Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
This session showcases the transformative potential of digital twins and semantic data modeling in enhancing building performance, efficiency, and sustainability. The first presentation highlights the creation of an energy model digital twin for a 356,000 sq. ft. net-zero ready mixed-use building, integrating 8,000+ sensors and live BMS data to enable dynamic calibration, fault detection, and predictive analytics. The second presentation explores a tool that automatically generates semantic models from BIM data using standardized ontologies like ASHRAE Standard 223, streamlining the deployment of software applications such as automated fault detection and diagnostics. The third presentation details how ASHRAE’s Net-Zero Energy Global Headquarters utilized digital twin workflows and BIM data integration to optimize asset management, predictive maintenance, and energy performance. Together, these presentations demonstrate how digital twins and semantic models empower designers, operators, and owners to achieve intelligent, adaptive, and sustainable building management.
Presentations
BIM2RDF: A tool for creating Semantic Models of Building Systems from Building Information Models
Michael Poplawski, Trisha Tarun Gupta, Majid Aldosari
Pacific Northwest National Laboratory, United States of America
Building systems are able to monitor their performance and environmental conditions. Software applications that can make use of this data (e.g., automated fault detection and diagnostics) can improve building performance and occupant satisfaction and reduce operational costs. Currently, such software needs to be configured manually, typically requiring specialized human labor, making the applications time-consuming and expensive to deploy. Semantic models created using standardized ontologies can reduce this deployment burden. This presentation describes a tool that creates semantic models that comply with the emerging ASHRAE Standard 223 ontology from source Building Information Models exported from Autodesk Revit using Speckle.
Real-Time Calibration of Energy Models Using BMS Data: Building the Next Generation of Digital Twins
Nupoor Kansara, Dr. Justin Shultz
Page, United States of America
This presentation explores an energy model digital twin for a 356,000 sq. ft. net-zero ready mixed use building, integrating BMS data from 8,000+ sensors for calibration. It details how live data maps to energy model variables, creating a dynamic feedback loop. The energy-model enables granular sensor access and actuator control for synchronization. A flexible data architecture and web interface ensure interoperability, supporting visualization, fault detection, and predictive analytics. This framework advances digital twin capabilities for intelligent optimization. AI-driven optimization will be leveraged in the future to evaluate energy efficiency measures and performance.
