Disaster City Digital Twin: Integrating Machine and Human Intelligence to Augment Flood Resilience

This X-Grant project will advance data science and artificial intelligence for modeling, analyzing, and predicting community resilience during urban flooding. It will focus on valuable data products (integrated into a Disaster City Digital twin) that will enhance government decision making, risk reduction, and citizen preparedness and education. In a Disaster City Digital Twin, spatiotemporal dynamics of disaster regions are integrated into an analytics platform fusing datasets from crowd sources and agencies. Through fusion, learning, and exchange of spatiotemporal information with the humanitarian actors (enabled through data integration, AI, and visualization) and the virtual coordination, the digital twin of a disaster city and its human users become smarter over time and gain predictive insights into the planning and response operations in humanitarian actions. This X-Grant project will serve as a research hub that connects and engages researchers with expertise in engineering, machine learning, data science, disaster science, urban science, and GIScience together in a concerted interdisciplinary effort to explore new approaches to the formulation and solution of problems in AI for flood resilience.