A Framework of ifcJSON-Based Digital Twin Platform for Monitoring Building Environment Using BIM, IoT, and Semantic Web Technologies

Over the past two decades, Building Information Modeling (BIM) has evolved into a multidisciplinary data repository in the Architecture, Engineering, and Construction sectors. This high-fidelity repository, compiled during the design, engineering, and construction phases, has significant potential for reuse in subsequent operation and maintenance phases; however, its static nature of the information is rarely utilized for facility management purposes. To address this issue, recent research works have focused on integrating BIM with Internet of Things (IoT) sensors to facilitate real-time updates of environmental or facility-related information for digital twin paradigm. Nevertheless, these systems encounter several challenges: 1) insufficient consideration of data transmission efficiency between sensors and servers, 2) inefficient data serialization of BIM models in web environments, and 3) limited interoperability with other systems in different domains. In response to these technical barriers, this paper proposes a framework for a generalizable web-based building monitoring system by integrating BIM, IoT, and semantic web technologies. The framework is composed of four layers: sensor layer, network layer, middleware layer, and application layer. To enhance semantic representation and data processing efficiency, we suggest converting BIM models from ifcSPF to a linked data version of ifcJSON. As a preliminary study, we develop a prototype of the web platform based on the proposed framework and conduct a pilot-test in a university laboratory. The results demonstrate that the ifcJSON-based linked data effectively federates building information with IoT sensor data and ontologies, such as Brick ontology and ifcOWL. This outcome can serve as a foundation for developing a scalable building monitoring system utilizing BIM, IoT, and semantic web technologies.