Context Fusion: Dealing with Sensor Reliability

Context-aware applications sense, combine and reason about contextual information in order to determine and adapt to the current user's context. A very important problem associated with context is the inherent ambiguity and inaccuracy. Contextual information is typically pervaded with imperfect sensing (e.g., noise of sensor readings). A novel context fusion model that represents, determines and reasons about context based on the reliability on sensor readings is proposed. This model adopts dynamic Bayesian networks and fuzzy-set theory in order to deal with the reliability of contextual data at the context inference phase.