Discovery of Gathering Patterns of Moving Objects
Ravi Raj Gupta, T. Ramakrishnudu
Journal of Data Processing, Vol. 5, No. 2, 2015.
DOI: 
Link: http://www.dline.info/jdp/fulltext/v5n2/v5n2_1.pdf
Abstract:
The increasing pervasiveness of location-acquisition technologies has embedded collection of huge amount of trajectories for almost any kind of moving objects. Discovering useful patterns from their movement behaviors can convey
valuable knowledge to a variety of critical applications. In this light we propose a concept, called gathering, which is a trajectory pattern modeling various group incidents such as celebrations, parades, protests, traffic jams and so on. In this work, we first develop a set of techniques to tackle the challenge of efficient discovery of gathering patterns on archived
trajectory dataset. For finding gathering firstly we have to find snapshot cluster, crowd and then super crowd. After getting super crowd, gathering can be identified. Here we proposed an efficient algorithm for finding super crowd if cluster database is given and algorithm for identify gathering after identifying the super crowd. Afterwards, since trajectory databases are
inherently dynamic in many real-world scenarios such as traffic monitoring, fleet management and battlefield surveillance, we further propose discovery solution by applying a series of optimization schemes to handle the incremental data.