Edge Video Analytics: A Survey on Applications, Systems and Enabling Techniques

IF 34.4 1区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

IEEE Communications Surveys and Tutorials Pub Date : 2023-10-10 DOI:10.1109/COMST.2023.3323091

Renjie Xu;Saiedeh Razavi;Rong Zheng

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引用次数: 0

Abstract

Video, as a key driver in the global explosion of digital information, can create tremendous benefits for human society. Governments and enterprises are deploying innumerable cameras for a variety of applications, e.g., law enforcement, emergency management, traffic control, and security surveillance, all facilitated by video analytics (VA). This trend is spurred by the rapid advancement of deep learning (DL), which enables more precise models for object classification, detection, and tracking. Meanwhile, with the proliferation of Internet-connected devices, massive amounts of data are generated daily, overwhelming the cloud. Edge computing, an emerging paradigm that moves workloads and services from the network core to the network edge, has been widely recognized as a promising solution. The resulting new intersection, edge video analytics (EVA), begins to attract widespread attention. Nevertheless, only a few loosely-related surveys exist on this topic. The basic concepts of EVA (e.g., definition, architectures) were not fully elucidated due to the rapid development of this domain. To fill these gaps, we provide a comprehensive survey of the recent efforts on EVA. In this paper, we first review the fundamentals of edge computing, followed by an overview of VA. EVA systems and their enabling techniques are discussed next. In addition, we introduce prevalent frameworks and datasets to aid future researchers in the development of EVA systems. Finally, we discuss existing challenges and foresee future research directions. We believe this survey will help readers comprehend the relationship between VA and edge computing, and spark new ideas on EVA.

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边缘视频分析:应用、系统和使能技术综述

视频作为全球数字信息爆炸的关键驱动力，可以为人类社会创造巨大的利益。政府和企业正在为各种应用部署无数摄像机，例如，执法、应急管理、交通控制和安全监控，所有这些都得益于视频分析(VA)。这一趋势是由深度学习(DL)的快速发展所推动的，它为目标分类、检测和跟踪提供了更精确的模型。与此同时，随着联网设备的激增，每天都会产生大量数据，使云计算不堪重负。边缘计算是一种将工作负载和服务从网络核心转移到网络边缘的新兴范式，已被广泛认为是一种有前途的解决方案。由此产生的新交叉领域——边缘视频分析(EVA)开始引起广泛关注。然而，关于这一主题的调查很少。由于该领域的快速发展，EVA的基本概念(例如，定义、体系结构)没有得到充分阐明。为了填补这些空白，我们对经济增加值的最新工作进行了全面的调查。在本文中，我们首先回顾了边缘计算的基础知识，然后概述了EVA。接下来讨论了EVA系统及其使能技术。此外，我们介绍了流行的框架和数据集，以帮助未来的研究人员在EVA系统的发展。最后，讨论了当前面临的挑战，展望了未来的研究方向。我们相信这项调查将有助于读者理解增值价值和边缘计算之间的关系，并激发出关于增值价值的新想法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Communications Surveys and Tutorials COMPUTER SCIENCE, INFORMATION SYSTEMS-TELECOMMUNICATIONS

CiteScore

80.20

自引率

2.50%

发文量

审稿时长

6 months

期刊介绍： IEEE Communications Surveys & Tutorials is an online journal published by the IEEE Communications Society for tutorials and surveys covering all aspects of the communications field. Telecommunications technology is progressing at a rapid pace, and the IEEE Communications Society is committed to providing researchers and other professionals the information and tools to stay abreast. IEEE Communications Surveys and Tutorials focuses on integrating and adding understanding to the existing literature on communications, putting results in context. Whether searching for in-depth information about a familiar area or an introduction into a new area, IEEE Communications Surveys & Tutorials aims to be the premier source of peer-reviewed, comprehensive tutorials and surveys, and pointers to further sources. IEEE Communications Surveys & Tutorials publishes only articles exclusively written for IEEE Communications Surveys & Tutorials and go through a rigorous review process before their publication in the quarterly issues. A tutorial article in the IEEE Communications Surveys & Tutorials should be designed to help the reader to become familiar with and learn something specific about a chosen topic. In contrast, the term survey, as applied here, is defined to mean a survey of the literature. A survey article in IEEE Communications Surveys & Tutorials should provide a comprehensive review of developments in a selected area, covering its development from its inception to its current state and beyond, and illustrating its development through liberal citations from the literature. Both tutorials and surveys should be tutorial in nature and should be written in a style comprehensible to readers outside the specialty of the article.