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Unmanned Vehicles’ Placement Optimisation for Internet of Things and Internet of Unmanned Vehicles

Telecommunications Department, Faculty of Electronics, Telecommunications and Information Technology, University Politehnica of Bucharest, 061071 Bucharest, Romania
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Author to whom correspondence should be addressed.
Academic Editor: Shafiqul Islam
Sensors 2021, 21(21), 6984; https://doi.org/10.3390/s21216984
Received: 13 September 2021 / Revised: 8 October 2021 / Accepted: 18 October 2021 / Published: 21 October 2021
(This article belongs to the Section Sensors and Robotics)
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. View Full-Text
Keywords: algorithm; Internet of Unmanned Vehicles; link budget; LoRa/LoRaWAN; optimisation; path loss; Wireless Sensors Networks; UAV; USV; Wi-Fi algorithm; Internet of Unmanned Vehicles; link budget; LoRa/LoRaWAN; optimisation; path loss; Wireless Sensors Networks; UAV; USV; Wi-Fi
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MDPI and ACS Style

Dragulinescu, A.-M.; Halunga, S.; Zamfirescu, C. Unmanned Vehicles’ Placement Optimisation for Internet of Things and Internet of Unmanned Vehicles. Sensors 2021, 21, 6984. https://doi.org/10.3390/s21216984

AMA Style

Dragulinescu A-M, Halunga S, Zamfirescu C. Unmanned Vehicles’ Placement Optimisation for Internet of Things and Internet of Unmanned Vehicles. Sensors. 2021; 21(21):6984. https://doi.org/10.3390/s21216984

Chicago/Turabian Style

Dragulinescu, Ana-Maria, Simona Halunga, and Ciprian Zamfirescu. 2021. "Unmanned Vehicles’ Placement Optimisation for Internet of Things and Internet of Unmanned Vehicles" Sensors 21, no. 21: 6984. https://doi.org/10.3390/s21216984

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