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pothole Detection and Warning System for Indian Roads

机译:印度道路的坑洞检测与警戒系统

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This paper is based on an application of mobile sensing: sensing and gathering the surface condition of roads. We will fabricate a system and mention the required algorithms to sense the road anomalies by making a portable sensor that can be equipped in any car or public transport. We will call this system pothole detection system (PDS), it will use the mobility of the particular vehicle on which the system will be fitted, and side by side gather data from the vibrations and the GPS sensors, and further process and filter the data to monitor road surface condition. At first, we will deploy the PDS on our own vehicle and test it out in a particular sector of Noida. Using the machine learning approach, we were able to identify and classify the potholes and other road anomalies from the accelerometer data. From the continuous testing and gathering data on a particular stretch of road, we were able to put an algorithm that will successfully detect a pothole with 4.3% chance of failure or if the pothole is too small to be detected. It was further conducted a manual inspection if the reported potholes and found that 80% of the road anomalies reported are in need of serious repair.
机译:本文基于移动感应的应用:感应和收集道路的表面状况。我们将通过制作可在任何汽车或公共交通工具的便携式传感器来制作一个系统并提及所需的算法来感测道路异常。我们将调用该系统坑洞检测系统(PDS),它将使用该系统将使用该系统的移动性,在此处安装系统,并并排收集来自振动和GPS传感器的数据,以及进一步的处理和过滤数据监控路面状况。首先,我们将在我们自己的车上部署PDS并在诺伊达的特定部门中测试。使用机器学习方法,我们能够从加速度计数据识别和分类坑洼和其他道路异常。从特定的道路上的连续测试和收集数据来看,我们能够将一个算法成功地检测到4.3%的故障机会或者坑洞太小而无法检测到坑道。如果报告的坑洼并发现报告的80%的道路异常需要严重修复,则进一步进行了手动检查。

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