EagleEYE: Aerial edge-enabled disaster relief response system

Muhammad Febrian Ardiansyah, Timothy William, Osamah Ibrahiem Abdullaziz, Li-Chun Wang, Po-Lung Tien, Maria C. Yuang

研究成果: Conference contribution同行評審

5 引文 斯高帕斯(Scopus)

摘要

The fifth generation (5G) mobile network has paved the way for innovations across vertical industries. The integration of distributed intelligent edge into the 5G orchestrated architecture brings the benefits of low-latency and automation. A successful example of this integration is exhibited by the 5G-DIVE project, which aims at proving the technical merits and business value proposition of vertical industries such as autonomous drone surveillance and navigation. In this paper, and as part of 5G-DIVE, we present an aerial disaster relief system, called EagleEYE, which utilizes edge computing and machine learning to detect emergency situations in real-time. EagleEYE reduces training time by devising an object fusion mechanism which enables reusing existing datasets. Furthermore, EagleEYE parallelizes the detection tasks to enable real-time response. Finally, EagleEYE is evaluated in a real-world testbed and the results show that EagleEYE can reduce the inference latency by 90% with a high detection accuracy of 87%.

原文English
主出版物標題2020 European Conference on Networks and Communications, EuCNC 2020
發行者Institute of Electrical and Electronics Engineers Inc.
頁面321-325
頁數5
ISBN(電子)9781728143552
DOIs
出版狀態Published - 6月 2020
事件29th European Conference on Networks and Communications, EuCNC 2020 - Virtual, Dubrovnik, Croatia
持續時間: 15 6月 202018 6月 2020

出版系列

名字2020 European Conference on Networks and Communications, EuCNC 2020

Conference

Conference29th European Conference on Networks and Communications, EuCNC 2020
國家/地區Croatia
城市Virtual, Dubrovnik
期間15/06/2018/06/20

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