Data-model hybrid-driven and artificial intelligence-based monitoring threshold update and short-term response prediction for high-formwork support system DOI Creative Commons
Qiang� Li, Peixuan Wang, Xianzhe Li

et al.

Developments in the Built Environment, Journal Year: 2025, Volume and Issue: unknown, P. 100645 - 100645

Published: March 1, 2025

Language: Английский

Robots in Inspection and Monitoring of Buildings and Infrastructure: A Systematic Review DOI Creative Commons
Srijeet Halder, Kereshmeh Afsari

Applied Sciences, Journal Year: 2023, Volume and Issue: 13(4), P. 2304 - 2304

Published: Feb. 10, 2023

Regular inspection and monitoring of buildings infrastructure, that is collectively called the built environment in this paper, critical. The includes commercial residential buildings, roads, bridges, tunnels, pipelines. Automation robotics can aid reducing errors increasing efficiency tasks. As a result, robotic has become significant research topic recent years. This review paper presents an in-depth qualitative content analysis 269 papers on use robots for infrastructure. found nine different types systems, with unmanned aerial vehicles (UAVs) being most common, followed by ground (UGVs). study also five applications monitoring, namely, maintenance inspection, construction quality progress as-built modeling, safety inspection. Common areas investigated researchers include autonomous navigation, knowledge extraction, motion control sensing, multi-robot collaboration, implications, data transmission. findings provide insight into developments field will benefit researchers, facility managers, developing implementing new solutions.

Language: Английский

Citations

89

Deep learning-based data analytics for safety in construction DOI

Jiajing Liu,

Hanbin Luo, Junxiao Liu

et al.

Automation in Construction, Journal Year: 2022, Volume and Issue: 140, P. 104302 - 104302

Published: May 10, 2022

Language: Английский

Citations

80

A digital twin approach for tunnel construction safety early warning and management DOI
Zijian Ye,

Ying Ye,

Chengping Zhang

et al.

Computers in Industry, Journal Year: 2022, Volume and Issue: 144, P. 103783 - 103783

Published: Sept. 26, 2022

Language: Английский

Citations

73

Deep learning technologies for shield tunneling: Challenges and opportunities DOI
Cheng Zhou,

Yuyue Gao,

Elton J. Chen

et al.

Automation in Construction, Journal Year: 2023, Volume and Issue: 154, P. 104982 - 104982

Published: June 27, 2023

Language: Английский

Citations

57

Machine learning in construction and demolition waste management: Progress, challenges, and future directions DOI
Yu Gao,

Jiayuan Wang,

Xiaoxiao Xu

et al.

Automation in Construction, Journal Year: 2024, Volume and Issue: 162, P. 105380 - 105380

Published: March 16, 2024

Language: Английский

Citations

29

Unsafe hoisting behavior recognition for tower crane based on transfer learning DOI
Weiguang Jiang, Lieyun Ding

Automation in Construction, Journal Year: 2024, Volume and Issue: 160, P. 105299 - 105299

Published: Jan. 31, 2024

Language: Английский

Citations

17

Vision-based monitoring of site safety compliance based on worker re-identification and personal protective equipment classification DOI Creative Commons

JackC.P. Cheng,

Peter Kok-Yiu Wong, Han Luo

et al.

Automation in Construction, Journal Year: 2022, Volume and Issue: 139, P. 104312 - 104312

Published: May 6, 2022

Construction sites are highly hazardous due to the dynamic interaction between workers and moving equipment, with high fatality rates caused by collision falling from height, etc. Hence, identifying unsafe behaviors among is crucial for enhancing site safety, such as tracking their on-site movement personal protective equipment (PPE). Vision-based video processing has been actively used automatically recognize on construction sites. However, existing studies mainly monitor within a single camera capturing only small sub-region. As typically move around fairly large sites, continuously across multiple cameras would enable more comprehensive behavioral analyses. this paper proposes framework monitoring safety compliance workers, combining worker re-identification (ReID) PPE classification. Deep learning-based approaches developed address challenges these two tasks respectively. For ReID, new loss function named similarity designed encourage deep learning models learn discriminative human features, realizing robust of individual workers. classifying statuses, weighted-class strategy proposed mitigate model bias when given imbalanced samples classes, improved performance despite limited training samples. By ReID classification results, workflow log any incident not wearing necessary PPEs. With an actual dataset, methods improve 4% 13% accuracies respectively, which will facilitate analytics inspection

Language: Английский

Citations

65

Automated vision-based construction progress monitoring in built environment through digital twin DOI Creative Commons
Aritra Pal, Jacob J. Lin, Shang‐Hsien Hsieh

et al.

Developments in the Built Environment, Journal Year: 2023, Volume and Issue: 16, P. 100247 - 100247

Published: Oct. 11, 2023

Effective progress monitoring is ineviTable for completing the construction of building and infrastructure projects successfully. In this digital transformation era, with data-centric management control approach, effectiveness methods expected to improve dramatically. "Digital Twin," which creates a bidirectional communication flow between physical entity its counterpart, found be crucial enabling technology information-aware decision-making systems in manufacturing other automotive industries. Recognizing benefits production construction, researchers have proposed Digital Twin Construction (DTC). DTC leverages information modeling processes, lean practices, on-site data collection mechanisms, Artificial Intelligence (AI) based analytics improving planning processes. Progress monitoring, key component control, can significantly benefit from DTC. However, some knowledge gaps still need filled practical implementation built environment domain. This research reviews existing vision-based methods, studies evolution automated research, highlights methodological technological that must addressed DTC-based predictive monitoring. Subsequently, it proposes framework closed-loop through Finally, way forward fully automated, real-time upon concept proposed.

Language: Английский

Citations

37

Excavator 3D pose estimation using deep learning and hybrid datasets DOI

Amin Assadzadeh,

Mehrdad Arashpour, Heng Li

et al.

Advanced Engineering Informatics, Journal Year: 2023, Volume and Issue: 55, P. 101875 - 101875

Published: Jan. 1, 2023

Language: Английский

Citations

30

A hybrid building information modeling and collaboration platform for automation system in smart construction DOI Creative Commons
Yonghao Wang,

Hailu lu,

Yao Wang

et al.

Alexandria Engineering Journal, Journal Year: 2024, Volume and Issue: 88, P. 80 - 90

Published: Jan. 12, 2024

Building information modeling (BIM) technology can organically combine data and virtual reality, compare them with actual construction objects to realize the smart collaboration of entity model in processes, greatly reducing early stage mistakes improve efficiency. This paper proposed an automation system framework based on BIM platform, discussed element configuration finally elaborated working mechanism automated platform. The study results show that platform supports rapid large-scale three-dimensional scenes precise integration multi-source data, bring together asset from different sources form open, safe, accessible digital environment. application cost management has brought huge economic benefits, efficiency been increased by 65%, period shortened 30%, labor intensity reduced 27%, productivity 39%, which considerable indirect benefits projects.

Language: Английский

Citations

12