Research Article
Mining Emerging Patterns for recognizing activities of multiple users in pervasive computing
@INPROCEEDINGS{10.4108/ICST.MOBIQUITOUS2009.7013, author={Tao Zhu and Zhanqing Wu and Liang Wang and Xianping Tao and Jian Lu}, title={Mining Emerging Patterns for recognizing activities of multiple users in pervasive computing}, proceedings={6th Annual International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services}, publisher={IEEE}, proceedings_a={MOBIQUITOUS}, year={2009}, month={11}, keywords={Acoustic noise Acoustic sensors Computer science Feedback loop Humans Laboratories Mathematics Pattern recognition Pervasive computing Testing}, doi={10.4108/ICST.MOBIQUITOUS2009.7013} }- Tao Zhu
Zhanqing Wu
Liang Wang
Xianping Tao
Jian Lu
Year: 2009
Mining Emerging Patterns for recognizing activities of multiple users in pervasive computing
MOBIQUITOUS
IEEE
DOI: 10.4108/ICST.MOBIQUITOUS2009.7013
Abstract
Understanding and recognizing human activities from sensor readings is an important task in pervasive computing. In this paper, we investigate the fundamental problem of recognizing activities for multiple users from sensor readings in a home environment, and propose a novel pattern mining approach to recognize both single-user and multi-user activities in a unified solution. We exploit Emerging Pattern - a type of knowledge pattern that describes significant changes between classes of data - for constructing our activity models, and propose an Emerging Pattern based Multi-user Activity Recognizer (epMAR) to recognize both single-user and multi-user activities.
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