4,969 research outputs found

    A Systematic Literature Survey of Unmanned Aerial Vehicle Based Structural Health Monitoring

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    Unmanned Aerial Vehicles (UAVs) are being employed in a multitude of civil applications owing to their ease of use, low maintenance, affordability, high-mobility, and ability to hover. UAVs are being utilized for real-time monitoring of road traffic, providing wireless coverage, remote sensing, search and rescue operations, delivery of goods, security and surveillance, precision agriculture, and civil infrastructure inspection. They are the next big revolution in technology and civil infrastructure, and it is expected to dominate more than $45 billion market value. The thesis surveys the UAV assisted Structural Health Monitoring or SHM literature over the last decade and categorize UAVs based on their aerodynamics, payload, design of build, and its applications. Further, the thesis presents the payload product line to facilitate the SHM tasks, details the different applications of UAVs exploited in the last decade to support civil structures, and discusses the critical challenges faced in UASHM applications across various domains. Finally, the thesis presents two artificial neural network-based structural damage detection models and conducts a detailed performance evaluation on multiple platforms like edge computing and cloud computing

    How much does a man cost? A dirty, dull, and dangerous application

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    Thesis (M.A.) University of Alaska Fairbanks, 2017This study illuminates the many abilities of Unmanned Aerial Vehicles (UAVs). One area of importance includes the UAV's capability to assist in the development, implementation, and execution of crisis management. This research focuses on UAV uses in pre and post crisis planning and accomplishments. The accompaniment of unmanned vehicles with base teams can make crisis management plans more reliable for the general public and teams faced with tasks such as search and rescue and firefighting. In the fight for mass acceptance of UAV integration, knowledge and attitude inventories were collected and analyzed. Methodology includes mixed method research collected by interviews and questionnaires available to experts and ground teams in the UAV fields, mining industry, firefighting and police force career field, and general city planning crisis management members. This information was compiled to assist professionals in creation of general guidelines and recommendations for how to utilize UAVs in crisis management planning and implementation as well as integration of UAVs into the educational system. The results from this study show the benefits and disadvantages of strategically giving UAVs a role in the construction and implementation of crisis management plans and other areas of interest. The results also show that the general public is lacking information and education on the abilities of UAVs. This education gap shows a correlation with negative attitudes towards UAVs. Educational programs to teach the public benefits of UAV integration should be implemented

    Benchmarking Image Processing Algorithms for Unmanned Aerial System-Assisted Crack Detection in Concrete Structures

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    This paper summarizes the results of traditional image processing algorithms for detection of defects in concrete using images taken by Unmanned Aerial Systems (UASs). Such algorithms are useful for improving the accuracy of crack detection during autonomous inspection of bridges and other structures, and they have yet to be compared and evaluated on a dataset of concrete images taken by UAS. The authors created a generic image processing algorithm for crack detection, which included the major steps of filter design, edge detection, image enhancement, and segmentation, designed to uniformly compare dierent edge detectors. Edge detection was carried out by six filters in the spatial (Roberts, Prewitt, Sobel, and Laplacian of Gaussian) and frequency (Butterworth and Gaussian) domains. These algorithms were applied to fifty images each of defected and sound concrete. Performances of the six filters were compared in terms of accuracy, precision, minimum detectable crack width, computational time, and noise-to-signal ratio. In general, frequency domain techniques were slower than spatial domain methods because of the computational intensity of the Fourier and inverse Fourier transformations used to move between spatial and frequency domains. Frequency domain methods also produced noisier images than spatial domain methods. Crack detection in the spatial domain using the Laplacian of Gaussian filter proved to be the fastest, most accurate, and most precise method, and it resulted in the finest detectable crack width. The Laplacian of Gaussian filter in spatial domain is recommended for future applications of real-time crack detection using UAS

    A Review on Potential Applications of Unmanned Aerial Vehicle for Construction Industry

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    In the recent years, the Unmanned Aerial Vehicles (UAVs) have been greatly used for different construction and operation applications of various types of construction projects. The main purpose of this paper is briefly reviewing the UAVs in the construction industry. In the building and construction industry, sustainable construction involves different issues among them, the design and management of projects can be named. In recent years, different types of technologies helped improve the management of projects; one of them is the Unmanned Aerial Vehicle (UAV). As a real-time capturing of data technology, UAV is used in the construction industry

