Paper Title
Distributed Trends In Mining And Clustering Group Movement Patterns For Tracking Moving Objects

In biological research domain like “Study of animal social behavior” and “Wild life migration” object tracking sensor networks are used. In this application concentrating on finding the group of object with similar movement pattern using distributed mining techniques. But generally WSN concentrating on finding moving patterns of single object or all objects. Tracking moving objects having two phases i.e. mining phase and cluster ensembling phase. In first phase of algorithm we find movement patterns based on local data then we are identifying new term of similarity measure of to computing the similarity of moving objects and find relationship between them. In second phase algorithm combine the local grouping results to derive the group relationship from global view. We hope that the final output shows that the proposed mining algorithm achieves good grouping quality and the mining technique helps reduce the energy consumption by reducing the amount of data to be transmitted.