Intelligent Drone Swarms to Search for Victims in Post-Disaster Areas
This study presents the Drone Swarms Routing Problem (DSRP), which consists of identifying the maximum number of victims in post-disaster areas. The post-disaster area is modeled in a complete graph, where each search location is represented by a vertex, and the edges are the shortest paths between...
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Format: | Article |
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MDPI AG
2023-11-01
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Series: | Sensors |
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Online Access: | https://www.mdpi.com/1424-8220/23/23/9540 |
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author | Matheus Nohra Haddad Andréa Cynthia Santos Christophe Duhamel Amadeu Almeida Coco |
author_facet | Matheus Nohra Haddad Andréa Cynthia Santos Christophe Duhamel Amadeu Almeida Coco |
author_sort | Matheus Nohra Haddad |
collection | DOAJ |
description | This study presents the Drone Swarms Routing Problem (DSRP), which consists of identifying the maximum number of victims in post-disaster areas. The post-disaster area is modeled in a complete graph, where each search location is represented by a vertex, and the edges are the shortest paths between destinations, with an associated weight, corresponding to the battery consumption to fly to a location. In addition, in the DSRP addressed here, a set of drones are deployed in a cooperative drone swarms approach to boost the search. In this context, a V-shaped formation is applied with leader replacements, which allows energy saving. We propose a computation model for the DSRP that considers each drone as an agent that selects the next search location to visit through a simple and efficient method, the Drone Swarm Heuristic. In order to evaluate the proposed model, scenarios based on the Beirut port explosion in 2020 are used. Numerical experiments are presented in the offline and online versions of the proposed method. The results from such scenarios showed the efficiency of the proposed approach, attesting not only the coverage capacity of the computational model but also the advantage of adopting the V-shaped formation flight with leader replacements. |
first_indexed | 2024-03-09T01:42:09Z |
format | Article |
id | doaj.art-81229b3061ff44a7a22338614e45f87d |
institution | Directory Open Access Journal |
issn | 1424-8220 |
language | English |
last_indexed | 2024-03-09T01:42:09Z |
publishDate | 2023-11-01 |
publisher | MDPI AG |
record_format | Article |
series | Sensors |
spelling | doaj.art-81229b3061ff44a7a22338614e45f87d2023-12-08T15:26:21ZengMDPI AGSensors1424-82202023-11-012323954010.3390/s23239540Intelligent Drone Swarms to Search for Victims in Post-Disaster AreasMatheus Nohra Haddad0Andréa Cynthia Santos1Christophe Duhamel2Amadeu Almeida Coco3LITIS, ISEL, Université Le Havre Normandie, 25 Rue Philippe Lebon, 76600 Le Havre, FranceLITIS, ISEL, Université Le Havre Normandie, 25 Rue Philippe Lebon, 76600 Le Havre, FranceLITIS, ISEL, Université Le Havre Normandie, 25 Rue Philippe Lebon, 76600 Le Havre, FranceLITIS, ISEL, Université Le Havre Normandie, 25 Rue Philippe Lebon, 76600 Le Havre, FranceThis study presents the Drone Swarms Routing Problem (DSRP), which consists of identifying the maximum number of victims in post-disaster areas. The post-disaster area is modeled in a complete graph, where each search location is represented by a vertex, and the edges are the shortest paths between destinations, with an associated weight, corresponding to the battery consumption to fly to a location. In addition, in the DSRP addressed here, a set of drones are deployed in a cooperative drone swarms approach to boost the search. In this context, a V-shaped formation is applied with leader replacements, which allows energy saving. We propose a computation model for the DSRP that considers each drone as an agent that selects the next search location to visit through a simple and efficient method, the Drone Swarm Heuristic. In order to evaluate the proposed model, scenarios based on the Beirut port explosion in 2020 are used. Numerical experiments are presented in the offline and online versions of the proposed method. The results from such scenarios showed the efficiency of the proposed approach, attesting not only the coverage capacity of the computational model but also the advantage of adopting the V-shaped formation flight with leader replacements.https://www.mdpi.com/1424-8220/23/23/9540drone swarmsroutingmulti-agents systemshumanitarian logisticsdisaster relief |
spellingShingle | Matheus Nohra Haddad Andréa Cynthia Santos Christophe Duhamel Amadeu Almeida Coco Intelligent Drone Swarms to Search for Victims in Post-Disaster Areas Sensors drone swarms routing multi-agents systems humanitarian logistics disaster relief |
title | Intelligent Drone Swarms to Search for Victims in Post-Disaster Areas |
title_full | Intelligent Drone Swarms to Search for Victims in Post-Disaster Areas |
title_fullStr | Intelligent Drone Swarms to Search for Victims in Post-Disaster Areas |
title_full_unstemmed | Intelligent Drone Swarms to Search for Victims in Post-Disaster Areas |
title_short | Intelligent Drone Swarms to Search for Victims in Post-Disaster Areas |
title_sort | intelligent drone swarms to search for victims in post disaster areas |
topic | drone swarms routing multi-agents systems humanitarian logistics disaster relief |
url | https://www.mdpi.com/1424-8220/23/23/9540 |
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