Probabilistic model to predict movement pattern in geospatial data

The task of trying to determine the movement pattern of objects based on available databases is a daunting one. Tracking the movement of these dynamic objects is important in different areas to understand the higher order patterns of movement that carry special meaning for a target application. However this is still a largely unsolved problem and recent work has focused on the relationships of moving point objects with stationary objects or landmarks on a map. Global Position System (GPS) is a widely used satellite-based navigation system. Popular use of these devices has produced large collections of data, some of which have been archived. These archived data sets and sometimes real time GPS data are now readily available over the internet and their analysis through computational methods can generate meaningful insights. These insights when applied appropriately can be used in everyday life. The purpose of this paper is to propose a probabilistic framework, which determines the probability of a new routing pattern using previous patterns.