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A decision support model for unmanned aerial vehicles assisted disaster response using AHP-TOPSIS method
Abstract
The main objective of disaster response is to secure lives and livelihoods at first. To achieve that, policymakers need accurate information regarding disaster areas to make a quick decision right after the disaster. Especially at a large scale disaster, it is much more important to respond to it quickly due to the number of affected people. In the uncertain atmosphere of the disaster, decision-makers can utilize UAS (Unmanned Aerial Systems) to gather instant images of the disaster area for Search and Rescue Mission (SAR) and damage assessment. Also, it will be used as a communication tool between emergency units and the command center. This paper discusses the usage of UAS in a possible İstanbul earthquake. Considering the damages that may occur after a possible Istanbul earthquake, 5 criteria have been determined, these criteria have been weighted within the Analytical Hierarchy Process (AHP) method, and the Technique for Order-Preference by Similarity to Ideal Solution (TOPSIS) method has prioritized the districts of Istanbul according to these criteria. With the help of this ranking, when the Istanbul earthquake occurs, if a different duty was not given to UASs, it was tried to be determined which districts should first look for the UAS's SAR mission.
Keywords
References
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Details
Primary Language
English
Subjects
Engineering
Journal Section
Research Article
Publication Date
December 31, 2020
Submission Date
May 15, 2020
Acceptance Date
October 12, 2020
Published in Issue
Year 2020 Number: 20
APA
Yıldızbası, A., & Gür, L. (2020). A decision support model for unmanned aerial vehicles assisted disaster response using AHP-TOPSIS method. Avrupa Bilim Ve Teknoloji Dergisi, 20, 56-66. https://doi.org/10.31590/ejosat.737764
Cited By
Human Factors and AI in UAV Systems: Enhancing Operational Efficiency Through AHP and Real-Time Physiological Monitoring
Journal of Intelligent & Robotic Systems
https://doi.org/10.1007/s10846-024-02188-y