A lightweight Ontology for real time semantic correlation of situation awareness data generated for first responders
Iosif Angelidis, Elena Politi, George Vafeiadis, Danai Vergeti, Dimitris Ntalaperas, Nikos Papageorgopoulos · 2021 International Conference on Computational Science and Computational Intelligence (CSCI) · 2021
In case of an emergency, the immediate action of the first responders is crucial for saving human lives. Their intervention requires specialized instrumentation, available at all times and easily accessible, which meets stringent requirements in terms of detection accuracy, quick localization, and reduction of false alarms. This work proposes a novel ontology-based methodology which integrates data from IoT devices in the frame of a Situation Awareness (SA) semantic model. The proposed model aims at providing the conceptual representation of core entities, which will be represented by concepts and will cover specific aspects of the SA domain, such as proper decision making during the course of an emergency operation, conceptual representation of critical information required for such tasks and of important information flows which potentially exist between involved actors. Finally, we set the scene towards validating the efficiency and efficacy of our proposed model directly in the field, through seven (7) use cases.