Monitoring and Modeling Simple Everyday Activities of the Elderly at Home

We present our work on a sensor-based smart system automatically trained to recognize the activities of individuals in their home. In this paper we present and analyze a method for recognizing the indoor everyday activities of a monitored individual. This method is based on the data mining technique of association rules and Allen\´s temporal relations. Our experimental results show that for many (but not all) activities, this method produces a recognition accuracy of nearly 100%, in contrast to other methods based on data mining classifiers. The proposed method is accurate, very flexible and adaptable to a dynamic environment such as the "Smart Home" and we believe that it deserves further attention.