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首页> 外文期刊>Sensors Journal, IEEE >Automated Moving Object Classification in Wireless Multimedia Sensor Networks
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Automated Moving Object Classification in Wireless Multimedia Sensor Networks

机译：无线多媒体传感器网络中的自动移动对象分类

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The use of wireless multimedia sensor networks (WMSNs) for surveillance applications has attracted the interest of many researchers. As with traditional sensor networks, it is easy to deploy and operate WMSNs. With inclusion of multimedia devices in wireless sensor networks, it is possible to provide data to users that is more meaningful than that provided by scalar sensor-based systems alone; however, producing, storing, processing, analyzing, and transmitting multimedia data in sensor networks requires consideration of additional constraints, including energy, processing power, storage capacity, and communication. Furthermore, as multimedia sensors produce much more data than scalar sensors, more manpower is required to analyze multimedia data. To overcome these constraints and challenges, this paper aimed to propose a system architecture and a set of procedures for WMSNs that facilitate automatic classification of moving objects using scalar and multimedia sensors. Methods and standards for detecting and classifying a moving object, as well as transmission of the results, are described in detail. The hardware for each sensor node includes a built-in camera, a passive infrared motion sensor, a vibration sensor, and an acoustic sensor. An application using our proposed methods was developed and embedded in the multimedia sensor node. In addition, a sink station was set up and the data produced by the sensor network was collected by this server. The classification performance of the application was tested using video recorded by the sensor node. The effect of the proposed methods on power consumption was also tested and measured. The experimental results show that the proposed approach is sufficiently lightweight to be used for real-world surveillance applications.
机译：在监视应用中使用无线多媒体传感器网络（WMSN）吸引了许多研究人员的兴趣。与传统的传感器网络一样，它易于部署和操作WMSN。通过在无线传感器网络中包含多媒体设备，可以为用户提供比仅基于标量传感器的系统提供的数据更有意义的数据。但是，在传感器网络中产生，存储，处理，分析和传输多媒体数据需要考虑其他约束条件，包括能量，处理能力，存储容量和通信。此外，由于多媒体传感器比标量传感器产生更多的数据，因此需要更多的人力来分析多媒体数据。为了克服这些限制和挑战，本文旨在为WMSN提出一种系统架构和一套程序，以利于使用标量和多媒体传感器对运动对象进行自动分类。详细描述了对运动物体进行检测和分类以及结果传输的方法和标准。每个传感器节点的硬件包括内置摄像机，被动红外运动传感器，振动传感器和声学传感器。使用我们提出的方法开发了一个应用程序，并将其嵌入到多媒体传感器节点中。此外，还建立了一个接收站，并由该服务器收集了传感器网络产生的数据。使用传感器节点记录的视频测试了应用程序的分类性能。还测试和测量了所提出方法对功耗的影响。实验结果表明，所提出的方法足够轻巧，可用于现实世界的监视应用程序。

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