UAV-Based IoT Platform: A Crowd Surveillance Use Case
UAV-Based IoT Platform: A Crowd Surveillance Use Case
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DOI：
10.1109/mcom.2017.1600587cm
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发表时间：
2017-02-01
影响因子：
11.2
通讯作者：
Taleb, Tarik
中科院分区：
文献类型：
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作者：
Motlagh, Naser Hossein;Bagaa, Miloud;Taleb, Tarik
无人驾驶飞行器在日益壮大的业余爱好者群体以及服务提供商中越来越受欢迎。诸如LTE 4G/5G网络和移动边缘计算等新兴技术将拓宽无人驾驶飞行器的应用场景。在本文中，我们讨论了配备物联网设备的无人驾驶飞行器在高空提供物联网服务的潜力。本文呈现了一个基于无人驾驶飞行器的综合物联网平台的高层视图，该平台用于从高空提供物联网服务，同时还介绍了整体系统编排器。作为该平台的一个设想用例，本文展示了如何利用无人驾驶飞行器基于人脸识别进行人群监控。为了评估该用例，我们研究了将视频数据处理卸载到移动边缘计算节点与在无人驾驶飞行器上本地处理视频数据的情况。为此，我们开发了一个由一个本地处理节点和一个移动边缘计算节点组成的测试平台。为了进行人脸识别，使用了开源计算机视觉库中的局部二值模式直方图方法。所获得的结果证明了基于移动边缘计算的卸载方法在节省无人驾驶飞行器稀缺能源、减少识别处理时间以及及时发现可疑人员方面的有效性。
Unmanned aerial vehicles are gaining a lot of popularity among an ever growing community of amateurs as well as service providers. Emerging technologies, such as LTE 4G/5G networks and mobile edge computing, will widen the use case scenarios of UAVs. In this article, we discuss the potential of UAVs, equipped with loT devices, in delivering loT services from great heights. A high-level view of a UAV-based integrative loT platform for the delivery of loT services from large height, along with the overall system orchestrator, is presented in this article. As an envisioned use case of the platform, the article demonstrates how UAVs can be used for crowd surveillance based on face recognition. To evaluate the use case, we study the offloading of video data processing to a MEC node compared to the local processing of video data onboard UAVs. For this, we developed a testbed consisting of a local processing node and one MEC node. To perform face recognition, the Local Binary Pattern Histogram method from the Open Source Computer Vision is used. The obtained results demonstrate the efficiency of the MEC-based offloading approach in saving the scarce energy of UAVs, reducing the processing time of recognition, and promptly detecting suspicious persons.