In the implementation of a smart home, activity recognition technology using simple sensors is very important. In this paper, we propose a new activity recognition method based on Bayesian network (BN). The structure of the BN is learned by K2 algorithm and is composed of sensor nodes, activity nodes and time node whose state is quantized with reasonable interval. In the proposed method, the BN has less complexity and provides better activity recognition rate than the previous method.
E. Munguia Tapia, S. S. Intille, and K. Larson, 'Activity recognition in the home setting using simple and ubiquitous sensors,' in Proceedings of PERVASIVE 2004, Vol. LNCS 3001, A. Ferscha and F. Mattern, Eds. Berlin Heidelberg: Springer-Verlag, 2004, pp. 158-175
Anand Ranganathan and Roy H. Campbell, 'A Middleware for Context-Aware Agents in Ubiquitous Computing Environments,' In ACM/IFIP/USENIX International Middleware Conference, 2003, Rio de Janeiro, Brazil, June 16-20, 2003
J. Anhalt, A. Smailagic, Daniel P. Siewiorek, F Gemperle, D. Salber, S. Weber, J. Beck, and J. Jennings, 'Toward Context-Aware Computing: Experiences and Lessons,' IEEE Intelligent Systems, Vol. 16, no. 3, pp. 38-46, May/Jun, 2001
Panu Korpipaa, Miika Koskinen, Johannes Peltola, Satu-Marja Makela and Tapio Seppanen, 'Bayesian approach to sensor-based context awareness,' Personal and Ubiquitous Computing pp. 113-124, July 2003