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Real Time Air Quality Monitoring by Using Internet Video Surveillance Camera

机译:使用互联网视频监控摄像机进行实时空气质量监测

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摘要

Nowadays internet video surveillance cameras are widely use in security monitoring. The quantities of installations of these cameras also become more and more. This paper reports that the internet video surveillance cameras can be applied as a remote sensor for monitoring the concentrations of particulate matter less than 10 micron (PM10), so that real time air quality can be monitored at multi location simultaneously. An algorithm was developed based on the regression analysis of relationship between the measured reflectance components from a surface material and the atmosphere. This algorithm converts multispectral image pixel values acquired from these cameras into quantitative values of the concentrations of PM10. These computed PM10 values were compared to other standard values measured by a DustTrak~TM meter. The correlation results showed that the newly develop algorithm produced a high degree of accuracy as indicated by high correlation coefficient (R~2) and low root-mean-square-error (RMS) values. The preliminary results showed that the accuracy produced by this internet video surveillance camera is slightly better than that from the internet protocol (IP) camera. Basically the spatial resolution of images acquired by the IP camera was poorer compared to the internet video surveillance camera. This is because the images acquired by IP camera had been compressed and there was no compression for the images from the internet video surveillance camera.
机译:如今,网络视频监控摄像机已广泛用于安全监控中。这些摄像机的安装数量也越来越多。本文报告说,互联网视频监控摄像机可以用作遥感器,以监测小于10微米(PM10)的颗粒物浓度,从而可以在多个位置同时监测实时空气质量。基于对表面材料和大气的反射系数之间的关系进行回归分析,开发了一种算法。该算法将从这些摄像机获取的多光谱图像像素值转换为PM10浓度的定量值。将这些计算出的PM10值与DustTrakTM仪测得的其他标准值进行比较。相关结果表明,如高相关系数(R〜2)和低均方根误差(RMS)值所示,新开发的算法产生了很高的准确性。初步结果表明,此互联网视频监控摄像机所产生的准确性略高于互联网协议(IP)摄像机。基本上,与互联网视频监控摄像机相比,IP摄像机获取的图像的空间分辨率差。这是因为IP摄像机获取的图像已被压缩,互联网视频监控摄像机的图像没有压缩。

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