Discovering Patterns of Behavior in a Smart Home
Dorothy N. Monekosso, P Remagnino
Journal of Digital Information Management, Vol. 7, No. 6, 2009.
DOI: 
Link: http://www.dline.info/fpaper/jdim/v7i6/7.pdf
Abstract:
In this paper, we describe a model-based system for context discovery and behavior analysis of a single occupant inhabiting a smart home. To analyze behavior, we build predictive models of behavior and behavior trends employing probabilistic techniques. Using these models, atypical behavior can be distinguished from typical behavior. Deviations from the norm resulting from failure of equipment as well as those deviations resulting from signifi cant variations atypical of the human inhabitant or small changes in trends are detected. In the context of a smart home, both situations are important and require ether automated or human intervention. The test-bed is a home embedded with sensors that unobtrusively record a variety of environmental conditions and household appliance status. The models of behavior are produced from the sensor observations based on statistical inference.