    Small unmanned airborne systems to support oil and gas pipeline monitoring and mapping

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    Acknowledgments We thank Johan Havelaar, Aeryon Labs Inc., AeronVironment Inc. and Aeronautics Inc. for kindly permitting the use of materials in Fig. 1.Peer reviewedPublisher PD

    Unmanned aerial vehicles (UAVs) for inspection in construction and building industry

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    Digital data capture is a key component of Industry 4.0 practices. In the past few decades Unmanned Aerial Vehicles (UAVs) have entered the construction industry to capture site data and to cover topographic as well as different types of inspection matters. Photographs, live video, photogrammetric digital elevation models and 3D point clouds can be generated using different photogrammetry facilities, cameras and lasers attached to either a fixed wing or rotorcraft UAVs. UAVs have the ability to deliver information by monitoring, 3Dmaping, measuring, analysing, as well as recording on-site activities. This paper presents the state of art of UAVs usage in construction and building industry and evaluates their applications by experimental case studies. The challenges of using UAVs and their links to BIM will be also discussed. This study found that visual imaging is currently the most popular use of UAVs on construction sites to ensure integrity of structural inspection, however, 3D models derived from LiDAR and photogrammetry techniques are surpassing more traditional methods as they are still significantly cheaper and faster to use. UAVs is also used to monitor workers on site to identify what resources they need in order to carry out their tasks more efficiently and also for the purposes of their health and safety. Despite the approved efficiency of using UAVs on sites to provide better visualization of the working environment, there are still key issues to be tackled such as: the limited flight time of UAVs and its weight. Structural/site investigations have shown that there are some defects on the use of aerial vehicles, with the most important to be the cost along with the precision of the results which may vary depending on the technologies used. There is further study required into the combination of UAVs derived data and its inclusion into BIM, as barriers remain regarding translatable data platforms. There are also some ethical concerns of surveying workers on site and how to protect their privacy

    Bridge Inspection: Human Performance, Unmanned Aerial Systems and Automation

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    Unmanned aerial systems (UASs) have become of considerable private and commercial interest for a variety of jobs and entertainment in the past 10 years. This paper is a literature review of the state of practice for the United States bridge inspection programs and outlines how automated and unmanned bridge inspections can be made suitable for present and future needs. At its best, current technology limits UAS use to an assistive tool for the inspector to perform a bridge inspection faster, safer, and without traffic closure. The major challenges for UASs are satisfying restrictive Federal Aviation Administration regulations, control issues in a GPS-denied environment, pilot expenses and availability, time and cost allocated to tuning, maintenance, post-processing time, and acceptance of the collected data by bridge owners. Using UASs with self-navigation abilities and improving image-processing algorithms to provide results near real-time could revolutionize the bridge inspection industry by providing accurate, multi-use, autonomous three-dimensional models and damage identification

    Impact of UAV Hardware Options on Bridge Inspection Mission Capabilities

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    Uncrewed Aerial Vehicles (UAV) constitute a rapidly evolving technology field that is becoming more accessible and capable of supplementing, expanding, and even replacing some traditionally manual bridge inspections. Given the classification of the bridge inspection types as initial, routine, in-depth, damage, special, and fracture critical members, specific UAV mission requirements can be developed, and their suitability for UAV application examined. Results of a review of 23 applications of UAVs in bridge inspections indicate that mission sensor and payload needs dictate the UAV configuration and size, resulting in quadcopter configurations being most suitable for visual camera inspections (43% of visual inspections use quadcopters), and hexa- and octocopter configurations being more suitable for higher payload hyperspectral, multispectral, and Light Detection and Ranging (LiDAR) inspections (13%). In addition, the number of motors and size of the aircraft are the primary drivers in the cost of the vehicle. 75% of vehicles rely on GPS for navigation, and none of them are capable of contact inspections. Factors that limit the use of UAVs in bridge inspections include the UAV endurance, the capability of navigation in GPS deprived environments, the stability in confined spaces in close proximity to structural elements, and the cost. Current research trends in UAV technologies address some of these limitations, such as obstacle detection and avoidance methods, autonomous flight path planning and optimization, and UAV hardware optimization for specific mission requirements
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