
Developments in the Built Environment, Journal Year: 2025, Volume and Issue: unknown, P. 100645 - 100645
Published: March 1, 2025
Language: Английский
Developments in the Built Environment, Journal Year: 2025, Volume and Issue: unknown, P. 100645 - 100645
Published: March 1, 2025
Language: Английский
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
89Automation in Construction, Journal Year: 2022, Volume and Issue: 140, P. 104302 - 104302
Published: May 10, 2022
Language: Английский
Citations
80Computers in Industry, Journal Year: 2022, Volume and Issue: 144, P. 103783 - 103783
Published: Sept. 26, 2022
Language: Английский
Citations
73Automation in Construction, Journal Year: 2023, Volume and Issue: 154, P. 104982 - 104982
Published: June 27, 2023
Language: Английский
Citations
57Automation in Construction, Journal Year: 2024, Volume and Issue: 162, P. 105380 - 105380
Published: March 16, 2024
Language: Английский
Citations
29Automation in Construction, Journal Year: 2024, Volume and Issue: 160, P. 105299 - 105299
Published: Jan. 31, 2024
Language: Английский
Citations
17Automation 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
65Developments 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
37Advanced Engineering Informatics, Journal Year: 2023, Volume and Issue: 55, P. 101875 - 101875
Published: Jan. 1, 2023
Language: Английский
Citations
30Alexandria 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