Automation in Construction最新文献_第3页

Data-driven additive manufacturing with concrete: Enhancing in-line sensory data with domain knowledge, Part II: Moisture and heat 数据驱动的混凝土增材制造：用领域知识增强在线感官数据，第二部分：水分和热量

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-06-23 DOI: 10.1016/j.autcon.2025.106327

J. Versteege, R.J.M. Wolfs, T.A.M. Salet

{"title":"Data-driven additive manufacturing with concrete: Enhancing in-line sensory data with domain knowledge, Part II: Moisture and heat","authors":"J. Versteege, R.J.M. Wolfs, T.A.M. Salet","doi":"10.1016/j.autcon.2025.106327","DOIUrl":"10.1016/j.autcon.2025.106327","url":null,"abstract":"<div><div>A data-driven approach to achieving first-time-right manufacturing in digital fabrication with concrete (DFC) relies on in-line sensors to capture real-time measurements. To extract meaningful information (features) from raw sensory data, these sensors must be integrated with knowledge-driven feature engineering (KDFE) strategies. The first paper describes the methodology and its application to geometric data. This paper continues by detailing features related to the dosing, mixing, and pumping of material, the quantification of surface dehydration by employing near-infrared spectroscopy, the measurement of surface temperature using infrared thermography, and the monitoring of atmospheric conditions. Although these in-line sensors provide valuable data, much of it is complex or indirectly related, which requires KDFE. The sensors and features are demonstrated using real-world data, while controlled laboratory experiments are used for their validation. In combination with the features presented in the first paper, this paper offers a comprehensive set of features for 3DCP process monitoring.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"177 ","pages":"Article 106327"},"PeriodicalIF":9.6,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144366353","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

Flight path planning of UAV-driven refinement inspection for construction sites based on 3D reconstruction 基于三维重建的无人机驱动建筑工地精细化检测航迹规划

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-06-23 DOI: 10.1016/j.autcon.2025.106360

Xin Liu , Wen Yi , Penglu Chen , Yi Tan

引用次数: 0

Two-stage S-curve trajectory generation for time-optimal, anti-sway crane-rotation with jib-luffing and rope hoisting 两阶段s曲线轨迹生成的时间最优，抗摇摆起重机旋转与吊臂变幅和绳索提升

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-06-23 DOI: 10.1016/j.autcon.2025.106339

Kazufumi Kudara , Hideki Takahashi , Hiroki Nakayama , Shintaro Sasai , Teppei Maedo , Naoki Uchiyama

{"title":"Two-stage S-curve trajectory generation for time-optimal, anti-sway crane-rotation with jib-luffing and rope hoisting","authors":"Kazufumi Kudara , Hideki Takahashi , Hiroki Nakayama , Shintaro Sasai , Teppei Maedo , Naoki Uchiyama","doi":"10.1016/j.autcon.2025.106339","DOIUrl":"10.1016/j.autcon.2025.106339","url":null,"abstract":"<div><div>This paper presents a trajectory generation method for rotary cranes that minimizes motion time while effectively suppressing load sway. A two-stage S-curve trajectory, derived from motion patterns observed in skilled operators was designed to suppress two-dimensional load sway attributed to inertial and centrifugal forces. The proposed method optimizes rotational angular velocity by incorporating nonlinear crane dynamics and actuator constraints, ensuring time-optimal control employing only jib rotation. The method is further generalized to accommodate multiaxial motions, including jib luffing and rope hoisting, thereby improving the adaptability. The trajectory was validated via simulations and laboratory-scale experiments, yielding residual load-sway angles below 0.006 rad with minimum motion time. The results demonstrate improved precision in load transport and reduced dependence on skilled operators. This study advances crane automation and operational safety in autonomous lifting systems. Future work will focus on full-scale implementation, real-world validation, and mitigation of mechanical stress induced by dynamic load swaying.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"177 ","pages":"Article 106339"},"PeriodicalIF":9.6,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144364648","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

Out-of-Order synchronization for off-site fit-out in smart prefabrication yard 智能预制场非现场装配的乱序同步

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-06-21 DOI: 10.1016/j.autcon.2025.106355

