Moving object modelling approach for lowering uncertainty in location tracking systems

Authors:
Wegdan Abdelsalam;David Chiu;Siu-Cheung Chau;Yasser Ebrahim;Maher Ahmed
Affiliations:
School of Computer Science, University of Guelph;School of Computer Science, University of Guelph;Physics & Computer Science Department, Wilfrid Laurier University;Physics & Computer Science Department, Wilfrid Laurier University;Physics & Computer Science Department, Wilfrid Laurier University
Venue:
Canadian AI'11 Proceedings of the 24th Canadian conference on Advances in artificial intelligence
Year:
2011

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Abstract

This paper introduces the concept of Moving Object (MO) modelling as a means of managing the uncertainty in the location tracking of human moving objects travelling on a network. For previous movements of the MOs, the uncertainty stems from the discrete nature of location tracking systems, where gaps are created among the location reports. Future locations of MOs are, by definition, uncertain. The objective is to maximize the estimation accuracy while minimizing the operating costs.