Weight factor algorithms for activity recognition in lattice-based sensor fusion

Authors:
Jing Liao;Yaxin Bi;Chris Nugent
Affiliations:
Computer Science Research Institute, School of Computing & Mathematics, University of Ulster, Jordanstown, Northern Ireland, UK;Computer Science Research Institute, School of Computing & Mathematics, University of Ulster, Jordanstown, Northern Ireland, UK;Computer Science Research Institute, School of Computing & Mathematics, University of Ulster, Jordanstown, Northern Ireland, UK
Venue:
KSEM'11 Proceedings of the 5th international conference on Knowledge Science, Engineering and Management
Year:
2011

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Abstract

Weighting connections between different layers within a lattice structure is an important issue in the process of modeling activity recognition within smart environments. Weights not only play an important role in propagating the relational strengths between layers in the structure, they can be capable of aggregating uncertainty derived from sensors along with the sensor context into the overall process of activity recognition. In this paper we present two weight factor algorithms and experimental evaluation. According to the experimental results, the proposed weight factor methods have a better performance of reasoning the complex and simple activity than other methods.