Haoran Ding , Ray Y. Zhong , Ming Li , George Q. Huang

{"title":"Out-of-Order synchronization for off-site fit-out in smart prefabrication yard","authors":"Haoran Ding , Ray Y. Zhong , Ming Li , George Q. Huang","doi":"10.1016/j.autcon.2025.106355","DOIUrl":"10.1016/j.autcon.2025.106355","url":null,"abstract":"<div><div>With the development of Modular Prefabricated Construction (MPC), efficiently synchronizing off-site fit-out operations is increasingly important. However, existing synchronization methods lack the flexibility and adaptability to address the challenges in off-site fit-out. This research introduces the concept of Out-of-Order (OoO) synchronization to improve off-site fit-out operations within prefabrication yards. A Cyber-Physical System (CPS)-enabled smart prefabrication yard is proposed to provide real-time visibility and traceability and support decision-making among various stakeholders. To simplify the synchronization problem, a spatial-temporal model is developed for dynamically locating disturbances and uncertainties. Inspired by OoO execution in computer processors, an OoO synchronization mechanism is introduced to ensure smooth workflows and reduce delays. Numerical analysis validates that the OoO synchronization mechanism significantly enhances resource utilization and operational efficiency. This paper advances smart construction by offering a flexible, data-driven method to manage complex, resource-limited production environments.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"177 ","pages":"Article 106355"},"PeriodicalIF":9.6,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330183","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

Deep learning-based fatigue monitoring of construction workers using physiological signals 基于深度学习的建筑工人生理信号疲劳监测

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-06-21 DOI: 10.1016/j.autcon.2025.106356

Waleed Umer , Imran Mehmood , Yazan Qarout , Maxwell Fordjour Antwi-Afari , Shahnawaz Anwer

{"title":"Deep learning-based fatigue monitoring of construction workers using physiological signals","authors":"Waleed Umer , Imran Mehmood , Yazan Qarout , Maxwell Fordjour Antwi-Afari , Shahnawaz Anwer","doi":"10.1016/j.autcon.2025.106356","DOIUrl":"10.1016/j.autcon.2025.106356","url":null,"abstract":"<div><div>Construction workers often suffer from physical fatigue, leading to health issues, quality compromises, and accidents. Previous research on fatigue monitoring using physiological measures has three main limitations: inappropriate benchmarking with the Ratings of Perceived Exertion (RPE) scale, which poorly correlates with actual field fatigue; data collection in controlled settings; and ignoring the time-series nature of physiological signals. These issues question the applicability of such measures for monitoring fatigue on active job sites. This paper introduces an approach leveraging deep learning models and physiological data, using appropriate benchmarks and comprehensive on-site data collection. The approach was evaluated using metrics such as accuracy, precision, recall, specificity, and the F1 Score. Results showed models like Bi-LSTM achieved up to 98.5 % accuracy, validating the effectiveness of physiological signals. This paper contributes to automation in construction by developing deep learning models for fatigue monitoring that can automate safety-related concerns for construction workers and managers.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"177 ","pages":"Article 106356"},"PeriodicalIF":9.6,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330184","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

Digital technologies for monitoring hazardous area entry in construction sites 监测建筑工地危险区域进入的数字技术

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-06-20 DOI: 10.1016/j.autcon.2025.106357

Si Van-Tien Tran , Hai Chien Pham , Quang Tuan Le , Ung-Kyun Lee

{"title":"Digital technologies for monitoring hazardous area entry in construction sites","authors":"Si Van-Tien Tran , Hai Chien Pham , Quang Tuan Le , Ung-Kyun Lee","doi":"10.1016/j.autcon.2025.106357","DOIUrl":"10.1016/j.autcon.2025.106357","url":null,"abstract":"<div><div>Construction sites are among the most hazardous occupational environments, making effective monitoring systems for hazardous area entry essential to prevent fatalities and severe injuries. Despite a growing body of research on advanced monitoring technologies, a systematic review remains necessary. Utilizing the PRISMA methodology, this paper analyzes 81 peer-reviewed articles, categorizing hazardous area entry scenarios into three distinct patterns: personnel entry into static hazards, interactions with dynamic hazards, and overlapping multi-equipment operations. The findings highlight prominent digital technologies, with computer vision (CV), Internet of Things (IoT), and integrated solutions representing 37 %, 42 %, and 21 % of the reviewed articles, respectively. Additionally, the analysis identifies several challenges, including limitations of current CV and IoT technologies and difficulties in deploying these solutions under dynamic construction conditions. The study outlines opportunities to enhance system intelligence, refine deployment strategies, and better integrate safety training, guiding future advancements in construction safety monitoring, particularly regarding hazardous area entry.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"177 ","pages":"Article 106357"},"PeriodicalIF":9.6,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144321952","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

