Ontology-based Feature Models for Context-Aware Configurations in IoT Applications

Abstract

To solve the abovementioned problem, this thesis explores merging IoT development with scenario-specific requirements by converging proven knowledge and software engineering approaches. Specifically, the research focuses on integrating graphical Feature Models with contextual knowledge stored in a Domain Ontology to support the development of Platform-Specific Models (PSM) in Model-Driven Engineering (MDE). This research utilizes and extends the Agile and Ontology-based Metamodelling Environment (AOAME) in conjunction with the model-driven FloWare framework to bridge the gap between Platform-Independent Models (PIM) and PSM in the IoT domain of smart buildings. The crucial aspect of this research is the exploration of the requirements for creating a scenario-specific IoT solution. These requirements, which need to be addressed in the Feature Models and the Domain Ontology at the model level, must align the nuances of a specific IoT scenario with the existing features of a PIM. The Brick Schema is adapted for this purpose. It constitutes the foundation for the Domain Ontology around the requirements of the IoT scenario, which is part of the smart building domain and is focused on implementing an operating room in a hospital environment.