Data Collection System for a Rapid Recovery Work: Using Digital Photogrammetry and a Small Unmanned Aerial Vehicle (UAV)

Yamamoto, T.; Kusumoto, Hiroshi; Banjo, Katsuhisa

doi:10.1061/9780784413616.109

Cited by 6 publications

(7 citation statements)

References 2 publications

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“…Michael et al (2012) used a UAS and a ground robot to map the layout of an earthquake-damaged building; the study found that aerial robots can maneuver through and gather data from vantages that are inaccessible to ground robots and the hovering capability made UASs well-suited for observation and inspection tasks. Yamamoto et al (2014) used UAS to assess the collapsed areas of slopes and river revetments; they explained that the accuracy of close-photogrammetric software would be reduced if photos taken are close to each other, which is often the limitation of ground photo collection methods. Kerle et al (2014) used UAS to collect damage information of roofs and facades on selected buildings; they stated that UAS-assisted survey was more controlled and flexible than Pictometry-type systems and required lower cost.…”

Section: Unmanned Aerial System Applications In Constructionmentioning

confidence: 99%

Unmanned aerial system applications in construction: a systematic review

Zhou

Gheisari

2018

104

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Purpose Over the past decade, researchers have used unmanned aerial systems (UASs) in construction industry for various applications from site inspection to safety monitoring or building maintenance. This paper aims to assort academic studies on construction UAS applications, summarize logics behind using UAS in each application and extend understanding of current state of UAS research in the construction setting. Design/methodology/approach This research follows a systematic literature assessment methodology to summarize the results of 54 research papers over the past ten years and outlines the research trends for applying UASs in construction. Findings UASs are used in building inspection, damage assessment, site surveying, safety inspection, progress monitoring, building maintenance and other construction applications. Cost saving, time efficiency and improved accessibility are the primary reasons for choosing UAS in construction applications. Rotary-wing UASs are the most common types of UASs being used in construction. Cameras, LiDAR and Kinect are the most common onboard sensors integrated in construction UAS applications. The control styles used are manual, semi-autonomous and autonomous. Originality/value This paper contributes to classification of UAS applications in construction research and identification of UAS hardware and sensor types as well as their flying control systems in construction literature.

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Section: Unmanned Aerial System Applications In Constructionmentioning

confidence: 99%

Unmanned aerial system applications in construction: a systematic review

Zhou

Gheisari

2018

104

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“…UAVs can quickly obtain aerial imagery, which can be used to up-date hazard maps and develop dense surface and elevation models (Erdejl et al 2017;Yamamoto et al 2014). Postdisaster, dangerous obstacles can hinder human teams on the ground which can be avoided (as least partly) with the use of UAVs (Greenwood et al 2019).…”

Section: Post-disaster Response Assessmentsmentioning

confidence: 99%

“…For example, if a bridge or building is damaged during earthquake or fire after earthquake, it is not safe to be assessed by human inspectors in the field. SHM using UAV imagery can accelerate the inspection and reconstruction phases (Adams and Friedland 2011;Erdejl et al 2017;Yamamoto et al 2014) as necessary data can be provided more quickly and safely. Pratt et al (2008) investigated the Berkman Plaza collapse in Jacksonville in 2007 using a tethered UAV.…”

Section: Post-disaster Response Assessmentsmentioning

confidence: 99%

Aerial robotic technologies for civil engineering: established and emerging practice

Freeman

Kashani

Vardanega

2021

J. Unmanned Veh. Sys.

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Aerial robotic technology has potential for use in a wide variety of civil engineering applications. Such technology potentially offers low-cost methods to replace expensive structural health monitoring activities such as visual inspection. Aerial robots also have potential uses in civil construction and for regional surveys. This paper presents the results of a review on the applications of aerial robotic technology in civil engineering. Such civil engineering applications can be classified into three broad areas: (i) monitoring and inspection of civil infrastructure; (ii) site management, robotic construction, and maintenance and (iii) post-disaster response surveys and rapid damage assessments. The motivations for uptake of aerial robotics in the civil engineering industry generally fall into the following categories: (i) cost savings, (ii) improved measurement capability and (iii) safety improvements. The categories of aerial robotic use in civil engineering are then classified as either ‘established’ or ‘emerging’ uses.

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“…(2) damage assessment, where the data collected by UAVs are used to assess the damage to buildings after disasters [23][24][25][26];…”

Section: Uavs For Building Deterioration Detection Currentlymentioning

confidence: 99%

Application of Deep Learning and Unmanned Aerial Vehicle on Building Maintenance

Kung

Pan

Wang

et al. 2021

Advances in Civil Engineering

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Several natural and human factors are responsible for the defacement of the external walls and tiles of buildings, and the related deterioration can be a public safety hazard. Therefore, active building maintenance and repair processes are essential for ensuring building sustainability. However, conventional inspection methods are time-, cost-, and labor-intensive processes. Therefore, herein, this study proposes a convolutional neural network (CNN) model for image-based automated detection and localization of key building defects (efflorescence, spalling, cracking, and defacement). Based on a pretrained CNN VGG-16 classifier, this model applies class activation mapping for object localization. After identifying its limitations in real-life applications, this study determined the model’s robustness and ability to accurately detect and localize defects in the external wall tiles of buildings. For real-time detection and localization, this study applied this model by using mobile devices and drones. The results show that the application of deep learning with UAV can effectively detect various kinds of external wall defects and improve the detection efficiency.

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Data Collection System for a Rapid Recovery Work: Using Digital Photogrammetry and a Small Unmanned Aerial Vehicle (UAV)

Cited by 6 publications

References 2 publications

Unmanned aerial system applications in construction: a systematic review

Unmanned aerial system applications in construction: a systematic review

Aerial robotic technologies for civil engineering: established and emerging practice

Application of Deep Learning and Unmanned Aerial Vehicle on Building Maintenance

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