With the emergence of ubiquitous data mining and recent advances in mobile communications, there is a need for visualization techniques to enhance the user-interactions, real-time decision making and comprehension of the results of mining algorithms. In this paper we propose a novel architecture for situation-aware adaptive visualization that applies intelligent visualization techniques to data stream mining of sensory data. The proposed architecture incorporates fuzzy logic principles for modeling and reasoning about context/situations and performs gradual adaptation of data mining and visualization parameters according to the occurring situations. A prototype of the architecture is implemented and described in the paper through a real-world scenario in the area of healthcare monitoring