generation of massive mobility data. These gadgets tracks and records particulars of moving objects such as location, time, waypoints etc. in to various geographical databases. The data are recorded in the form of trajectories. Identification of the moving pattern is very much useful for setting up of the architectural platform of transportation systems, design of supply chain networks, preparation of travel itinerary of tourists and the like. In order to understand the characteristic features of the journey made by objects, appropriate mining techniques are essential. Many of the existing trajectory mining applications use geographic features precisely location and time for the pattern identification. Mining of data by considering more parameters will identify divergent locations of interest in the trajectory. The concept of semantic trajectory analysis is gaining acceptance in the domain of trajectory analysis. In this paper we are introducing a conceptual model for the identification of interesting locations on the basis of spatio temporal attributes of moving objects and its semantic features. This model considers direction of the movement of the object as semantic mean for the identification of interesting locations.