An Evaluation of Ontology-based User Preferences and Profiling System in a Smart Home

In the concept of smart home systems, this study has highlighted a research gap with notable markings to the inadequacies associated with personalizing the static-centric preferences of users in real time. Consequently, the study leverages the intersection of ontology and user preferences on smart home semantics to serve as a knowledge base for a dynamic user preference system. A mixed-method approach was utilized, incorporating the “Noy and McGuinness” model with a case-based method for development. Elaborating on the capabilities of the ontology-based preferencing system with notable markings to scenario-based evaluations, two distinct user scenarios were modelled to demonstrate the user adaptability with regards to preferences in smart space, using the “Smart Space Lab” as a testbed for the study. The evaluation was based on scenarios that featured two user-centric preferences: the lighting state of a smart bedroom and the heating state of a smart kettle device. The outcome of the evaluation compellingly establishes the solution’s capability to accomplish dynamism in user profiles and preferences. The results extend significant ontological impact across varying applications, that include adaptive user interfaces, recommender systems, and smart labs. The findings are with potential advancement in the automation of the smart home industry, paving the way for more user-centric and cohesive interactions within smart spaces. Nonetheless, several challenges were identified in the study, highlighting the need for further research into the evaluation of the developed application for privacy measures that pertain to the refinement of ontological considerations in the deployment of ontology-based systems within smart environments.