Dynamic Ontological Modeling of Complex Subway Systems for Flood Resilience through Multi-Source Data Integration
This “Human+AI Protocols” project provides the broader "Human+AI" framework into which the specific subway model fits perfectly.
The dynamic ontology can be the "machine memory" that allows an AI to understand the complex interdependencies of a subway flood, enabling it to guide human operators in finding the best real-time operational and evacuation solutions as described in this project.
This “Urban stormwater digital twin” project models the source of the threat to the subway system.
We can combine these by creating an integrated digital twin where the "Urban stormwater" model provides the boundary conditions and inputs (e.g., rate and location of water ingress) for the Subway System.
Researchers
Jinfeng Lou
Postdoctoral Researcher