Unmanned Vehicles’ Placement Optimisation for Internet of Things and Internet of Unmanned Vehicles
Currently, the use of unmanned vehicles, such as drones, boats and ships, in monitoring tasks where human presence is difficult or even impossible raises several issues. Continuous efforts to improve the autonomy of such vehicles have not solved all aspects of this issue. In an Internet of Unmanned...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-10-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/21/6984 |
| _version_ | 1797511809571225600 |
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| author | Ana-Maria Dragulinescu Simona Halunga Ciprian Zamfirescu |
| author_facet | Ana-Maria Dragulinescu Simona Halunga Ciprian Zamfirescu |
| author_sort | Ana-Maria Dragulinescu |
| collection | DOAJ |
| description | Currently, the use of unmanned vehicles, such as drones, boats and ships, in monitoring tasks where human presence is difficult or even impossible raises several issues. Continuous efforts to improve the autonomy of such vehicles have not solved all aspects of this issue. In an Internet of Unmanned Vehicles (IoUV) environment, the idea of replacing the static wireless infrastructure and reusing the mobile monitoring nodes in different conditions would converge to a dynamic solution to assure data collection in areas where there is no infrastructure that ensures Internet access. The current paper fills a significant gap, proposing an algorithm that optimises the positions of unmanned vehicles such that an ad hoc network is deployed to serve specific wireless sensor networks that have no other Internet connectivity (hilly/mountainous areas, Danube Delta) and must be connected to an Internet of Things (IoT) ecosystem. The algorithm determines the optimum positions of UV nodes that decrease the path losses below the link budget threshold with minimum UV node displacement compared to their initial coordinates. The algorithm was tested in a rural scenario and 3rd Generation Partnership Project (3GPP), free space and two-ray propagation models. The paper proposes another type of network, a Flying and Surface Ad Hoc Network (FSANET), a concept which implies collaboration and coexistence between unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs) and several use cases that motivate the need for such a network. |
| first_indexed | 2024-03-10T05:53:17Z |
| format | Article |
| id | doaj.art-cfde94f9aa7940368228dc31ff8ec133 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T05:53:17Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-cfde94f9aa7940368228dc31ff8ec1332023-11-22T21:34:51ZengMDPI AGSensors1424-82202021-10-012121698410.3390/s21216984Unmanned Vehicles’ Placement Optimisation for Internet of Things and Internet of Unmanned VehiclesAna-Maria Dragulinescu0Simona Halunga1Ciprian Zamfirescu2Telecommunications Department, Faculty of Electronics, Telecommunications and Information Technology, University Politehnica of Bucharest, 061071 Bucharest, RomaniaTelecommunications Department, Faculty of Electronics, Telecommunications and Information Technology, University Politehnica of Bucharest, 061071 Bucharest, RomaniaTelecommunications Department, Faculty of Electronics, Telecommunications and Information Technology, University Politehnica of Bucharest, 061071 Bucharest, RomaniaCurrently, the use of unmanned vehicles, such as drones, boats and ships, in monitoring tasks where human presence is difficult or even impossible raises several issues. Continuous efforts to improve the autonomy of such vehicles have not solved all aspects of this issue. In an Internet of Unmanned Vehicles (IoUV) environment, the idea of replacing the static wireless infrastructure and reusing the mobile monitoring nodes in different conditions would converge to a dynamic solution to assure data collection in areas where there is no infrastructure that ensures Internet access. The current paper fills a significant gap, proposing an algorithm that optimises the positions of unmanned vehicles such that an ad hoc network is deployed to serve specific wireless sensor networks that have no other Internet connectivity (hilly/mountainous areas, Danube Delta) and must be connected to an Internet of Things (IoT) ecosystem. The algorithm determines the optimum positions of UV nodes that decrease the path losses below the link budget threshold with minimum UV node displacement compared to their initial coordinates. The algorithm was tested in a rural scenario and 3rd Generation Partnership Project (3GPP), free space and two-ray propagation models. The paper proposes another type of network, a Flying and Surface Ad Hoc Network (FSANET), a concept which implies collaboration and coexistence between unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs) and several use cases that motivate the need for such a network.https://www.mdpi.com/1424-8220/21/21/6984algorithmInternet of Unmanned Vehicleslink budgetLoRa/LoRaWANoptimisationpath loss |
| spellingShingle | Ana-Maria Dragulinescu Simona Halunga Ciprian Zamfirescu Unmanned Vehicles’ Placement Optimisation for Internet of Things and Internet of Unmanned Vehicles Sensors algorithm Internet of Unmanned Vehicles link budget LoRa/LoRaWAN optimisation path loss |
| title | Unmanned Vehicles’ Placement Optimisation for Internet of Things and Internet of Unmanned Vehicles |
| title_full | Unmanned Vehicles’ Placement Optimisation for Internet of Things and Internet of Unmanned Vehicles |
| title_fullStr | Unmanned Vehicles’ Placement Optimisation for Internet of Things and Internet of Unmanned Vehicles |
| title_full_unstemmed | Unmanned Vehicles’ Placement Optimisation for Internet of Things and Internet of Unmanned Vehicles |
| title_short | Unmanned Vehicles’ Placement Optimisation for Internet of Things and Internet of Unmanned Vehicles |
| title_sort | unmanned vehicles placement optimisation for internet of things and internet of unmanned vehicles |
| topic | algorithm Internet of Unmanned Vehicles link budget LoRa/LoRaWAN optimisation path loss |
| url | https://www.mdpi.com/1424-8220/21/21/6984 |
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