An Engineering Toolbox to Build Situation Aware Ambient Assisted Living Systems

Due to increasing anticipated average life and health expenditure ambient assisted living (AAL) systems attract the attention of researchers. To successfully build and deploy AAL systems knowledge from different fields of computer science is needed: pervasive computing to gain the raw data, machine learning and pattern recognition to interpret these data and HCI knowledge to allow implicit interaction with the system. In this paper we propose a reference architecture for building AAL systems. Based on this reference architecture we introduce a toolbox that simplifies the development of AAL systems. The toolbox consists of a meta-model for pipeline systems, a low-level context model, high-level context ontologies, customizable components and tool support.