基于物联网的道路驼峰和坑洼检测与信息共享

C. Chellaswamy, H. Famitha, T. Anusuya, S. Amirthavarshini
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引用次数: 22

摘要

减少交通事故的方法之一是识别道路上的驼峰和坑洼。本文提出了一种基于物联网的道路监测系统(IoT-RMS),用于识别道路上的坑洼和驼峰。超声传感器的散射信号对受坑洞影响的路径影响很大。因此,由于表面的粗糙度,反射信号的幅度减小,信号幅度难以分析。Kirchofft理论基本适用于实时分析,有一定的局限性。为了克服这一困难,超声波传感器中包含了一个加速度计来测量信号中存在的变化,并使用蜜蜂优化(HBO)技术进行了优化。IoT-RMS会根据云端的位置信息自动更新道路状态。每辆道路车辆都可以从服务器获取信息,并根据道路上的坑洼和驼峰估计速度。仿真结果表明,物联网rms可用于道路车辆,减少事故发生。采用Arduino Uno和ESP 8266对系统进行了实现和测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IoT Based Humps and Pothole Detection on Roads and Information Sharing
One of the ways to reduce road accident is to identify the humps and potholes present in the path. In this paper, an internet of things based road monitoring system (IoT-RMS) is proposed to identify the potholes and humps in the road. The pathway which is affected by the pothole is greatly influenced by the scattering signal of the ultrasonic sensor. So the magnitude of the reflected signal decreased due to the roughness of the surface and the signal amplitude is difficult to analyze. The Kirchofft's theory basically applied for real-time analysis and it has certain limitations. To overcome this difficulty, an accelerometer has been included with the ultrasonic sensor to measure variation present in the signal and optimized using honey bee optimization (HBO) technique. The IoT-RMS automatically updates the status of the road with location information in the cloud. Each road vehicles can access the information from the server and estimate the speed according to the potholes and humps present on the road. The simulation has been done and the result shows that the IoT-RMS can be accommodated in road vehicles to reduce the accidents. The proposed system is implemented and tested using Arduino Uno with ESP 8266.
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