Indoor environmental quality (IEQ) affects occupants’ satisfaction, health, productivity, comfort, and well-being. IoT developments enable better monitoring of IEQ parameters; however, integrating the various types of heterogeneous data from both the IoT and BIM domains is cumbersome and capital intensive, and therefore, limits the potential of smart buildings. Semantic web technologies can reduce heterogeneity issues, which is necessary to facilitate complex IEQ models. An ontology integrating data related to a building’s topology and its static and dynamic properties is still lacking. The outline of this research is twofold. First, a systematic literature review was conducted to find state-of-the-art semantic web technologies related to building topology, static properties, and dynamic properties from the IoT and BIM domains. By graphically reviewing various ontologies, their valuable patterns, commonalities, and best practices were revealed. Secondly, those results were used to develop a new ontology that integrates topological building information with static and dynamic properties. This Building Performance Ontology (BOP) provides a generic upper-level description of properties and two lower-level ontologies representing observations and actuation. The ontology results in intuitive queries and is both horizontally and vertically extensible. Multiple levels of detail are introduced to ensure practical applicability and efficient patterns based on the data modeler’s needs. BOP opens up a new range of research opportunities in the IEQ domain.

Smart office concepts are gaining increasing attention in the built environment domain, as they promise efficient and effective workplaces that cater to user needs. While previous researchers have primarily focused on Internet of Things (IoT) technologies in the office environment and their impacts on office users, few studies have addressed the users’ preferences of smart office concepts. This study aims to fill this gap by investigating users’ preferences for four smart features: smart parking, smart workspace booking, smart temperature control and smart lighting, and exploring how different attributes of these smart features influence users’ preferences. The study conducted a stated choice experiment with 137 valid respondents and analysed the data using both Multinomial Logit (MNL) models and Latent Class (LC) models. The MNL model results indicate that users have varying preferences for different smart features and that there are significant interactive impacts between attribute levels and age, gender, working hours per week and attitudes towards technologies, highlighting the heterogeneity in users’ preferences. The LC model revealed two distinct user classes for each smart feature, which have significantly improved the overall model performance. This study guides the design and implementation of smart office concepts that cater to users’ needs and preferences.

Interconnecting building information on multiple scales and lifecycle stages enables designers to improve their decision-making and tackle ecological, societal, and economical challenges. However, this information is often generated in different software tools, saved in different file formats, using a stakeholder’s own domain language, and is stored in decentral storage locations. This paper presents a tool that integrates data from different stakeholders into a single viewpoint. The tool – LBDviz – combines a browser-based IFC viewer and semantic web technologies to combine geometry with other data that falls outside the scope of the IFC schema. The tool is tested in multiple case studies. These case studies range from requirement checking during the design phase, generating design feedback during the operational phase, and maintaining building performance in a sustainable and economically viable manner. The results of these studies can be reused in future designs, stimulating a more circular design process. The method used in LBDviz enables the interconnection of data within and without the architectural design domain and reduces data interoperability challenges in many lifecycle phases of a construction project.