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...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/22/7735 |
| _version_ | 1797508475337572352 |
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| author | Lucas Rodrigues André Riker Maria Ribeiro Cristiano Both Filipe Sousa Waldir Moreira Kleber Cardoso Antonio Oliveira-Jr |
| author_facet | Lucas Rodrigues André Riker Maria Ribeiro Cristiano Both Filipe Sousa Waldir Moreira Kleber Cardoso Antonio Oliveira-Jr |
| author_sort | Lucas Rodrigues |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T05:04:31Z |
| format | Article |
| id | doaj.art-d4a14811e7984f63b63e6a98251f87b7 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T05:04:31Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-d4a14811e7984f63b63e6a98251f87b72023-11-23T01:28:57ZengMDPI AGSensors1424-82202021-11-012122773510.3390/s21227735Flight Planning Optimization of Multiple UAVs for Internet of ThingsLucas Rodrigues0André Riker1Maria Ribeiro2Cristiano Both3Filipe Sousa4Waldir Moreira5Kleber Cardoso6Antonio Oliveira-Jr7Institute of Informatics (INF), Universidade Federal de Goiás (UFG), Goiânia 74690-900, BrazilInstitute of Exact and Natural Sciences (ICEN), Federal University of Pará, Belém 66075-110, BrazilInstitute for Systems and Computer Engineering, Technology and Science (INESC-TEC), 4200-465 Porto, PortugalApplied Computing Graduate Program, University of Vale do Rio dos Sinos (UNISINOS), São Leopoldo 93022-750, BrazilFraunhofer Portugal AICOS, 4200-135 Porto, PortugalFraunhofer Portugal AICOS, 4200-135 Porto, PortugalInstitute of Informatics (INF), Universidade Federal de Goiás (UFG), Goiânia 74690-900, BrazilInstitute of Informatics (INF), Universidade Federal de Goiás (UFG), Goiânia 74690-900, BrazilThis 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.https://www.mdpi.com/1424-8220/21/22/7735Internet of Things (IoT)Unmanned Aerial Vehicle (UAV)autonomous flight planningoptimization |
| spellingShingle | Lucas Rodrigues André Riker Maria Ribeiro Cristiano Both Filipe Sousa Waldir Moreira Kleber Cardoso Antonio Oliveira-Jr Flight Planning Optimization of Multiple UAVs for Internet of Things Sensors Internet of Things (IoT) Unmanned Aerial Vehicle (UAV) autonomous flight planning optimization |
| 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 | Internet of Things (IoT) Unmanned Aerial Vehicle (UAV) autonomous flight planning optimization |
| url | https://www.mdpi.com/1424-8220/21/22/7735 |
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