Data-Driven Monitoring System for Preventing the Collapse of Scaffolding Structures

Cho, Chunhee; Kim, Kyungki; Park, J.; Cho, Yong

doi:10.1061/(asce)co.1943-7862.0001535

Cited by 36 publications

(18 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, sensor technology can be used to automatically monitor the construction environment. Cho et al [43] developed a system to estimate the status of scaffoldings, including safe, over-turning, uneven settlement, and over-loading, by fitting strain sensors onto the scaffoldings. They developed a model to distinguish different safety conditions of scaffolds through the combination of finite element analysis (FEA) and machine learning.…”

Section: Identification Of Unsafe Construction Environmentmentioning

confidence: 99%

“…These problems are widespread in construction projects, and the following solutions are proposed based on the DT concept. 4D BIM and sensors can be used to digitise the construction site [43,46,49]. The 4D BIM simulates the construction activity, and the sensors synchronise real-time data during construction to monitor unexpected events.…”

Section: The Status Quo Of Digital Twins (Dt) To Improve Construction Workforce Safetymentioning

confidence: 99%

See 1 more Smart Citation

Literature Review of Digital Twins Applications in Construction Workforce Safety

et al. 2020

View full text Add to dashboard Cite

For many decades, safety has been a challenge in the construction sector. Despite extensive efforts to improve overall safety, the sector’s casualty rate still remains high. In practice, dynamic and complex construction processes may lead to on-site risks and safety plans being overlooked, likely leading to a variety of safety accidents. Nowadays, under the guidance of the digital twins (DT) concept, the advent of state-of-the-art sensing and visualisation technologies has offered the possibility to improve construction health and safety in the workplace. To understand the research advances of these technologies, identify their gaps and challenges, and propose solutions to further advance the industry’s safety, we conducted and report a thorough review on the state-of-the-art technological studies, and elaborate upon the key findings in detail. For instance, despite DT being proven to be effective in improving construction workforce safety, the construction industry has yet to fully exploit and streamline these innovations in practice. Overall, this review provides insights into technological clustering, improvement strategies, as well as workforce safety, which can benefit from formulating effective digital technology paradigms.

show abstract

Section: Identification Of Unsafe Construction Environmentmentioning

confidence: 99%

Section: The Status Quo Of Digital Twins (Dt) To Improve Construction Workforce Safetymentioning

confidence: 99%

Literature Review of Digital Twins Applications in Construction Workforce Safety

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Regression and statistical methods in analyzing productivity (Hanna, Chang, Lackney and Sullivan, 2007) Computation of productivity involving visual techniques, data analytics, or framework establishment (Mani, Kisi, Rojas and Foster, 2017) Safety Safety climate (Fang, Chen and Wong, 2006); Safety hazard identification (Carter and Smith, 2006); Causes of safety incident/accident (Beheiry, Chong and Haas, 2006) Social network analysis (Allison and Kaminsky, 2017); Data analytics of accidents (Gerassis, Martín, García, Saavedra and Taboada, 2017); smart safety monitoring (Cho, Kim, Park and Cho, 2018)…”

Section: Resultsmentioning

confidence: 99%

“…Similarly, the data analytics approach such as Bayesian Decision Tool (Gerassis et al, 2017) is gaining more application in construction safety research. Research in safety management has also shown the application of artificial intelligence and smart monitoring (Cho et al, 2018). It should be noticed that the topics studied from 2000 to 2008 may still be continuously studied in the more recent years, such as safety climate (Chen and Jin, 2013).…”

Section: Qualitative Analysis Of Research Abstractmentioning

confidence: 99%

Scientometric Review of Articles Published in ASCE’sJournal of Construction Engineering and Managementfrom 2000 to 2018

Jin

Zuo

Hong

2019

J. Constr. Eng. Manage.

View full text Add to dashboard Cite

This study aims to address research questions related to the evolutionof academic research in the field of construction engineering and management (CEM): (1) what are the mainstream research topics since 2000? (2) whatare the emerging topics or techniques in CEM within the recent decades? (3) whatarepotentialCEM research areas in the near future? Ascientometric analysiswas conducted to review articles published in Journal of Construction Engineering and Mnagement (JCEM) since 2000,follow by a qualitative discussion.Thisstudy revealed that project performance indicator-related topics (e.g., cost, scheduling, safety, productivity, and risk management) had been the ongoing mainstream issues over the past decades.Labor and personnel issues had gained even more research attention in the last ten years. Information and communication technologies (e.g., Building Information Modeling or BIM) applied in CEM had been gaining the momentum since 2009. A variety of quantitative methods had gained popularity in the CEM discipline, such as algorithm, statistics, fuzzy set, and neural networks. The follow-up qualitative analysis led to the contributions of this review-based study in terms that: (1) it provided an overview of the research topics in CEM since 2000 through a text-mining approach; (2) it offered insights on the emerging and near

show abstract

“…In the process of moving objects, its appearance will change constantly. At this time, the filter is constantly updated, and the updated filter cannot guarantee to fully track the target of the next frame, which usually leads to tracking drift [93]. Therefore, it is suggested that future research focus on two aspects: (1) constantly updating the apparent model of objects to adapt to the changes of the apparent model and (2) control the update of filters.…”

Section: Irregularity Of Object Motionmentioning

confidence: 99%

Applications of Computer Vision in Monitoring the Unsafe Behavior of Construction Workers: Current Status and Challenges

Liu

Meng

et al. 2021

Buildings

View full text Add to dashboard Cite

The unsafe behavior of construction workers is one of the main causes of safety accidents at construction sites. To reduce the incidence of construction accidents and improve the safety performance of construction projects, there is a need to identify risky factors by monitoring the behavior of construction workers. Computer vision (CV) technology, which is a powerful and automated tool used for extracting images and video information from construction sites, has been recognized and adopted as an effective construction site monitoring technology for the identification of risky factors resulting from the unsafe behavior of construction workers. In this article, we introduce the research background of this field and conduct a systematic statistical analysis of the relevant literature in this field through the bibliometric analysis method. Thereafter, we adopt a content-based analysis method to depict the historical explorations in the field. On this basis, the limitations and challenges in this field are identified, and future research directions are proposed. It is found that CV technology can effectively monitor the unsafe behaviors of construction workers. The research findings can enhance people’s understanding of construction safety management.

show abstract

Data-Driven Monitoring System for Preventing the Collapse of Scaffolding Structures

Cited by 36 publications

References 27 publications

Literature Review of Digital Twins Applications in Construction Workforce Safety

Literature Review of Digital Twins Applications in Construction Workforce Safety

Scientometric Review of Articles Published in ASCE’sJournal of Construction Engineering and Managementfrom 2000 to 2018

Applications of Computer Vision in Monitoring the Unsafe Behavior of Construction Workers: Current Status and Challenges

Contact Info

Product

Resources

About