Rapid prototyping of semantic applications in smart spaces with a visual rule language

Abstract

One of the major limitations of Ambient Intelligent systems today is the lack of semantic models in human behavior and the environment, so that the system can recognize the specific activity being performed by the users and act accordingly. In this context, we address the general problem of knowledge representation in Smart Spaces. In order to monitor and act over human behavior in intelligent environments, we design a sufficiently simple and flexible visual language to be managed by non-expert users, thus facilitating the programming of the environment. The prototype of the visual language serves to represent rules about human behavior to provide the Smart Space with more usability. These rules can be mapped into SPARQL queries and rule subscriptions. In addition, we add support to represent imprecise and fuzzy knowledge. The proposed general-domain language can help managing resource allocation, assisting people with special needs, in remote monitoring and other domains.