Knowledge Graphs for Coastal Bridge Networks

Managing the long-term risk of coastal bridge networks requires integrating data from many sources — bridge inspections, traffic monitoring, streamflow records — in a way that captures how these systems interact. This project developed a city-scale knowledge graph for Miami-Dade County that maps relationships between variables relevant to bridge life-cycle risk, including correlated climate hazards like flooding and hurricanes. Built on the AutoGraCS framework, the knowledge graph is designed to scale easily to other regions and can be converted into Bayesian networks for probabilistic risk analysis. The result is a foundation for future digital twins of coastal transportation networks.