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Design and implementation of PAVEMON: A GIS web-based pavement monitoring system based on large amounts of heterogeneous sensors data.

机译:PAVEMON的设计和实现:基于GIS网络的基于大量异构传感器数据的路面监测系统。

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摘要

A web-based PAVEment MONitoring system, PAVEMON, is a GIS oriented platform for accommodating, representing, and leveraging data from a multi-modal mobile sensor system. Stated sensor system consists of acoustic, optical, electromagnetic, and GPS sensors and is capable of producing as much as 1 Terabyte of data per day. Multi-channel raw sensor data (microphone, accelerometer, tire pressure sensor, video) and processed results (road profile, crack density, international roughness index, micro texture depth, etc.) are outputs of this sensor system. By correlating the sensor measurements and positioning data collected in tight time synchronization, PAVEMON attaches a spatial component to all the datasets. These spatially indexed outputs are placed into an Oracle database which integrates seamlessly with PAVEMON's web-based system.;The web-based system of PAVEMON consists of two major modules: 1) a GIS module for visualizing and spatial analysis of pavement condition information layers, and 2) a decision-support module for managing maintenance and repair (M&R;) activities and predicting future budget needs. PAVEMON weaves together sensor data with third-party climate and traffic information from the National Oceanic and Atmospheric Administration (NOAA) and Long Term Pavement Performance (LTPP) databases for an organized data driven approach to conduct pavement management activities.;PAVEMON deals with heterogeneous and redundant observations by fusing them for jointly-derived higher-confidence results. A prominent example of the fusion algorithms developed within PAVEMON is a data fusion algorithm used for estimating the overall pavement conditions in terms of ASTM's Pavement Condition Index (PCI). PAVEMON predicts PCI by undertaking a statistical fusion approach and selecting a subset of all the sensor measurements. Other fusion algorithms include noise-removal algorithms to remove false negatives in the sensor data in addition to fusion algorithms developed for identifying features on the road. PAVEMON offers an ideal research and monitoring platform for rapid, intelligent and comprehensive evaluation of tomorrow's transportation infrastructure based on up-to-date data from heterogeneous sensor systems.
机译:基于Web的PAVEment监控系统PAVEMON是面向GIS的平台,用于容纳,表示和利用来自多模式移动传感器系统的数据。状态传感器系统由声学,光学,电磁和GPS传感器组成,每天能够产生多达1 TB的数据。多通道原始传感器数据(麦克风,加速计,轮胎压力传感器,视频)和处理结果(道路轮廓,裂缝密度,国际粗糙度指数,微观纹理深度等)是该传感器系统的输出。通过关联紧密的时间同步中收集的传感器测量值和定位数据,PAVEMON将空间分量附加到所有数据集。这些空间索引的输出被放置到Oracle数据库中,该数据库与PAVEMON的基于Web的系统无缝集成。; PAVEMON的基于Web的系统包括两个主要模块:1)GIS模块,用于可视化和空间分析路面状况信息层, 2)决策支持模块,用于管理维护和维修(M&R;)活动并预测未来的预算需求。 PAVEMON将传感器数据与来自美国国家海洋和大气管理局(NOAA)和长期路面性能(LTPP)数据库的第三方气候和交通信息结合在一起,以进行有组织的数据驱动方法来进行路面管理活动。通过将它们融合以获得共同的更高置信度的结果,可以得到多余的观察结果。 PAVEMON中开发的融合算法的一个突出示例是一种数据融合算法,用于根据ASTM的路面状况指数(PCI)估算总体路面状况。 PAVEMON通过采取统计融合方法并选择所有传感器测量的子集来预测PCI。除了为识别道路特征而开发的融合算法外,其他融合算法还包括去除传感器数据中的假阴性的噪声消除算法。 PAVEMON提供了理想的研究和监控平台,可基于来自异构传感器系统的最新数据对未来的运输基础设施进行快速,智能和全面的评估。

著录项

  • 作者

    Shahini Shamsabadi, Salar.;

  • 作者单位

    Northeastern University.;

  • 授予单位 Northeastern University.;
  • 学科 Engineering Civil.;Remote Sensing.;Computer Science.
  • 学位 M.S.
  • 年度 2015
  • 页码 103 p.
  • 总页数 103
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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