InteLiv: An Architecture for Graph-Based Dynamic Context Modeling for Smart Living

Advancements in the Internet of Things (IoT) applied by automation systems lead to an increasing and flexible interconnection of various devices and the generation of voluminous data. In the domain of home automation for instance, having a multitude of interconnected data leveraged to knowledge could enhance user-centeredness and energy efficiency, among other use cases. However, the data as well as data sources are dynamic and heterogeneous, posing a great challenge to unfold their full capabilities. Thus, a unifying and correspondingly dynamic architecture is needed for supporting the flexibility and extensibility of such systems and data sources. In this paper, we present the concept and implementation of a context-aware INTElligent LIVing (inteLiv) architecture. Consisting of a data layer, a context layer and a service layer, the architecture abstracts the heterogeneous data of the linked devices via a middleware. The resulting system enables the collection of data across networked heterogeneous devices and models the collected data by using a unified dynamic context model. A hybrid approach was chosen for the designed context model: A combination of an ontology-based and property graph-based model represent a core aspect of this work as opposed to common static ontological representations and pre-defined context-based use cases. In the following contribution, the inteLiv ontology is first defined to describe the concepts of the intelligent living system. Based on the modeled context, reasoning algorithms also enable the derivation of new context information. The context is stored as a knowledge graph and can be used for context-aware applications, which can be designed during runtime. Furthermore, a user interaction with the system is possible via a web interface.