Benchmarking Results of Semantic Reasoners Applied to an Ambient Assisted Living Environment


Ambient Assisted Living (AAL) environments and applications have been receiving a great amount of interest in recent years. The main reason of this interest is the increasing lifetime of elderly people. Our goal is to determine and clarify which combination of semantic reasoners and frameworks is the most suitable for building knowledge-driven smart environments. In particular, we are interested in the combination which provides a better computational performance and reasonable memory requirements. The obtained results show that the fastest choice under the employed dataset is to use the OWL API accessing the Pellet reasoner. On the other hand, the less memory consumption experiment is provided by a combination of HermiT and custom Java rules.