RES-Q: Self-evolving Post-disaster Response Plans Utilizing Semantics

Abstract

During the last decade, communities at local and national level are implementing actions geared towards improving disaster resilience. In this context, the importance of ICT in disaster risk management is rapidly increasing globally, especially nowadays amidst the climate crisis and the covid-19 pandemic. However, disaster risk management operations require contributions and collaboration of different type of actors and infrastructures with different functions, rules, protocols and datasets, forming complex contexts in decision making and event coordination. Hence, semantic interoperability between the various stakeholders is one of the challenges to be confronted. In this paper, we present the RES-Q (RESCUE) approach that proposes an information technology solution concerning the real-time recommendation and orchestration of post-disaster response plans. The implemented RES-Q prototype comprises an expert system and a workflow execution engine based on an ontological infrastructure for modeling the response actions for each type of disaster. The ontological model is designed using a multi-layer approach encapsulating the required knowledge streams and a semantic rule repository. During the execution of a post-disaster plan, the system reasons over the rules and composes the next steps of the corresponding response processes. The rule repository is able to infer new knowledge as each plan progresses, which can update the RES-Q ontology accordingly. © 2022, National Technical University of Athens. All rights reserved.