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2024 Volume 39
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RESEARCH ARTICLE   Open Access    

XR4DRAMA a knowledge-based system for disaster management and media planning

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  • Corresponding author: Corresponding author: Alexandros Vassiliades; Email: valexande@iti.gr 
  • Abstract: In the previous two decades, Knowledge Graphs (KGs) have evolved, inspiring developers to build ever-more 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 (POI) 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, POI 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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  • Cite this article

    Alexandros Vassiliades, Grigorios Stathopoulos-Kampilis, Gerasimos Antzoulatos, Spyridon Symeonidis, Sotiris Diplaris, Stefanos Vrochidis, Nick Bassiliades, Ioannis Kompatsiaris. 2024. XR4DRAMA a knowledge-based system for disaster management and media planning. The Knowledge Engineering Review 39(1), doi: 10.1017/S026988892400002X
    Alexandros Vassiliades, Grigorios Stathopoulos-Kampilis, Gerasimos Antzoulatos, Spyridon Symeonidis, Sotiris Diplaris, Stefanos Vrochidis, Nick Bassiliades, Ioannis Kompatsiaris. 2024. XR4DRAMA a knowledge-based system for disaster management and media planning. The Knowledge Engineering Review 39(1), doi: 10.1017/S026988892400002X

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RESEARCH ARTICLE   Open Access    

XR4DRAMA a knowledge-based system for disaster management and media planning

  • Corresponding author: Corresponding author: Alexandros Vassiliades; Email: valexande@iti.gr 

Abstract: Abstract: In the previous two decades, Knowledge Graphs (KGs) have evolved, inspiring developers to build ever-more 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 (POI) 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, POI 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).

    • This work has been funded by XR4DRAMA Horizon 2020 project, grant agreement number 952133. The publication of the article in OA mode was financially supported in part by HEAL-Link.

    • https://xr4drama.eu/2022/07/07/xr4drama-pois-virtual-whiteboards/

    • https://xr4drama.eu

    • https://github.com/valexande/xr4dramaFramework

    • https://en.wikipedia.org/wiki/Project_Genoa

    • https://en.wikipedia.org/wiki/DARPA

    • https://xr4drama.eu/wp-content/uploads/2021/12/d3.5_xr4drama_semanticrepresentationfusiondss_20211201_v1.2.pdf

    • https://solr.apache.org/

    • http://www.adbve.it/

    • https://en.wikipedia.org/wiki/Main_Page

    • http://www.alpiorientali.it/

    • https://www.dw.com

    • https://www.w3.org/TR/vocab-ssn/

    • https://oeg.fi.upm.es/index.php/en/technologies/292-oops/index.html

    • This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
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    Alexandros Vassiliades, Grigorios Stathopoulos-Kampilis, Gerasimos Antzoulatos, Spyridon Symeonidis, Sotiris Diplaris, Stefanos Vrochidis, Nick Bassiliades, Ioannis Kompatsiaris. 2024. XR4DRAMA a knowledge-based system for disaster management and media planning. The Knowledge Engineering Review 39(1), doi: 10.1017/S026988892400002X
    Alexandros Vassiliades, Grigorios Stathopoulos-Kampilis, Gerasimos Antzoulatos, Spyridon Symeonidis, Sotiris Diplaris, Stefanos Vrochidis, Nick Bassiliades, Ioannis Kompatsiaris. 2024. XR4DRAMA a knowledge-based system for disaster management and media planning. The Knowledge Engineering Review 39(1), doi: 10.1017/S026988892400002X
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