Digital Twin Framework for Smart Campus to Reduce Greenhouse Gas Emission

Building sectors have significant footprints in carbon emissions. However, monitoring and reducing carbon emissions in buildings are still challenging due to the siloed workflow throughout the building lifecycle. The research proposed a digital twin framework to facilitate communication between real-time building use/operation and energy simulations to reduce greenhouse gas emissions. A digital twin is a virtual representation of a physical object or process, widely studied in product design and system engineering. Digital twins in building research focus on a virtual building model that can monitor real building use and produce feedback to improve building operation and management.The paper presents the testbed development using a university campus building and the digital twin creation connected with parametric BIM, CO2 emission simulation, and ML-based prediction. The testbed is located in Stanley Hall of University of Missouri. The 30m x 8m space has sensor-equipped lighting systems and a data gateway to transfer sensor data to the data server. The digital twin was built on parametric BIM with the building configuration and material information for simulation and visualization. We created the software prototypes for the physics-based energy simulation and ML predictions. The system interface expeditiously displayed the benchmark data of energy use and gas emissions with the web-based dashboard. The paper describes the novel findings, challenges, limitations, and recommendations for future digital twin research for smart campuses.