Towards intelligent systems for ubiquitous computing: Tacit knowledge-inspired ubicomp

Abstract

This work attempts to contribute to shortening the gap between the original conception of ubicomp and the current state of the art. Thus, the original concept has been analyzed to identify one of the main advances required to achieve this. Authors consider that context-awareness is the key element to accomplish this goal and compare the context-aware system architectures to humans’ body parts, activities, and processes. Later they argue that, since context-aware systems are heavily influenced by humans context-awareness, it should implement techniques inspired by the human thinking process. Then, the concept of knowledge is reviewed altogether with a model of the human thinking process. Consequently, they propose the tacit context-modeling and the tacit context-reasoning techniques based on that model. Later, granular computing theory is proposed to implement the tacit context modeling technique, with which we propose the particular granular computing, the preconcept granular computing, and the concept granular computing. The authors conclude that the approach presented could help improve context-aware systems’ performance since it takes inspiration on how they perceive the only perfect machine ever created works, the brain.