干旱区生态环境知识资源中心(Arid): Towards an Machine Learning-Based Edge Computing Oriented Monitoring System for the Desert Border Surveillance Use Case

Arid

DOI	10.1109/ACCESS.2020.3042699
	Towards an Machine Learning-Based Edge Computing Oriented Monitoring System for the Desert Border Surveillance Use Case
	Bellazi, Khalifa M.; Marino, Rodrigo; Lanza-Gutierrez, Jose M.; Riesgo, Teresa
通讯作者	Bellazi, KM
来源期刊	IEEE ACCESS
ISSN	2169-3536
出版年	2020
卷号	8 页码:218304-218322
英文摘要	The design of border surveillance systems is critical for most countries in the world, having each border specific needs. This paper focuses on an Internet of Things oriented surveillance system to be deployed in the Sahara Desert, which is composed of many unattended fixed platforms, where the nodes in the edge have a Forward Looking InfraRed (FLIR) camera for field monitoring. To reduce communications and decentralise the processing, IR images should be fully computed on the edge by an Automated Target Recognition (ATR) algorithm, tracking and identifying targets of interest. As edge nodes are constrained in energy and computing capacity, this work proposes two ATR systems to be executed in low-power microprocessors. Both proposals are based on using Bag-of-Features for feature extraction and a supervised algorithm for classification, both differing in segmenting the InfraRed image in regions of interest or working directly with the whole image. Both proposals are successfully applied to infer about a dataset generated to this end, getting a trade-off between computing cost and detection capacity. As a result, the authors obtained a detection capacity of up to 97% and a frame rate of up to 5.71 and 59.17, running locally on the edge device and the workstation, respectively.
英文关键词	Automatic target recognition approximate computing bag of features border surveillance classification edge computing Internet of Things machine learning Sahara desert
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000597790900001
WOS关键词	RECOGNITION ; FEATURES ; INTERNET
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS研究方向	Computer Science ; Engineering ; Telecommunications
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/327887
作者单位	[Bellazi, Khalifa M.; Marino, Rodrigo; Riesgo, Teresa] Univ Politecn Madrid, Ctr Elect Ind, Escuela Tecn Super Ingn Ind, Madrid 28040, Spain; [Lanza-Gutierrez, Jose M.] Univ Alcala De Henares, Dept Comp Sci, Alcala De Henares 28871, Spain
推荐引用方式 GB/T 7714	Bellazi, Khalifa M.,Marino, Rodrigo,Lanza-Gutierrez, Jose M.,et al. Towards an Machine Learning-Based Edge Computing Oriented Monitoring System for the Desert Border Surveillance Use Case[J],2020,8:218304-218322.
APA	Bellazi, Khalifa M.,Marino, Rodrigo,Lanza-Gutierrez, Jose M.,&Riesgo, Teresa.(2020).Towards an Machine Learning-Based Edge Computing Oriented Monitoring System for the Desert Border Surveillance Use Case.IEEE ACCESS,8,218304-218322.
MLA	Bellazi, Khalifa M.,et al."Towards an Machine Learning-Based Edge Computing Oriented Monitoring System for the Desert Border Surveillance Use Case".IEEE ACCESS 8(2020):218304-218322.