E3-UAV: An Edge-Based Energy-Efficient Object Detection System for Unmanned Aerial Vehicles

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Author(s)Suo, Jiashun
Author(s)Zhang, Xingzhou
Author(s)Shi, Weisong
Author(s)Zhou, Wei
Date Accessioned2023-11-30T21:13:43Z
Date Available2023-11-30T21:13:43Z
Publication Date2023-08-03
Description© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This article was originally published in IEEE Internet of Things Journal. The version of record is available at: https://doi.org/10.1109/JIOT.2023.3301623. This article will be embargoed until 08/03/2025.
AbstractMotivated by the advances in deep learning techniques, the application of Unmanned Aerial Vehicle (UAV)-based object detection has proliferated across a range of fields, including vehicle counting, fire detection, and city monitoring. While most existing research studies only a subset of the challenges inherent to UAV-based object detection, there are few studies that balance various aspects to design a practical system for energy consumption reduction. In response, we present the E3-UAV, an edge-based energy-efficient object detection system for UAVs. The system is designed to dynamically support various UAV devices, edge devices, and detection algorithms, with the aim of minimizing energy consumption by deciding the most energy-efficient flight parameters (including flight altitude, flight speed, detection algorithm, and sampling rate) required to fulfill the detection requirements of the task. We first present an effective evaluation metric for actual tasks and construct a transparent energy consumption model based on hundreds of actual flight data to formalize the relationship between energy consumption and flight parameters. Then we present a lightweight energy-efficient priority decision algorithm based on a large quantity of actual flight data to assist the system in deciding flight parameters. Finally, we evaluate the performance of the system, and our experimental results demonstrate that it can significantly decrease energy consumption in real-world scenarios. Additionally, we provide four insights that can assist researchers and engineers in their efforts to study UAV-based object detection further.
SponsorThis work was supported in part by the National Natural Science Foundation of China under Grant 62162067, 62101480, and 62072434; in part by the Yunnan Province Science Foundation under Grant No.202005AC160007, No.202001BB050076; in part by the China Postdoctoral Science Foundation under Grant No.2021M693227; in part by the Innovation Funding of ICT, CAS under Grant No.E361040; and in part by the Beijing Natural Science Foundation under Grant No.4212027. (Corresponding author: Wei Zhou.)
CitationJ. Suo, X. Zhang, W. Shi and W. Zhou, "E3-UAV: An Edge-Based Energy-Efficient Object Detection System for Unmanned Aerial Vehicles," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2023.3301623.
ISSN2327-4662
URLhttps://udspace.udel.edu/handle/19716/33644
Languageen_US
PublisherIEEE Internet of Things Journal
KeywordsUnmanned Aerial Vehicle (UAV)
Keywordsenergy efficiency
Keywordsobject detection system
Keywordsedge intelligence
Keywordsedge computing
TitleE3-UAV: An Edge-Based Energy-Efficient Object Detection System for Unmanned Aerial Vehicles
TypeArticle
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