Fires: A Semantic Model for Advanced Querying and Prediction Analysis for First Responders in Post-Disaster Response Plans

33 Pages Posted: 1 Aug 2023

See all articles by Areti Bania

Areti Bania

affiliation not provided to SSRN

Omiros Iatrellis

affiliation not provided to SSRN

Nicholas Samaras

affiliation not provided to SSRN

Theodor Panagiotakopoulos

Theodor Panagiotakopoulos

Abstract

Natural disasters can significantly threaten the sustainability of countries. Prompt and effective response by first responders is essential in Disaster Risk Management (DRM) to reduce individuals’ vulnerability and minimize environmental and infrastructural damages. However, disaster-related information is often generated by heterogeneous sources, making the first responders’ decision-making process complex and time-consuming. To address these challenges, a common conceptual model is imperative to improve interoperability among diverse organizations and software systems, enabling effective collaboration. Semantic Web technologies offer a promising solution for integrating heterogeneous data and providing well-defined meaning in the representation and exchange of DRM-related knowledge. In this context, this study introduces FiReS (First Responders System), an ontological model designed to enhance data interoperability among first responders in post-disaster response plans for advanced data analysis and machine learning prediction. The validation of FiReS is conducted through a series of case studies exploring various aspects of disaster response, such as the response time of emergency services and the volume and classification of emergency calls. This approach facilitates streamlined access, thorough analysis, and seamless exchange of information, empowering stakeholders to strengthen their disaster response strategies and foster resilience within communities.

Keywords: natural disasters, First Responders, Post-disaster Response, Web Semantic, Ontology, machine learning

Suggested Citation

Bania, Areti and Iatrellis, Omiros and Samaras, Nicholas and Panagiotakopoulos, Theodor, Fires: A Semantic Model for Advanced Querying and Prediction Analysis for First Responders in Post-Disaster Response Plans. Available at SSRN: https://ssrn.com/abstract=4527923 or http://dx.doi.org/10.2139/ssrn.4527923

Areti Bania (Contact Author)

affiliation not provided to SSRN ( email )

No Address Available

Omiros Iatrellis

affiliation not provided to SSRN ( email )

No Address Available

Nicholas Samaras

affiliation not provided to SSRN ( email )

No Address Available

Theodor Panagiotakopoulos

Theodor Panagiotakopoulos ( email )

Patra
Greece

HOME PAGE: http://daissy.eap.gr/resume/theodor-panagiotakopoulos/

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