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Real Time Density Based Traffic Surveillance System Integrated with Acoustic Based Emergency Vehicle Detection

机译:基于实时密度的交通监控系统与基于声学的应急车辆检测

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As the problem of traffic congestion is prevalent in many metropolitan cities there is an urgent need for a traffic surveillance system which regulates the traffic in an efficient way. The current conventional methods such as timer based traffic control system is proved to be inferior to solve this issue and also the current systems does not give priority in the cases where emergency vehicles are detected. In this paper a smart traffic surveillance system has implemented where the access will be given to the lane having the highest density of traffic in the absence of emergency vehicle. When an emergency vehicle is detected in any lane, the priority shifts to the lane in which the emergency vehicle is present. Digital image processing techniques are used to compute the density of traffic and signal processing techniques are used to detect the presence of an emergency vehicle. The complete proposed system, from image and sound acquisition to canny edge detection and noise removal by Least Mean Square(LMS) filter and finally the green signal allotment to the lanes depending on the output results are illustrated with proper schematics and the final results are validated by hardware implementation.
机译:由于交通拥堵问题在许多大都市城市中普遍存在,因此迫切需要以有效的方式调节交通的交通监测系统。现有的传统方法如基于定时器的业务控制系统被证明是较差的,以解决这个问题,并且在检测到应急车辆的情况下,当前系统也不优先考虑。在本文中,智能流量监控系统已经实现了在没有紧急车辆的情况下给予具有最高交通密度的通道的通道。当在任何车道中检测到紧急车辆时,优先级转移到存在紧急车辆的车道。数字图像处理技术用于计算流量的密度,并且信号处理技术用于检测应急车辆的存在。完整的建议系统,从图像和声音获取到Canny Edge检测和噪声去除至少均值方形(LMS)滤波器,并且最后用正确的原理图示出了根据输出结果的绿色信号分配,并用适当的原理图示出了最终结果并验证了最终结果通过硬件实现。

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