The American Society for Testing and Materials (ASTM) is an independent organization devoted to the development of standards.

American Society for Testing and Materials

Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring

Data-driven methods in structural health monitoring (SHM) is gaining popularity due to recent technological advancements in sensors, as well as high-speed internet and cloud-based computation. Since the introduction of deep learning (DL) in civil engineering, particularly in SHM, this emerging and promising tool has attracted significant attention among researchers. The main goal of this paper is to review the latest publications in SHM using emerging DL-based methods and provide readers with an overall understanding of various SHM applications. After a brief introduction, an overview of various DL methods (e.g., deep neural networks, transfer learning, etc.) is presented. The procedure and application of vibration-based, vision-based monitoring, along with some of the recent technologies used for SHM, such as sensors, unmanned aerial vehicles (UAVs), etc. are discussed. The review concludes with prospects and potential limitations of DL-based methods in SHM applications.

Data-Driven Structural Health Monitoring and Damage Detection through Deep Learning: State-of-the-Art Review.

Advent of computationally efficient smartphones, inexpensive high‐resolution cameras, drones, and robotic sensors has brought a new era of next‐generation intelligent monitoring systems for civil infrastructure. Vibration‐based condition assessment has garnered as a prominent method of evaluating the health of large‐scale infrastructure. The use of contact‐based sensors for acquiring vibration data becomes uneconomical and tedious due to their instrumentation cost, centralized nature, and densification required to collect sufficient data for system identification of modern complex structures. A need to advance and develop alternative methods for efficient sensing system results in next‐generation measurement technology of structural health monitoring. The abundance of handheld smartphones with easily programmable framework has helped in modifying relevant software to acquire vibration data using embedded sensors in the smartphone. The inexpensive cameras have been used to capture images and videos that are utilized to understand the structural behavior with the aid of advanced signal processing techniques. The inaccessible components of structures require noncontact sensors such as unmanned aerial vehicles (UAVs) or so‐called drones and mobile sensors to acquire structural data. To the authors' knowledge, this paper first time presents a comprehensive review of a suite of next‐generation smart sensing technology that has been developed in recent years within the context of structural health monitoring. The state‐of‐the‐art methods have been presented by conducting a detailed literature review of the recent applications of smartphones, UAVs, cameras, and robotic sensors used in acquiring and analyzing the vibration data for structural condition monitoring and maintenance.

A literature review of next-generation smart sensing technology in structural health monitoring

For next-generation smart cities, small UAVs (also known as drones) are vital to incorporate in airspace for advancing the transportation systems. This paper presents a review of recent developments in relation to the application of UAVs in three major domains of transportation, namely; road safety, traffic monitoring and highway infrastructure management. Advances in computer vision algorithms to extract key features from UAV acquired videos and images are discussed along with the discussion on improvements made in traffic flow analysis methods, risk assessment and assistance in accident investigation and damage assessments for bridges and pavements. Additionally, barriers associated with the wide-scale deployment of UAVs technology are identified and countermeasures to overcome these barriers are discussed, along with their implications.

Applications of unmanned aerial vehicle (UAV) in road safety, traffic and highway infrastructure management: Recent advances and challenges.

This paper is intended to provide the state-of-the-art and of-the-practice on visual inspection, monitoring, and analysis of infrastructure using unmanned aerial vehicles (UAVs). Several re...

https://www.fpl.fs.fed.us/documnts/pdf2018/fpl_2018_duque003.pdf

Synthesis of Unmanned Aerial Vehicle Applications for Infrastructures

Bridge Deterioration Quantification Protocol Using UAV

The use of Unmanned Aerial Systems (UASs), commonly known as drones, has significantly increased over recent years in the field of civil engineering. In detail, the need for a more efficient altern...

https://www.fpl.fs.fed.us/documnts/pdf2018/fpl_2018_seo001.pdf

Field Application of UAS-Based Bridge Inspection

This paper aims to summarize central findings from a literature review and technical survey on unmanned aerial vehicle (UAV) techniques for bridge inspection and damage quantification. This...

Literature Review and Technical Survey on Bridge Inspection Using Unmanned Aerial Vehicles

Bridge inspection using a drone, also referred to as an unpiloted aircraft system, has gained more interest in recent years among bridge owners, researchers, and stakeholders because of its efficiency and effectiveness. In fact, numerous bridges classified as structurally deficient in the United States that require more attention and effort for maintenance activities can be inspected using drones in an efficient manner. The primary goal of this project was to evaluate drones as supplemental bridge inspection tools for bridges that present accessibility challenges for inspectors. To accomplish this goal, an extensive literature review and technical survey were initially conducted to gain knowledge of the state-of-the-art and practices and critical considerations that should be accounted for while conducting inspections. Also, analysis of the drones was conducted and the most suitable drone for bridge inspections was selected. To recognize the drone-enabled inspection efficiency, preliminary inspections were conducted for structural damage identification in three structures, including a reinforced masonry building and two pedestrian timber deck bridges. With the knowledge and techniques established during the preliminary inspections, a six-stage recommended bridge inspection protocol using the drone was proposed and applied to two in-service highway timber bridges, including a timber arch bridge and a three-span timber girder bridge in South Dakota. Through the acquisition and analysis of image and video data, the effectiveness of the drone platform was evaluated in terms of image quality, damage identification and quantification, and comparisons with results from traditional inspections conducted on the bridges. This study details drone-enabled inspection advantages and challenges and provides conclusions and recommendations for future work. A key finding demonstrated throughout this project was that different types of structural damage on the bridges were efficiently identified using the drone.

https://www.fpl.fs.fed.us/documnts/fplgtr/fpl_gtr258.pdf

Evaluating the use of drones for timber bridge inspection

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

James P. Wacker

Author Tools

Chat about Author