Automation in Construction最新文献_第7页

Component-based BIM-semantic web integration for enhanced robotic visual perception 基于组件的bim -语义web集成，增强机器人视觉感知

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-06-05 DOI: 10.1016/j.autcon.2025.106270

Aiyu Zhu , Zimu Shao , Xini Chai , Encheng Ma , Qingyang Li , Hongyu Ye , Hong Zhang

{"title":"Component-based BIM-semantic web integration for enhanced robotic visual perception","authors":"Aiyu Zhu , Zimu Shao , Xini Chai , Encheng Ma , Qingyang Li , Hongyu Ye , Hong Zhang","doi":"10.1016/j.autcon.2025.106270","DOIUrl":"10.1016/j.autcon.2025.106270","url":null,"abstract":"<div><div>Visual perception plays a crucial role in enhancing construction robots’ real-time performance by enabling accurate object recognition, localization, and scene understanding in complex construction environments. While current research focuses on visual recognition for tasks like spatial localization and navigation, it falls short of addressing the more advanced functions necessary for comprehensive construction planning. This paper proposes an integrated framework that combines building semantic web technologies with image recognition techniques to significantly improve robotic perception. By merging real-time image recognition with BIM-based semantic mapping, robots can gather critical information on component types, spatial relationships, and construction requirements. Case studies illustrate the framework’s ability to improve adaptability, precision, and efficiency in both static and dynamic construction environments, thereby enabling more intelligent, automated, and efficient robotic construction processes, with the potential for broader applications in the future of construction technology.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"177 ","pages":"Article 106270"},"PeriodicalIF":9.6,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144221141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Topology optimisation for large-scale wire-arc directed energy deposition considering environmental impact and cost 考虑环境影响和成本的大规模线弧定向能沉积拓扑优化

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-06-05 DOI: 10.1016/j.autcon.2025.106313

Mohammad Hassan Baqershahi , Can Ayas , Elyas Ghafoori

{"title":"Topology optimisation for large-scale wire-arc directed energy deposition considering environmental impact and cost","authors":"Mohammad Hassan Baqershahi , Can Ayas , Elyas Ghafoori","doi":"10.1016/j.autcon.2025.106313","DOIUrl":"10.1016/j.autcon.2025.106313","url":null,"abstract":"<div><div>Advancements in wire-arc directed energy deposition (DED) have created new opportunities for manufacturing efficient large-scale structures. While wire-arc DED is often viewed as more sustainable and economical due to the potential of producing lighter structures, its higher environmental impact and cost per unit of weight necessitate further considerations during the design phase. This paper explores how sustainability and cost can be integrated into conceptual design through topology optimisation. The approach is demonstrated through a case study, including a parametric study on specific environmental impact and the cost of wire-arc DED versus CM, applicable to current data and future estimates. Findings indicate that beams manufactured solely with wire-arc DED are sensitive to fluctuations in specific environmental impact and cost of wire-arc DED, potentially losing their material saving advantage. Conversely, hybrid beams that combine conventional profiles with wire-arc DED offer a better balance between structural performance, sustainability and economic feasibility.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"177 ","pages":"Article 106313"},"PeriodicalIF":9.6,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144221142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advancing polymer composites in civil infrastructure through 3D printing 通过3D打印推进民用基础设施中的聚合物复合材料

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-06-04 DOI: 10.1016/j.autcon.2025.106311

Sachini Wickramasinghe , Allan Manalo , Omar Alajarmeh , Charles Dean Sorbello , Senarath Weerakoon , Tuan D. Ngo , Brahim Benmokrane

