The United Control System of Fog and Haze Distribution Based on Vision Sensing

 Ruan Ya-Duan,Chen Xiang-Jun,Chen Qi-Mei

Journal of Nanjing University(Natural Sciences) ›› 2015, Vol. 51 ›› Issue (2) : 234-242.

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Journal of Nanjing University(Natural Sciences) ›› 2015, Vol. 51 ›› Issue (2) : 234-242.

 The United Control System of Fog and Haze Distribution Based on Vision Sensing

  •  Ruan Ya-Duan,Chen Xiang-Jun,Chen Qi-Mei
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Abstract

 The dynamic regional distribution of fog and haze reflects pollution source distribution and road traffic situation. It is related to people’s health and driving safety. But the current instruments on visibility and PM2.5 are expensive and the measurement range is so limited. So it’s too costly to increase monitoring points to cover the whole region which makes the sampling data is too sparse to form the regional distribution of fog and haze. Therefore, this paper designs the united control system of fog and haze distribution and security early-warning by means of vision sensing, on the basis of the existing environment monitoring system and the intelligent traffic system (ITS). A new three-dimensional information aggregation network framework is introduced and the massive data center is construction to provide a kind of unified information service interface for the compatibility, information share and interactive among the heterogeneous application systems. The distribution of visibility is obtained based on the camera calibration method and video visibility detection model, taking advantage of a large number of video surveillance of the road network. The intrinsic relationship reveals the regional distribution of PM2.5 with the visibility distribution data through the analysis of correlation on the visibility and particles. The paper also descripts the data processing of the information fusion center in detail and gives some early-warning or auxiliary decision advice for fog and haze monitoring. The experimental system for traffic safety has been applied to the Ning Huai Expressway southern section and plays an important role in the haze black spot of Laoshan hills.

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 Ruan Ya-Duan,Chen Xiang-Jun,Chen Qi-Mei
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 The United Control System of Fog and Haze Distribution Based on Vision Sensing
[J]. Journal of Nanjing University(Natural Sciences), 2015, 51(2): 234-242

References

 [1]. Nicolas H. Automatic fog detection and estimation of visibility distance through use of an onboard camera. Machine Vision and Applications, 2006, 17(1): 8–20.
[2]. Babari R. Visibility monitoring using conventional roadside cameras: Shedding light on and solving a multi-national road safety problem. Annual Meeting Compendium of Papers (TRB’11) Transportation Research Board, Washington, D.C, USA :2011.
[3]. Hautière N, Babari R, Dumont E. Estimating meteorological visibility using cameras: A probabilistic model-driven approach. Computer Science, Computer Vision - ACCV, 2010, 6495:243-254.
[4]. Ling X, Alex C, Shawn N. Estimating atmospheric visibility using general purpose cameras. International Symposium on Advances in Visual Computing. Berlin: Heidelberg, 2008.356–367.
[5]. Liaw J J, Lian S B, Huang Y F, et al. Using sharpness image with haar function for urban atmospheric visibility measurement. Aerosol and Air Quality Research, 2010, 10:323–330.
[6]. Schubert R, Schlingelhof M, Cramer H, et al. Accurate positioning for vehicular safety applications - The SAFESPOT Approach. IEEE 65th Vehicular Technology Conference (VTC2007-Spring). IEEE Press, 2007. 2506-2510.
[7]. Domenichini F, Rossa A,?????????? et al. The Cmmbined fogmonitoring system of arpav over the veneto region.. PO VALLEY–ITALY. 5th International Conference on Fog, Fog Collection and Dew. Germany, http://www. fogconference. Org, 2010, 1(5):80.
[8]. 陈钊正,周庆逵.基于小波变换的视频能见度检测算法研究与实现.仪器仪表学报,2010,31(1):92—98.
[9]. 李勃,董蓉,陈启美.无需人工标记的视频对比度道路能见度检测.计算机辅助设计与图形学学报,2009,11(21):1575—1982.
[10]. 刘虎,孙召敏,陈启美.CUDA架构下H.264快速去块滤波算法.计算机应用,2010,Vol.12.
[11]. Dong R, Li B, Chen Q M. An automatic calibration method for PTZ camera in expressway monitoring system. WRI Word Congress on Computer Science and Information Engineering. 2009(6):636-640.
[12]. 江登表,李勃,陈启美.用于高动态范围图像生成的CCD辐照度标定.光学精密工程,2013,21(11):2980-298.
[13]. Pinoli J C. The logarithmic image processing model: Connections with human brightness perception and contrast estimators. Journal of Mathematical Imaging and Vision, 1997, 7(4): 341-358.
[14]. 丁铭.苏州市“霾”污染变化趋势分析.南京:南京工业大学,2013.
[ 1 5 ]陈钊正, 李 勃, 陈启美等 . 基于分布式监控数字单元系列的高速公路综合管理系统 . 南京大学学报( 自然科学) ,2010,46 (4) : 394~406.

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