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Flight Planning Optimization of Multiple UAVs for Internet of Things

This article presents an approach to autonomous flight planning of Unmanned Aerial Vehicles (UAVs)-Drones as data collectors to the Internet of Things (IoT). We have proposed a model for only one aircraft, as well as for multiple ones. A clustering technique that extends the scope of the number of I...

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Detalles Bibliográficos
Autores principales: Rodrigues, Lucas, Riker, André, Ribeiro, Maria, Both, Cristiano, Sousa, Filipe, Moreira, Waldir, Cardoso, Kleber, Oliveira-Jr, Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8618574/
https://www.ncbi.nlm.nih.gov/pubmed/34833810
http://dx.doi.org/10.3390/s21227735
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author Rodrigues, Lucas
Riker, André
Ribeiro, Maria
Both, Cristiano
Sousa, Filipe
Moreira, Waldir
Cardoso, Kleber
Oliveira-Jr, Antonio
author_facet Rodrigues, Lucas
Riker, André
Ribeiro, Maria
Both, Cristiano
Sousa, Filipe
Moreira, Waldir
Cardoso, Kleber
Oliveira-Jr, Antonio
author_sort Rodrigues, Lucas
collection PubMed
description This article presents an approach to autonomous flight planning of Unmanned Aerial Vehicles (UAVs)-Drones as data collectors to the Internet of Things (IoT). We have proposed a model for only one aircraft, as well as for multiple ones. A clustering technique that extends the scope of the number of IoT devices (e.g., sensors) visited by UAVs is also addressed. The flight plan generated from the model focuses on preventing breakdowns due to a lack of battery charge to maximize the number of nodes visited. In addition to the drone autonomous flight planning, a data storage limitation aspect is also considered. We have presented the energy consumption of drones based on the aerodynamic characteristics of the type of aircraft. Simulations show the algorithm’s behavior in generating routes, and the model is evaluated using a reliability metric.
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spelling pubmed-86185742021-11-27 Flight Planning Optimization of Multiple UAVs for Internet of Things Rodrigues, Lucas Riker, André Ribeiro, Maria Both, Cristiano Sousa, Filipe Moreira, Waldir Cardoso, Kleber Oliveira-Jr, Antonio Sensors (Basel) Article This article presents an approach to autonomous flight planning of Unmanned Aerial Vehicles (UAVs)-Drones as data collectors to the Internet of Things (IoT). We have proposed a model for only one aircraft, as well as for multiple ones. A clustering technique that extends the scope of the number of IoT devices (e.g., sensors) visited by UAVs is also addressed. The flight plan generated from the model focuses on preventing breakdowns due to a lack of battery charge to maximize the number of nodes visited. In addition to the drone autonomous flight planning, a data storage limitation aspect is also considered. We have presented the energy consumption of drones based on the aerodynamic characteristics of the type of aircraft. Simulations show the algorithm’s behavior in generating routes, and the model is evaluated using a reliability metric. MDPI 2021-11-20 /pmc/articles/PMC8618574/ /pubmed/34833810 http://dx.doi.org/10.3390/s21227735 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Rodrigues, Lucas
Riker, André
Ribeiro, Maria
Both, Cristiano
Sousa, Filipe
Moreira, Waldir
Cardoso, Kleber
Oliveira-Jr, Antonio
Flight Planning Optimization of Multiple UAVs for Internet of Things
title Flight Planning Optimization of Multiple UAVs for Internet of Things
title_full Flight Planning Optimization of Multiple UAVs for Internet of Things
title_fullStr Flight Planning Optimization of Multiple UAVs for Internet of Things
title_full_unstemmed Flight Planning Optimization of Multiple UAVs for Internet of Things
title_short Flight Planning Optimization of Multiple UAVs for Internet of Things
title_sort flight planning optimization of multiple uavs for internet of things
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8618574/
https://www.ncbi.nlm.nih.gov/pubmed/34833810
http://dx.doi.org/10.3390/s21227735
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