Structured context-analysis techniques in biologically inspired ambient-intelligence systems

Abstract—In this paper, techniques and related issues for the def-inition of a contextual knowledge in ambient-intelligence systems are explored. A logical structure for this kind of system, inspired by a neurobiological brain model, is proposed. Through these con-siderations, the role and the importance of context awareness in the definition of an artificial organism showing adaptability, perva-siveness, and scalability features are described. Techniques for the definition of a multilayer context representation are explained and practically demonstrated with a test-bed. In the proposed system, a complex event classification is obtained through the fusion of het-erogeneous data coming from a set of sensors thanks to the design of a self-organizing map (SOM). The SOM represents the core of the system and testing proofs show good results in the classification of the events taking place in the monitored environment. Index Terms—Context awareness, data fusion, self-organizing maps (SOMs), smart spaces. I