A Datalog Model for Context Reasoning in Pervasive Environments

Abstract

Context is considered by research community in pervasive computing, and particularly in context awareness, to be subject to the available environmental sensors to retrieve the suitable information to the user. For example, the users context is based on location information or even based on other deterministic information, such as time (morning, evening, 11:00 am, etc.). The challenge is to also consider the user as a parameter influencing the context in addition to environmental information collected by sensors. This implies that human factors should be highly considered in order to formalize the ldquouser profilerdquo as an input to context awareness (context reasoning) and also as an output to the context adaptation. This vision, which we have adopted in this paper, implied to investigate both, the user actions acting in his or her living environment (Human behavior, preferences, etc.), and the context reasoning sensitive to human factors.