Automation in Construction最新文献

BIM-based terrestrial laser scanning path planning for large-scale civil infrastructure 基于bim的大型民用基础设施地面激光扫描路径规划

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-08-02 DOI: 10.1016/j.autcon.2025.106439

Jinsong Zhu , Duowu Wang , Zhongqiu Fu , Zeyu Zhang , Weinan Han

引用次数: 0

Feasibility of VR-generated synthetic data for automated productivity monitoring in modular construction 虚拟现实生成的综合数据用于模块化建筑自动化生产力监控的可行性

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-08-02 DOI: 10.1016/j.autcon.2025.106432

Jiyun Ban , Daeho Kim , Tae Wan Kim , Byungjoo Choi

引用次数: 0

Model-based topological assessment for selective deconstruction: Enhancing quantity recovery and reuse accuracy 基于模型的选择性解构拓扑评估：提高数量回收和重用的准确性

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-08-01 DOI: 10.1016/j.autcon.2025.106438

Guilherme Eliote , Christopher Rausch , Fernanda Leite

{"title":"Model-based topological assessment for selective deconstruction: Enhancing quantity recovery and reuse accuracy","authors":"Guilherme Eliote , Christopher Rausch , Fernanda Leite","doi":"10.1016/j.autcon.2025.106438","DOIUrl":"10.1016/j.autcon.2025.106438","url":null,"abstract":"<div><div>Design for reuse (DfR) is a key strategy for advancing sustainable construction, yet its adoption remains limited. A major gap is the lack of tools that incorporate topological assessments to support deconstruction and material reuse planning. Existing quantity takeoff (QTO) tools primarily focus on design and virgin material procurement stages, often overlooking the in-situ topology of materials and the realities of disassembly, resulting in inaccurate reuse estimates. To address this, a method is introduced that topologically evaluates structural components within as-built models, identifies connection types using enriched information, and anticipates component availability after deconstruction. Using the results of two institutional building projects, this framework is shown to more accurately estimate quantities of materials at their end of life, facilitating planning and decision-making for sustainable construction initiatives. The main contribution of this paper is the adaptation of conventional QTO practices to better support circular decision-making at the end-of-life stage of construction projects.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"178 ","pages":"Article 106438"},"PeriodicalIF":11.5,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144749469","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

Embedded framework for low-cost pavement condition evaluation using microcontroller and single-board computer platforms 基于单片机和单板计算机平台的低成本路面状况评估嵌入式框架

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-07-31 DOI: 10.1016/j.autcon.2025.106442

Yazan Ibrahim Alatoom, Omar Smadi

{"title":"Embedded framework for low-cost pavement condition evaluation using microcontroller and single-board computer platforms","authors":"Yazan Ibrahim Alatoom, Omar Smadi","doi":"10.1016/j.autcon.2025.106442","DOIUrl":"10.1016/j.autcon.2025.106442","url":null,"abstract":"<div><div>Traditional automated pavement evaluation methods, while effective, are often prohibitively expensive for transportation agencies with limited budgets. This paper presents a framework for developing low-cost embedded-based systems for pavement condition evaluation using microcontroller and single-board computer platforms. The paper focuses on providing guidance to transportation agencies for creating customized pavement monitoring solutions that are low-cost and flexible. A comprehensive set of criteria for component selection and system integration are discussed from a civil engineering perspective, emphasizing practical considerations. To demonstrate the framework's application, a case study featuring the development of a multi-sensor device integrating various sensors with a single-board computer platform is presented. The proof-of-concept implementation validates the framework's effectiveness for creating tailored pavement monitoring systems. Preliminary results confirm the system's data collection capabilities across multiple pavement condition indicators. The methodology, selection criteria, and implementation considerations provide a foundation for transportation agencies to develop affordable, fit-for-purpose pavement evaluation solutions.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"178 ","pages":"Article 106442"},"PeriodicalIF":11.5,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144739218","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

Graph-based method for extracting spatial information from semi-formal text to derive 3D bridge and damage models from legacy maintenance data 基于图的方法从半正式文本中提取空间信息，从遗留维护数据中导出三维桥梁和损伤模型

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-07-31 DOI: 10.1016/j.autcon.2025.106418

Anne Göbels, Jakob Beetz

{"title":"Graph-based method for extracting spatial information from semi-formal text to derive 3D bridge and damage models from legacy maintenance data","authors":"Anne Göbels, Jakob Beetz","doi":"10.1016/j.autcon.2025.106418","DOIUrl":"10.1016/j.autcon.2025.106418","url":null,"abstract":"<div><div>Aging bridges require improved maintenance strategies; however, recent developments often rely on newly collected data to represent the bridge and its condition, hindering their large-scale adoption and thus significant improvements. This paper demonstrates how existing data from legacy bridge management systems (BMS) can be utilized to automatically create object-oriented knowledge graphs and three-dimensional models of bridge structures and their inspection data. It applies a relative spatial reference system to position and link components and damage, generating a bridge maintenance graph from BMS data that supports spatial queries using natural-language-based location terms. This enables the automatic localization of recorded damage through their textual location descriptions. The method successfully processed 90% of 2,348 damages from two use cases with a precision of 0.8 and a recall of 0.97. The approach bridges the gap between the needs of modern information models and legacy data structures, facilitating the widespread implementation of improved maintenance strategies.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"178 ","pages":"Article 106418"},"PeriodicalIF":11.5,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144749963","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

