Search results for "Road pavement distre"
showing 5 items of 5 documents
Exploiting Low-Cost 3D Imagery for the Purposes of Detecting and Analyzing Pavement Distresses
2020
Road pavement conditions have significant impacts on safety, travel times, costs, and environmental effects. It is the responsibility of road agencies to ensure these conditions are kept in an acceptable state. To this end, agencies are tasked with implementing pavement management systems (PMSs) which effectively allocate resources towards maintenance and rehabilitation. These systems, however, require accurate data. Currently, most agencies rely on manual distress surveys and as a result, there is significant research into quick and low-cost pavement distress identification methods. Recent proposals have included the use of structure-from-motion techniques based on datasets from unmanned a…
Image-based 3D reconstruction using traditional and UAV datasets for analysis of road pavement distress
2018
Abstract On local and urban networks, the enduring issue of scarce resources for Maintenance, Rehabilitation, and Reconstruction strategies (MR&R) has led, in many cases, to using unadjusted or poor techniques for road pavement distress detection and analysis, yielding ineffective or even counterproductive results. Therefore, it is necessary to have tools that can carry out quick, reliable and low-cost assessment surveys. This paper aims at validating the use of innovative and low-cost technologies for road pavement analysis, assessing their potentialities for improving the automation and reliability of distress detection. A Structure from Motion (SfM) technique is analyzed at different alt…
Towards Low-Cost Pavement Condition Health Monitoring and Analysis Using Deep Learning
2020
Governments are faced with countless challenges to maintain conditions of road networks. This is due to financial and physical resource deficiencies of road authorities. Therefore, low-cost automated systems are sought after to alleviate these issues and deliver adequate road conditions for citizens. There have been several attempts at creating such systems and integrating them within Pavement management systems. This paper utilizes replicable deep learning techniques to carry out hotspot analyses on urban road networks highlighting important pavement distress types and associated severities. Following this, analyses were performed illustrating how the hotspot analysis can be carried out to…
Image-based 3D reconstruction using traditional and mobile-phone data-sets for road pavement distress analysis
2021
The issue of road networks being in deplorable conditions is one that is widespread globally. One of the main precursors for this is that when preparing maintenance management systems, many road agencies rely on data which is often outdated or inaccurate. This is due in many cases to insufficient budgets which are unable to adequately address both maintenance and rehabilitation. It is therefore critical that road agencies have better tools at their disposal to help combat these issues. One of the possible techniques that have been identified is the use of structure from motion techniques to adequately identify road pavement distresses. This paper advances previous work in this area and expl…
Smart Monitoring of Civil Infrastructures
2022
In this presentation, I will show a case study of smart monitoring applied on pavement road to detect the distresses and verify the real state of life of the infrastructures. The methodology used is based on the photogrammetric technique that allow us to carry out a 3D model that has the follow features: low cost process, low time process, user friendly, repeatability. These features consent to make a planning with frequently acquisition to guarantee a reliability monitoring. It works with the comparison between the dense clouds of the 3D models acquired in different moment: the mean square distance between the dense clouds shows where there has been a new distress or an increasing of an ol…