{"title":"Advancing polymer composites in civil infrastructure through 3D printing","authors":"Sachini Wickramasinghe , Allan Manalo , Omar Alajarmeh , Charles Dean Sorbello , Senarath Weerakoon , Tuan D. Ngo , Brahim Benmokrane","doi":"10.1016/j.autcon.2025.106311","DOIUrl":"10.1016/j.autcon.2025.106311","url":null,"abstract":"<div><div>Polymer composites (PCs) are increasingly used in civil infrastructure and construction due to their high strength, lightweight properties, and durability. When combined with automated manufacturing technologies such as 3D printing, they enable the efficient fabrication of complex engineering structures while minimizing material waste. As construction moves toward sustainable, automated, and digitally driven methods, understanding the potential of 3D-printed polymer composites becomes essential. This review addresses this emerging need by offering a civil-infrastructure specific synthesis of polymer composites in additive manufacturing as a pathway to a more sustainable and resilient built environment. The paper presents a comprehensive overview of the use of PCs in automated construction, highlighting key 3D printing techniques and printable polymer-based materials applied in building and infrastructure projects. It also discusses recent developments, current challenges, and emerging opportunities in PC-based 3D printing for civil engineering, supported by case studies, innovative construction methodologies, and future research directions.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"177 ","pages":"Article 106311"},"PeriodicalIF":9.6,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144204416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Psychophysiological impacts of working with powered exoskeletons on construction sites 在建筑工地使用动力外骨骼的心理生理影响

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-06-03 DOI: 10.1016/j.autcon.2025.106312

Amit Ojha , Shayan Shayesteh , Yizhi Liu , Houtan Jebelli , Abiola Akanmu

{"title":"Psychophysiological impacts of working with powered exoskeletons on construction sites","authors":"Amit Ojha , Shayan Shayesteh , Yizhi Liu , Houtan Jebelli , Abiola Akanmu","doi":"10.1016/j.autcon.2025.106312","DOIUrl":"10.1016/j.autcon.2025.106312","url":null,"abstract":"<div><div>Powered exoskeletons are aimed at enhancing user strength and minimizing physical strain to prevent work-related musculoskeletal injuries. However, their widespread adoption within the construction sector remains limited, primarily due to uncertainties about their psychophysiological impacts, such as potential cognitive overload, trust issues, and changes in attention levels. To tackle these concerns, this paper sets out to empirically assess the psychophysiological risks associated with using powered exoskeletons during construction tasks. An immersive virtual reality environment was created to simulate typical construction activities, aiming to gather large amounts of high-quality physiological data. Subsequently, psychological sensing frameworks were developed to quantify workers' cognitive load, trust, and vigilance. The findings indicated that powered exoskeletons induced cognitive burden, fostering distrust among the workers without affecting vigilance levels. These findings offer a robust empirical basis for the broader implementation of powered exoskeletons in construction settings.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"177 ","pages":"Article 106312"},"PeriodicalIF":9.6,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144204415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Attention-guided cascaded network for predicting tunnel surrounding rock properties using measurement-while-drilling data 利用随钻测量数据预测隧道围岩特性的注意力引导级联网络

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-06-03 DOI: 10.1016/j.autcon.2025.106310

Jun Wang, Qian Fang, Gan Wang, Dong Li, Jiayao Chen, Guoli Zheng

{"title":"Attention-guided cascaded network for predicting tunnel surrounding rock properties using measurement-while-drilling data","authors":"Jun Wang, Qian Fang, Gan Wang, Dong Li, Jiayao Chen, Guoli Zheng","doi":"10.1016/j.autcon.2025.106310","DOIUrl":"10.1016/j.autcon.2025.106310","url":null,"abstract":"<div><div>The quality of rock mass is a critical factor in evaluating the stability of surrounding rock and determining excavation and support strategies during tunnel construction. This paper presents a physical mechanism-constrained cascade (PMC) model strategy for multi-task learning (MTL), effectively capturing both the correlations and distinctions among tasks. In addition, an attention-guided cascade progressive layer extraction (AGCPLE) model is proposed to predict key rock mass quality indicators, including the surface rock quality designation index (S-RQD), Schmidt rebound value (RV), and basic quality (BQ) of surrounding rock. The AGCPLE model utilizes measurement-while-drilling data from multiple blastholes, and tunnel construction data as input to predict these indicators. Performance and generalization capabilities are evaluated using data from the Yangjiawopu tunnel in China. Results show that the AGCPLE model outperforms conventional deep learning and machine learning approaches. Furthermore, the PMC model strategy shows improved predictive performance compared to other MTL strategies.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"177 ","pages":"Article 106310"},"PeriodicalIF":9.6,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Context-aware vision-language model agent enriched with domain-specific ontology for construction site safety monitoring 基于领域本体的建筑工地安全监测环境感知视觉语言模型智能体

