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引用次数: 2
摘要
本研究旨在将无线传感器网络(WSNs)应用于矿井巷道环境监测中。无线传感器节点具有摄像机,该摄像机可以实时传输图像信号,以便在无线传感器节点感知到湿度增加、瓦斯浓度增加等异常情况时监测矿井隧道内的状态。图像信号的质量取决于图像群(Group of Pictures, GOP)的结构和量化尺度(quanti量化Scale, Qscale)。本文研究了矿井巷道无线传感器网络中GOP长度和Qscale对图像质量的影响。使用工具- myevalvid - nt将编码后的图像信号转换成跟踪文件,然后在模拟的网络环境-NS2中运行。接收节点接收到的图像文件根据平均PSNR进行检查。仿真结果表明,在设定参数范围内,随着GOP长度和Qscale值的增大,平均PSNR逐渐降低,图像质量变差,这对我们今后研究无线传感器网络在矿井巷道环境监测中的应用具有重要意义。
Analysis of Image Transmission for Wireless Sensor Networks in the Mine Tunnel
The research aimed to use Wireless Sensor Networks(WSNs) applying in the mine tunnel environmental monitoring. The wireless sensor node has a camera which can transmit live image signal in order to monitor the status in the mine tunnel when an exception occurs that the wireless sensor nodes perceived such as humidity increases, gas concentration increases, etc. The quality of image signal depends on Group of Pictures (GOP) structure and Quantization Scale(Qscale). In this paper, the effects of the GOP length and Qscale to the image quality for wireless sensor networks in the mine tunnel are investigated. The encoded image signal converted in to trace files using the tools-MyEvalvid-NT, and then run in a simulated network environment -NS2. The image files which the sink node received are examined in terms of average PSNR. The simulation results indicate that in range of setting parameters, by increasing the GOP length and the value of Qscale, the average PSNR decreases gradually, the image quality is worse, which is significant for our future research on wireless sensor networks applying in the mine tunnel environmental monitoring.