Ontology-based crisis simulation system for population sheltering management

Climate change has led to an increase in the frequency and intensity of natural disasters, necessitating the development of efficient crisis management strategies for population sheltering. However, existing research on this topic primarily focuses on the use of public resources such as ambulances and fire trucks, which may sometimes be insufficient due to high demand and impacted locations, worsening the shortage of resources. This research introduces an ontology-based crisis simulation system for population sheltering management that focuses on the integration and distribution of citizen–volunteer drivers/vehicles into the evacuation process. Recognizing the limitations of public resources in current crisis management models, our approach incorporates citizen resources to enhance overall evacuation capacity. We develop an ontology to standardize crisis management knowledge, frame vehicle distribution as a recommendation problem, and design a simulation module incorporating a constraint-based recommender system. The proposed scenario illustrates how the simulation system can recommend citizen resources during crisis situations by considering the constraints to be satisfied. With our system, we aim at helping stakeholders to be prepared for various disaster scenarios: optimizing resource allocation and reducing time to make decisions by decision-makers.