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-06-02 DOI: 10.1016/j.autcon.2025.106305

Chak-Fu Chan , Peter Kok-Yiu Wong , Xiaowen Guo , Jack C.P. Cheng , Jolly Pui-Ching Chan , Pak-Him Leung , Xingyu Tao

{"title":"Context-aware vision-language model agent enriched with domain-specific ontology for construction site safety monitoring","authors":"Chak-Fu Chan , Peter Kok-Yiu Wong , Xiaowen Guo , Jack C.P. Cheng , Jolly Pui-Ching Chan , Pak-Him Leung , Xingyu Tao","doi":"10.1016/j.autcon.2025.106305","DOIUrl":"10.1016/j.autcon.2025.106305","url":null,"abstract":"<div><div>Traditional approaches of construction site safety monitoring heavily rely on manual on-site inspection, which are prone to overlooked incidents. Existing computer vision methods require time-consuming and case-by-case data labeling, and lack high-level reasoning capability. This paper develops a human-alike virtual assistant agent by integrating a multi-modal vision-language model into video analytics: (1) To efficiently generate image-text data for model development, a semi-automatic image-text labeling pipeline based on in-context learning is designed; (2) To optimize a virtual agent from pre-trained to domain-tailored, a two-stage curriculum learning paradigm is designed to enhance model fine-tuning effectiveness toward domain-specific tasks; (3) To inject construction-domain knowledge more effectively into the virtual agent, a hierarchical prompting framework driven by a construction safety ontology is developed for more domain-tailored reasoning capability. The virtual agent has been deployed on a real construction site for real-time video analytics, with over 90 % accuracy in identifying violations of work-at-height safety regulations.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"177 ","pages":"Article 106305"},"PeriodicalIF":9.6,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144190058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Generative AI-augmented offshore jacket design: Integrated approach for mixed tabular data generation under scarcity and imbalance 生成人工智能增强海上导管架设计：稀缺性和不平衡条件下混合表格数据生成的集成方法

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-06-02 DOI: 10.1016/j.autcon.2025.106287

Emmanouil Panagiotou , Han Qian , Steffen Marx , Eirini Ntoutsi

{"title":"Generative AI-augmented offshore jacket design: Integrated approach for mixed tabular data generation under scarcity and imbalance","authors":"Emmanouil Panagiotou , Han Qian , Steffen Marx , Eirini Ntoutsi","doi":"10.1016/j.autcon.2025.106287","DOIUrl":"10.1016/j.autcon.2025.106287","url":null,"abstract":"<div><div>Generative Artificial Intelligence (AI) has found various applications in domains like computer vision and natural language processing. However, limited research exists in the engineering domain, where prevailing challenges involve mixed tabular data, data scarcity, and imbalances. This paper focuses on generating synthetic offshore jacket designs to improve the data quality of a scarce and imbalanced existing dataset. Data quality is quantified by evaluating the machine-learning efficiency of the synthetic data on a domain-specific downstream task.</div><div>An integrated method is proposed for generating jacket designs, combining modern data-driven techniques with traditional multi-objective-driven approaches. The method addresses challenges related to mixed attributes, data scarcity, and class imbalances. Experimental results demonstrate improved predictive performance on the downstream task when models are trained on synthetic data compared to using only real data. These findings contribute to the advancement of generative AI in offshore engineering and related fields, offering valuable insights and potential applications.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"177 ","pages":"Article 106287"},"PeriodicalIF":9.6,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144190057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data-augmented explainable AI for pavement roughness prediction 用于路面粗糙度预测的数据增强可解释人工智能

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-05-31 DOI: 10.1016/j.autcon.2025.106307

