A. Vassiliades, G. Stathopoulos-Kampilis, G. Antzoulatos, S. Symeonidis, S. Diplaris, S. Vrochidis, N. Bassiliades, I. Kompatsiaris, “XR4DRAMA a knowledge-based system for disaster management and media planning”, The Knowledge Engineering Review, Cambridge University Press, vol. 39, e1, pp. 1-28, 2024.

Authors:

  • A. Vassiliades, G. Stathopoulos-Kampilis, G. Antzoulatos, S. Symeonidis, S. Diplaris, S. Vrochidis, N. Bassiliades, I. Kompatsiaris

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Keywords:

  • Knowledge Graphs, Disaster Management, Points of Interest, POI Management Mechanism

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Abstract:

  • In the previous two decades, Knowledge Graphs (KGs) have evolved, inspiring developers to build evermore context-related KGs. Because of this development, Artificial Intelligence (AI) applications can now access open domain-specific information in a format that is both semantically rich and machine comprehensible. In this article, we introduce the XR4DRAMA framework. The KG of the XR4DRAMA framework can represent data for media preparation and disaster management. More specifically, the KG of the XR4DRAMA framework can represent information about: (a) Observations and Events (e.g., data collection of biometric sensors, information in photos and text messages), (b) Spatio-temporal (e.g., highlighted locations and timestamps), (c) Mitigation and response plans in crisis (e.g., first responder teams). In addition, we provide a mechanism that allows Points of Interest to be created or updated based on videos, photos, and text messages sent by users. For improved disaster management and media coverage of a location, Points of Interest serve as markers to journalists and first responders. A task creation mechanism is also provided for the disaster management scenario with the XR4DRAMA framework, which indicates to first responders and citizens what tasks need to be performed in case of an emergency. Finally, the XR4DRAMA framework has a danger zone creation mechanism. Danger zones are regions in a map that are considered as dangerous for citizens and first responders during a disaster management scenario, and are annotated by a severity score. The last two mechanisms are based on a Decision Support System (DSS).
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School of Informatics
Aristotle University of Thessaloniki
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Prof. Ioannis P. Vlahavas
tel: ++30 231099-8145
fax: ++30 231099-8362
e-mail: vlahavas@csd.auth.gr

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