The digital transformation in the built environment is happening. Smart buildings and smart cities are poised to create efficiencies and improve sustainability. The digital twin concept, a digital representation of a real-world entity or system, will help with asset management, improve decision-making processes, and advance sustainability efforts. While this is positive, the architectural, engineering, construction, and operations industry as a whole has been slow to adopt the latest technologies, has experienced product fragmentation, and has had issues with effectively interconnecting data. So, what technologies should the AECO explore to help reshape and transform our society? The authors of a recent study identified building information management, Internet of Things, and artificial intelligence as the most relevant digital innovations.
Researchers Nicola Moretti, Xiang Xie, Jorge Merino Garcia, Janet Chang and Ajith Kumar Parlikad present a federated data modeling approach to support data interoperability. The model proposed in their paper, “Federated Data Modeling for Built Environment Digital Twins,” in the Journal of Computing in Civil Engineering, would enable DT-based asset management applications. They used a real-life case study to understand how to develop built environment DTs focusing on better operation, performance, and organizational productivity. This research will enable the alignment of the asset information requirements with the service needs during the life cycle of the assets, allowing for data reuse and integration. Learn more about this research at https://doi.org/10.1061/JCCEE5.CPENG-4859. The abstract is below.
Abstract
The digital twin (DT) approach is an enabler for data-driven decision making in architecture, engineering, construction, and operations. Various open data models that can potentially support the DT developments, at different scales and application domains, can be found in the literature. However, many implementations are based on organization-specific information management processes and proprietary data models, hindering interoperability. This article presents the process and information management approaches developed to generate a federated open data model supporting DT applications. The business process modeling notation and transaction and interaction modeling techniques are applied to formalize the federated DT data modeling framework, organized in three main phases: requirements definition, federation, validation and improvement. The proposed framework is developed adopting the cross-disciplinary and multiscale principles. A validation on the development of the federated building-level DT data model for the West Cambridge Campus DT research facility is conducted. The federated data model is used to enable DT-based asset management applications at the building and built environment levels.
Learn more about how federated digital twins can help manage infrastructure in the ASCE Library: https://doi.org/10.1061/JCCEE5.CPENG-4859.