Abdolmajid Erfani , Narjes Shayesteh , Tamim Adnan

{"title":"Data-augmented explainable AI for pavement roughness prediction","authors":"Abdolmajid Erfani , Narjes Shayesteh , Tamim Adnan","doi":"10.1016/j.autcon.2025.106307","DOIUrl":"10.1016/j.autcon.2025.106307","url":null,"abstract":"<div><div>Effective pavement management systems rely on accurate predictions of pavement conditions to guide strategic decisions about maintenance and rehabilitation projects. Although recent studies have explored various artificial intelligence-based methods for predicting pavement roughness, notable gaps remain in the literature. Existing studies often use homogeneous data from similar climates and pavement types and overlook imbalances in historical pavement condition data. They also treat machine learning models as black boxes, relying on static feature rankings that miss complex relationships between inputs and predictions. This paper bridges these gaps by applying an explainable AI framework, enhanced with data augmentation, to a diverse and comprehensive dataset of pavement conditions. The proposed approach enhanced performance across a comprehensive set of metrics, reducing RMSE by 28.28 %, RSR by 36.92 %, and WMAP by 33.74 %, while increasing R-squared by 7.28 % and VAF by 6.61 %. Explainable AI analysis provided practical insights, enhancing model applicability and supporting informed maintenance decisions.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"176 ","pages":"Article 106307"},"PeriodicalIF":9.6,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144185437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Network analysis and graph neural network (GNN)-based link prediction of construction hazards 基于网络分析和图神经网络（GNN）的施工环节危害预测

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-05-30 DOI: 10.1016/j.autcon.2025.106302

Brian H.W. Guo , Qilan Li , Wen Yi , Bowen Ma , Zhe Zhang , Yonger Zuo

{"title":"Network analysis and graph neural network (GNN)-based link prediction of construction hazards","authors":"Brian H.W. Guo , Qilan Li , Wen Yi , Bowen Ma , Zhe Zhang , Yonger Zuo","doi":"10.1016/j.autcon.2025.106302","DOIUrl":"10.1016/j.autcon.2025.106302","url":null,"abstract":"<div><div>Hazard recognition is critical for construction safety, especially for accident prevention. Traditional methods often fail to capture the dynamic and interdependent nature of construction hazards. To address this issue, this paper proposes a network-based framework that conceptualizes construction hazards as dynamic interactions between objects with hazardous attributes. A link prediction model using Graph Neural Networks (GNNs) is integrated in this framework to automatically explore latent interactions between hazard objects that are ignored by the existing dataset. By analyzing 4470 construction accident reports, this paper constructed a hazard network and revealed key structural properties, including hazard object centrality, cliques, and communities. The experimental results of link prediction showed that the GNN-based model demonstrated superior performance compared to traditional methods, with 81 % of GNN-predicted links validated by actual construction accident cases. This framework provides a practical solution for intelligent hazard recognition and proactive risk management in the construction industry.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"176 ","pages":"Article 106302"},"PeriodicalIF":9.6,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144170491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data integration for space-aware Digital Twins of hospital operations 医院操作的空间感知数字孪生数据集成

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-05-30 DOI: 10.1016/j.autcon.2025.106276

Nicola Moretti , Yin-Chi Chan , Momoko Nakaoka , Anandarup Mukherjee , Jorge Merino , Ajith Kumar Parlikad

{"title":"Data integration for space-aware Digital Twins of hospital operations","authors":"Nicola Moretti , Yin-Chi Chan , Momoko Nakaoka , Anandarup Mukherjee , Jorge Merino , Ajith Kumar Parlikad","doi":"10.1016/j.autcon.2025.106276","DOIUrl":"10.1016/j.autcon.2025.106276","url":null,"abstract":"<div><div>Healthcare facilities are complex systems where operational efficiency depends on space, processes, resources, and logistics. While many studies propose process-simulation-based improvements, few dynamically consider the built space’s effect on process efficiency. The critical challenge here is the effective integration of data from these disparate domains. This article addresses this challenge by proposing an open Building Information Modelling (BIM) to Discrete Event Simulation (DES) data integration framework towards the development of a space-aware process Digital Twin (DT), with the goal of determining and controlling the impact of spatial layout and built asset performance on core-process throughput. A case study of a multi-storey Histopathology laboratory demonstrates how the impact of changes in travel time between process stages, due to a faulty lift and functional re-configurations, on laboratory turnaround time can be managed integrating up-to-date building information in modelling core business processes. This is achieved through the space-aware process DT architecture.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"176 ","pages":"Article 106276"},"PeriodicalIF":9.6,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144170490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0