Computer vision-based construction progress monitoring

Reja, Varun Kumar; Varghese, Koshy; Ha, Q.P.

doi:10.1016/j.autcon.2022.104245

Cited by 72 publications

(30 citation statements)

References 68 publications

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“…Cameras are cheap, portable, easy to use, and available on almost all mobile devices, making them a preferred alternative over other technologies. However, processing camera images using SfM have a relatively high computational cost if the images are not in sequence and also requires acceptable capturing conditions like lighting, distance, and adequate and obstacle-free field of view for accurate results (Reja, et al, 2022). (Braun, et al, 2020) Digital Images UAV Outdoor (Vincke, et al, 2019) Laser Scanning or Photogrammetry Manual Both (Han, et al, 2018) Photogrammetry/Laser Scanning UAV Both (Arif and Khan, 2021) Videography Fixed Both (Kim, Kim and Lee, 2020) Laser Scanning and Photogrammetry UAV Both (Wang, et al, 2021) Video Camera Fixed Outdoor (Kopsida and Brilakis, 2020) RGBD Camera Manual Indoor (Mahami, et al, 2019) Photogrammetry Manual Both (Maalek, et al, 2019) Laser Scanning Manual Both (Bognot, et al, 2018) Videogrammetry UAS Outdoor (Omar, et al, 2018) Photogrammetry Manual Outdoor (Pučko, et al, 2018) RGBD Camera Manual Both…”

Section: Cameras (Images and Videos)mentioning

confidence: 99%

“…Therefore, this study identifies the factors based on their use in literature while choosing the technology and method and the authors' experience in this field. Our recent study identified these factors (Reja, Varghese and Ha, 2022) by a thorough review of the literature using a well-defined PRISMA methodology.…”

Section: Factors Affecting Data Acquisition Technology Selectionmentioning

confidence: 99%

“…Computer Vision-Based Construction Progress Monitoring (CV-CPM) involves three steps, namely -data acquisition, as-built modelling, and progress estimation (Bhadaniya, et al, 2021;Reja, et al, 2021). Our recent study presented the integrated CV-CPM framework, which defines the three steps in detail while discussing the tools, technologies, algorithms and the methods involved in each step (Reja, et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…Identifying and evaluating these factors is critical for data acquisition and further steps of CV-CPM. In our recent study (Reja, et al, 2022), we identified these factors through an in-depth literature review through the PRISMA methodology. It was found that there is a critical need to evaluate these factors to guide the selection of technology and mounting method for implementation on construction projects.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

As-built data acquisition for vision-based construction progress monitoring: A qualitative evaluation of factors

Reja¹,

Varghese²,

Ha³

2022

Proceedings of 10th World Construction Symposium 2022

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The accuracy of computer vision-based progress monitoring of construction projects depends on the quality of data acquired. The data acquisition can be conducted through different vision-based sensors combined with several options for sensor mounting. Several factors affect this combination and considering these factors in selecting the acquisition technology and sensor mounting combination is critical for acquiring accurate vision-based data for the project. Currently, their definition and impact of these factors on the selection of these technologies are both subjective, and there are no formal studies to evaluate the impact. Hence, in this study, we first identify and define twelve key factors affecting data acquisition technology and eight factors affecting sensor mounting. Next, a questionnaire survey was designed, and responses from professionals were used to evaluate the Relative Importance Index (RII) for the individual factors for these technologies and methods. The obtained ratings were compared to the author's initial assessment, and the cause for a few variations obtained was justified. This study provides a clear assessment of these factors and forms a basis for selection based on the factors involved with the project requirements.

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Section: Cameras (Images and Videos)mentioning

confidence: 99%

Section: Factors Affecting Data Acquisition Technology Selectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

As-built data acquisition for vision-based construction progress monitoring: A qualitative evaluation of factors

Reja¹,

Varghese²,

Ha³

2022

Proceedings of 10th World Construction Symposium 2022

View full text Add to dashboard Cite

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“…Progress monitoring is a procedure to review, track, and orchestrate the performance of construction projects [ 1 ], referring to comparing and inspecting the daily on-site progress of work activities with the constructed plan and validating the projected performance [ 2 ]. Progress monitoring of the construction project is crucial and enables construction managers to make timely decisions based on vital inputs [ 3 ]. In the success of construction projects, effective progress measurement is a critical key parameter [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Characteristics-Based Framework of Effective Automated Monitoring Parameters in Construction Projects

Qureshi

Alaloul²,

Wing³

et al. 2022

Arab J Sci Eng

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The construction industry is moving toward digitalization, and technologies support various construction processes. In the automated construction progress monitoring domain, several modern progress measurement techniques have been introduced. However, a hesitant attitude has been observed toward its adoption. Researchers have highlighted lack of theoretical understanding of effectual implementation is one of the significant reasons. This study aims to analyze general technological parameters related to automated monitoring technologies and devise a theoretical-based conceptual framework explaining the aspects affecting the adequate operation of automated monitoring. The study has been executed by following a systematic inline process for the identification of effective parameters, which include a structured literature review, semi-structured interviews, pilot survey, questionnaire survey, and structural equation modeling (SEM)-based mathematical model. A refined conceptual framework has been devised with 21 effective parameters under five significant categories, i.e., “Target Object,” “Technical,” “External Interference,” “Occlusions,” and “Sensing.” A knowledge framework has been established by adopting the SEM technique, which is designed on the characteristics-based theme. This conceptual framework provides the theoretical base for practitioners toward the conceptual understanding of automated monitoring processes related to technological parameters that affect the outcomes. This study is unique as it focused on the general criteria or parameters that affect the performance or outcomes of the digital monitoring process and is easily understandable by the user or operator.

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Digitaler Zwilling Baustelle – Baustellenüberwachung zur automatisierten Zeit‐ und Kostenkontrolle

et al. 2023

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Während in der Produktions-und Fertigungsbranche bereits mit hoch automatisierten Verfahren gearbeitet wird, tut sich die Bauindustrie schwer, den technologischen Fortschritt zu nutzen [1]. Das begünstigt Ungenauigkeiten bei der Fortschrittskontrolle, was unweigerlich zu Verzögerungen im Bauprojekt führt.Ein etabliertes Konzept, welches v. a. in der Fertigungsindustrie zu einem hohen Grad an Automatisierung geführt hat, ist der Digitale Zwilling. Diese Technologie basiert darauf, ein digitales Abbild der Realität zu schaffen. Der Begriff Digitaler Zwilling wurde erstmalig 2003 von Michael Grieves als "digitales Abbild eines physischen Objektes" verwendet [1,2]. In den letzten 20 Jahren gab es zahlreiche Entwicklungen und Anwendungsfälle dieses Konzepts, der Kern ist jedoch gleich geblieben: Durch den Digitalen Zwilling entsteht eine Wechselwirkung zwischen der physischen und der digitalen Welt. Infolgedessen entstehen viele neue Perspektiven, bspw. beim Einsatz während der Bauausführung, wie in diesem Bei-trag vorgestellt wird. Den Kern bildet dabei die automatisierte Baufortschrittsüberwachung.

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Computer vision-based construction progress monitoring

Cited by 72 publications

References 68 publications

As-built data acquisition for vision-based construction progress monitoring: A qualitative evaluation of factors

As-built data acquisition for vision-based construction progress monitoring: A qualitative evaluation of factors

Characteristics-Based Framework of Effective Automated Monitoring Parameters in Construction Projects

Digitaler Zwilling Baustelle – Baustellenüberwachung zur automatisierten Zeit‐ und Kostenkontrolle

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