Ontology-based representation of quality assurance and inspection planning in construction 基于本体的施工质量保证与检验规划表示

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-06-20 DOI: 10.1016/j.autcon.2025.106268

Sebastian Seiß , Yuan Zheng , Jürgen Melzner , Jan Wium , Olli Seppänen

引用次数: 0

From automation to agency: Prototype for self-owning intelligent buildings enabled by blockchain 从自动化到代理：区块链实现的自主智能建筑原型

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-06-20 DOI: 10.1016/j.autcon.2025.106309

Hongyang Wang , Jens J. Hunhevicz , Daniel M. Hall

引用次数: 0

Form-finding and metaheuristic multiobjective optimization methodology for sustainable gridshells with reduced construction complexity and waste 可持续性网格壳的寻形与元启发式多目标优化方法

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-06-20 DOI: 10.1016/j.autcon.2025.106315

Jonathan Melchiorre , Amedeo Manuello Bertetto , Sigrid Adriaenssens , Giuseppe Carlo Marano

{"title":"Form-finding and metaheuristic multiobjective optimization methodology for sustainable gridshells with reduced construction complexity and waste","authors":"Jonathan Melchiorre , Amedeo Manuello Bertetto , Sigrid Adriaenssens , Giuseppe Carlo Marano","doi":"10.1016/j.autcon.2025.106315","DOIUrl":"10.1016/j.autcon.2025.106315","url":null,"abstract":"<div><div>The construction industry is one of the sectors with the highest environmental impact, yet it constitutes an important part of the global economy. Therefore, minor improvements in this sector can lead to substantial global benefits. Structural optimization protocols offer promising solutions to this challenge, especially for gridshell structures. Given the complexities involved in constructing gridshells, optimization techniques can play a crucial role in enhancing design by reducing material usage, and improving construction efficiency. This paper presents a methodology for the optimization of gridshell structures using the NSGA II optimization algorithm, combined with the improved Multi-body Rope Approach (i-MRA) form-finding method. The primary objective of this methodology is to minimize the variety of structural elements, reduce material consumption, decrease production waste, and ensure adherence to structural verification standards. This methodology provides an efficient approach for the conceptual design of gridshell structures.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"177 ","pages":"Article 106315"},"PeriodicalIF":9.6,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330259","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

LLM agent framework for intelligent change analysis in urban environment using remote sensing imagery 基于遥感影像的城市环境智能变化分析的LLM代理框架

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-06-19 DOI: 10.1016/j.autcon.2025.106341

Zixuan Xiao, Jun Ma

{"title":"LLM agent framework for intelligent change analysis in urban environment using remote sensing imagery","authors":"Zixuan Xiao, Jun Ma","doi":"10.1016/j.autcon.2025.106341","DOIUrl":"10.1016/j.autcon.2025.106341","url":null,"abstract":"<div><div>Existing change detection methods often lack the versatility to handle diverse real-world queries and the intelligence for comprehensive analysis. This paper presents a general agent framework, integrating Large Language Models (LLM) with vision foundation models to form ChangeGPT. A hierarchical structure is employed to mitigate hallucination. The agent was evaluated on a curated dataset of 140 questions categorized by real-world scenarios, encompassing various question types (e.g., Size, Class, Number) and complexities. The evaluation assessed the agent's tool selection ability (Precision/Recall) and overall query accuracy (Match). ChangeGPT, especially with a GPT-4-turbo backend, demonstrated superior performance, achieving a 90.71 % Match rate. Its strength lies particularly in handling change-related queries requiring multi-step reasoning and robust tool selection. Practical effectiveness was further validated through a real-world urban change monitoring case study in Qianhai Bay, Shenzhen. By providing intelligence, adaptability, and multi-type change analysis, ChangeGPT offers a powerful solution for decision-making in remote sensing applications.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"177 ","pages":"Article 106341"},"PeriodicalIF":9.6,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144312530","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