An insightful workshop was organized by GRID@UNSW and RIIS in collaboration with the Next-Gen Architectural Manufacturing group at UNSW, delving into the potential of Artificial Intelligence (AI), Deep Learning (DL), and Large Language Models (LLM) for semantic enrichment of geospatial data, intelligent queries and complex analytics.

The session kicked off with and insightful plenary by Rob Atkinson from the Open Geospatial Consortium (OGC), describing Digital Twins as a “systems of systems” connected by OGC APIs to enable cross-domain interoperability and enhance complex problem solving.

The session provided PhD students with a platform to engage in discussions and updates on the latest developments. Presenters highlighted how AI tools are poised to significantly enhance their respective research areas, considering the diverse backgrounds of the attendees. Jack Yafei Sun presented his PhD work exploring information extraction for domain knowledge graph construction and Saeed Heidary presented graph-structured information management systems in construction. Jidnyasa Patil described her Scan-to-BIM DL approach and Yu Gao examined Intelligent lifecycle management of construction and demolition waste in complex environments, focusing on integrating multimodal LLM and agents. Binjie Xu explored the use of multimodal LLM to monitor mental matigue of plant and machinery operators and Mahdi Soheyil Fard discussed AI-integrated solutions for decarbonizing the building industry.

For those interested in more details, the presentations can be accessed at grid.unsw.edu.au/presentations.