IOT BASED STATISTICAL APPROACH FOR HUMAN CROWD DENSITY ESTIMATION-DESIGN AND ANALYSIS

J. Gupta, S. Gupta
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引用次数: 8

Abstract

In this paper we present an IoT based solution that can reduce the complexity of crowd estimation. About the human crowd estimation many technique are in existence but now a day’s more work are going on in the field of IoT, because this is era of IoT and most of the every organization is shifted towards IoT based system. So we are also proposed this system in this field and we are using the Respberry Pi-3 which are having quad core processor that can very useful and gives better result and gives accurate number even in the humans are very close to each others. This IoT based model can easily implements in the crowded areas and monitor the same in this area. The camera module in this model also helps to differentiate between human and other bodies. As this is a mobile model it can easily fix on the walls of street light and in the time of dark or in night the camera capture clear image for process in the presence of street light. So that this model gives better result almost 70% better result in compare to exiting approaches.
基于物联网的人口密度估计统计方法——设计与分析
在本文中,我们提出了一种基于物联网的解决方案,可以降低人群估计的复杂性。关于人群估计,许多技术已经存在,但现在在物联网领域的工作越来越多,因为这是物联网时代,大多数组织都转向了基于物联网的系统。所以我们也在这个领域提出了这个系统,我们使用的是Respberry Pi-3,它有四核处理器,非常有用,可以提供更好的结果,甚至在人类非常接近的时候也能给出准确的数字。这种基于物联网的模型可以很容易地在拥挤的区域实施,并监控该区域的相同情况。这个模型中的相机模块也有助于区分人体和其他身体。由于这是一个可移动的模型,它可以很容易地固定在路灯的墙壁上,在天黑或夜间,相机在路灯的存在下拍摄清晰的图像进行处理。所以这个模型给出了更好的结果几乎70%的结果比现有的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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