Qin, Yujie, Kishk, Mustafa A. and Alouini, Mohamed-Slim (2023) Stochastic-Geometry-Based Analysis of Multipurpose UAVs for Package and Data Delivery. IEEE Internet of Things Journal, 10 (5). pp. 4664-4676. ISSN 2372-2541
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Official URL: https://doi.org/10.1109/JIOT.2022.3218674
Abstract
Using drones for communications and transportation is drawing great attention in many practical scenarios, such as package delivery and providing additional wireless coverage. However, the increasing demand for unmanned aerial vehicles (UAVs) from industry and academia will cause aerial traffic conflicts in the future. This, in turn, motivates the idea of this article: multipurpose UAVs, acting as aerial wireless data relays and means of aerial transportation simultaneously, to deliver packages and data at the same time. This article aims to analyze the feasibility of using drones to collect and deliver data from the Internet of Things (IoT) devices to terrestrial base stations (TBSs) while delivering packages from warehouses to residential areas. We propose an algorithm to optimize the trajectory of UAVs to maximize the size of collected/delivered data while minimizing the total round trip time subject to the limited onboard battery of UAVs. Specifically, we use tools from stochastic geometry to model the locations of the IoT clusters and the TBSs and study the system performance with respect to energy efficiency, average size of collected/delivered data, and package delivery time. Our numerical results reveal that multifunctional UAVs have great potential to enhance the efficiency of both communication and transportation networks.
Item Type: | Article |
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Keywords: | Data collection; Internet of Things; IoT; devices, multipurpose unmanned aerial vehicle; UAV; package delivery; Poisson point process; stochastic geometry; |
Academic Unit: | Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute |
Item ID: | 19396 |
Identification Number: | 10.1109/JIOT.2022.3218674 |
Depositing User: | Mustafa Kishk |
Date Deposited: | 21 Jan 2025 16:42 |
Journal or Publication Title: | IEEE Internet of Things Journal |
Refereed: | Yes |
Related URLs: | |
URI: | https://mural.maynoothuniversity.ie/id/eprint/19396 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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