Dynamical cognitive services for ambient intelligence environments

Ambient Intelligence systems are more than a simple integration among computer technologies, indeed, their design can strongly depend upon psychology and social sciences aspects describing, analyzing and forecasting the human being status during the system's decision making. Consequently, if from a technological view an AmI system can be considered as a simple framework for distributing personalized services, from a computational point of view, an AmI system is a distributed cognitive framework composed by a collection of intelligent entities capable of modifying their behaviours by taking into account the user's cognitive status in a given time. This paper introduces a novel methodology of AmI systems' design that exploits a service-oriented paradigm and a novel extension of Fuzzy Cognitive Maps theory benefiting on the theory of Timed Automata in order to create a collection of dynamical intelligent agents that use cognitive computing to define advanced services able to maximize environmental parameters as, for instance, user's comfort or energy saving. As will be shown in experimental results, the proposed approach maximize the system's usability in terms of efficiency, accuracy, recall and emotional response.