邓晓衡

教授 博士生导师 硕士生导师

入职时间:2006-01-05

所在单位:电子信息学院

职务:院长

学历:博士研究生毕业

性别:男

联系方式:Email:dxh@csu.edu.cn

学位:博士学位

在职信息:在职

主要任职:湖南省数据传感与交换设备工程中心 主任 IEEE RS Chapter长沙 主席CCF普适计算专委 委员 CCF长沙 执委

毕业院校:中南大学

学科:信息与通信工程
计算机科学与技术

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Y. Liu, C. Zhu, X. Deng, et al. UAV-aided urban target tracking system based on edge computing[J]. arXiv preprint arXiv:1902.00837, 2019.

发布时间:2024-03-13

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发表刊物:arXiv preprint arXiv:1902.00837

摘要:Abstract—Target tracking is an important issue of social security. In order to track a target, traditionally a large amount of surveillance video data need to be uploaded into the cloud for processing and analysis, which put stremendous bandwidth pressure on communication links in access networks and core networks. At the same time, the long delay in wide area network is very likely to cause a tracking system to lose its target. Often, unmanned aerial vehicle (UAV) has been adopted for target tracking due to its flexibility, but its limited flight time due to battery constraint and the blocking by various obstacles in the field pose two major challenges to its target tracking task, which also very likely results in the loss of target. A novel target tracking model that coordinates the tracking by UAV and ground nodes in an edge computing environment is proposed in this study. The model can effectively reduce the communication cost and the long delay of the traditional surveillance camera system that relies on cloud computing, and it can improve the probability of finding a target again after an UAV loses the tracing of that target. It has been demonstrated that the proposed system achieved a significantly better performance in terms of low latency, high reliability, and optimal quality of experience (QoE).

备注:http://faculty.csu.edu.cn/dengxiaoheng/zh_CN/lwcg/10445/content/49258.htm

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  • 51-UAV-aided urban target tracking system based on edge computing.pdf

  • 上一条: F. Zeng, Y. Ren, X. Deng, et al. Cost-effective edge server placement in wireless metropolitan area networks[J]. Sensors, 2018, 19(1): 32.

    下一条: X. Deng, D. Zeng, H. Shen. Causation analysis model: based on AHP and hybrid Apriori-Genetic algorithm[J]. Journal of Intelligent & Fuzzy Systems, 2018, 35(1): 767-778.