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

The Internet of Things (IoT) rapidly expands into every aspect of our lives, which requires customization for each application scenario. However, integrating these context-specific requirements is a complex and labor-intensive process requiring specialized knowledge and is prone to errors due to manual interactions. This presents a significant challenge for the entire software development process. Consequently, new solutions are demanded to facilitate the anticipated growth of IoT.

Peraic, Martin Hrvoje, 2023

Art der Arbeit Master Thesis
Auftraggebende
Betreuende Dozierende Laurenzi, Emanuele
Keywords
Views: 4 - Downloads: 0
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.
The primary contribution of this research lies in conceptualizing and formalizing the requirements of Feature Models and the scenario. This involves the development of a methodology that aligns these requirements with the PIM stage of the FloWare framework, implemented within AOAME. This alignment ensures that the specific context and the broader set of standards that need to be considered for systems and devices within an operation room are available during PSM design. Subsequently, the generated artifact is implemented and evaluated in AOAME based on the AOAME4FloWare proposal.
The research adopts the Design Science Research methodology, adjusted for developing the artifact. Furthermore, this thesis outlines potential future research directions. These include the exploration of further IoT domains or applying SHACL to validate the abstract syntax of the feature models and automating the newly introduced manual steps.
Studiengang: Business Information Systems (Master)
Vertraulichkeit: öffentlich
Art der Arbeit
Master Thesis
Autorinnen und Autoren
Peraic, Martin Hrvoje
Betreuende Dozierende
Laurenzi, Emanuele
Publikationsjahr
2023
Sprache der Arbeit
Englisch
Vertraulichkeit
öffentlich
Studiengang
Business Information Systems (Master)
Standort Studiengang
Olten