research-article

Ontology-based Modelling and Reasoning for Forest Fire Emergencies in Resilient Societies

Authors:

Panagiota Masa,

Georgios Meditskos,

Spyridon Kintzios,

Stefanos Vrochidis,

Ioannis KompatsiarisAuthors Info & Claims

SETN '22: Proceedings of the 12th Hellenic Conference on Artificial Intelligence

Article No.: 24, Pages 1 - 9

https://doi.org/10.1145/3549737.3549765

Published: 09 September 2022 Publication History

Abstract

Every year, thousands of forest fires throughout the world cause disasters. One of the most critical challenges during a wildfire disaster is the effective management of heterogeneous information relative to the crisis to support human operators and authorities. Towards addressing this challenge, this paper presents an ontology-based framework for data representation and interlinking of wildfire events that are being used to foster advanced reasoning, situational awareness and interpretation for decision support. More specifically, we illustrate the capabilities of the ONTO-SAFE ontology to symbolically model contextual information in the domain, addressing application and user requirements promoting the creation of interoperable knowledge graphs. On top of the symbolic knowledge graphs, we define a rule-based framework for infusing expert knowledge in the form of constraints and rules to recognize patterns and situations of interest based on domain knowledge, assisting end-users in taking informed decisions and facilitating advanced decision-making.

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Digital Library

Cited By

Doumanas DSoularidis AKotis KVouros G(2024)Integrating LLMs in the Engineering of a SAR OntologyArtificial Intelligence Applications and Innovations10.1007/978-3-031-63223-5_27(360-374)Online publication date: 21-Jun-2024
https://doi.org/10.1007/978-3-031-63223-5_27
Zhong WMei XNiu FFan XOu SZhong S(2023)Fusing Social Media, Remote Sensing, and Fire Dynamics to Track Wildland-Urban Interface FireRemote Sensing10.3390/rs1515384215:15(3842)Online publication date: 2-Aug-2023
https://doi.org/10.3390/rs15153842
Masa PKintzios SVasileiou ZMeditskos GVrochidis SKompatsiaris I(2023)A Semantic Framework for Decision Making in Forest Fire EmergenciesApplied Sciences10.3390/app1316906513:16(9065)Online publication date: 8-Aug-2023
https://doi.org/10.3390/app13169065
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cover image ACM Other conferences

SETN '22: Proceedings of the 12th Hellenic Conference on Artificial Intelligence

September 2022

450 pages

ISBN:9781450395977

DOI:10.1145/3549737

Copyright © 2022 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

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Published: 09 September 2022

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SETN 2022

SETN 2022: 12th Hellenic Conference on Artificial Intelligence

September 7 - 9, 2022

Corfu, Greece

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Cited By

Doumanas DSoularidis AKotis KVouros G(2024)Integrating LLMs in the Engineering of a SAR OntologyArtificial Intelligence Applications and Innovations10.1007/978-3-031-63223-5_27(360-374)Online publication date: 21-Jun-2024
https://doi.org/10.1007/978-3-031-63223-5_27
Zhong WMei XNiu FFan XOu SZhong S(2023)Fusing Social Media, Remote Sensing, and Fire Dynamics to Track Wildland-Urban Interface FireRemote Sensing10.3390/rs1515384215:15(3842)Online publication date: 2-Aug-2023
https://doi.org/10.3390/rs15153842
Masa PKintzios SVasileiou ZMeditskos GVrochidis SKompatsiaris I(2023)A Semantic Framework for Decision Making in Forest Fire EmergenciesApplied Sciences10.3390/app1316906513:16(9065)Online publication date: 8-Aug-2023
https://doi.org/10.3390/app13169065
Wang XNady SZhang ZZhang MWang J(2023)Knowledge Graph of Urban Firefighting with Rule-Based Entity ExtractionEngineering Applications of Neural Networks10.1007/978-3-031-34204-2_15(168-177)Online publication date: 7-Jun-2023
https://doi.org/10.1007/978-3-031-34204-2_15

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