Automated machine learning pipeline for robust project cost and duration forecasting 自动化机器学习管道，用于稳健的项目成本和持续时间预测

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-07-30 DOI: 10.1016/j.autcon.2025.106426

Filippo Maria Ottaviani , Pablo Ballesteros-Pérez , Timur Narbaev

引用次数: 0

Free fall simulation-driven synthetic modeling for deep learning-based potential wind-borne debris assessment in jobsites 自由落体模拟驱动的基于深度学习的工地潜在风载碎片评估综合建模

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-07-29 DOI: 10.1016/j.autcon.2025.106437

Mirsalar Kamari , Youngjib Ham

{"title":"Free fall simulation-driven synthetic modeling for deep learning-based potential wind-borne debris assessment in jobsites","authors":"Mirsalar Kamari , Youngjib Ham","doi":"10.1016/j.autcon.2025.106437","DOIUrl":"10.1016/j.autcon.2025.106437","url":null,"abstract":"<div><div>Significant economic losses from extreme winds are caused by Potential Wind-borne Debris (PWDs). Prior studies proposed vision-based approaches for identifying PWDs in jobsites, aiming to manage such debris before wind events, thereby reducing the related risks. However, implementation of these techniques requires substantial training datasets and extensive manual annotation to effectively train neural networks. Moreover, these networks often rely on imbalanced datasets for training, potentially compromising the performance. This paper proposes free fall simulation-driven synthetic models of PWDs in jobsites, reflecting the geometrical characteristics.</div><div>These models are converted into Digital Surface Models (DSM) for training deep learning semantic segmentation. The proposed method was evaluated with case studies using both synthetic and real-world datasets. The experimental results demonstrate that the proposed method mitigates data imbalance issues and reduces the reliance on labor-intensive data preparation, enabling efficient PWD detection for proactive disaster risk management toward resilient jobsites against extreme wind-induced damages.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"178 ","pages":"Article 106437"},"PeriodicalIF":11.5,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144720817","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

Automating exterior BIM for existing buildings using GIS data and UAV-based 3D modeling 使用GIS数据和基于无人机的3D建模自动化现有建筑的外部BIM

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-07-29 DOI: 10.1016/j.autcon.2025.106422

Zeyu Duan , Kunhan Lu , Mingchen Li , Shihong Zhang , Borong Lin , Zhe Wang

引用次数: 0

Explainable data-driven analysis of uncertainty propagation in 3D concrete printing via adaptive polynomial chaos expansion 基于自适应多项式混沌展开的三维混凝土打印不确定性传播可解释数据驱动分析

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-07-29 DOI: 10.1016/j.autcon.2025.106414

Baixi Chen , Xiaoping Qian

{"title":"Explainable data-driven analysis of uncertainty propagation in 3D concrete printing via adaptive polynomial chaos expansion","authors":"Baixi Chen , Xiaoping Qian","doi":"10.1016/j.autcon.2025.106414","DOIUrl":"10.1016/j.autcon.2025.106414","url":null,"abstract":"<div><div>Understanding buildability uncertainty during the printing process remains a major challenge in 3D concrete printing (3DCP). This paper investigates how underlying uncertainty sources influence buildability in 3DCP. An explainable data-driven framework is proposed by integrating adaptive polynomial chaos expansion (aPCE) with Shapley additive explanation (SHAP) to efficiently analyze uncertainty propagation in 3DCP and interpret its underlying mechanisms. Applied to two diverse 3DCP scenarios (a straight wall and a hollow cylinder), the framework achieves accuracy comparable to Monte Carlo simulations with 90% less computational cost, while effectively capturing uncertainty propagation patterns and identifying dominant drivers of buildability uncertainty among potential uncertainty sources. The findings are valuable for 3DCP practitioners and can provide them with actionable insights for mitigating buildability uncertainty, thereby improving the reliability of the printing process. These insights also motivate future research on controlling variability in dominant factors and developing uncertainty-aware process optimization strategies for 3DCP.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"178 ","pages":"Article 106414"},"PeriodicalIF":11.5,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144720816","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

Amodal instance segmentation optimized by metaheuristics for enhanced safety behavior detection on construction sites 基于元启发式优化的模态实例分割增强了建筑工地安全行为检测

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-07-29 DOI: 10.1016/j.autcon.2025.106412

Jui-Sheng Chou, Chi-Jung Chen, Chi-Yun Liu

{"title":"Amodal instance segmentation optimized by metaheuristics for enhanced safety behavior detection on construction sites","authors":"Jui-Sheng Chou, Chi-Jung Chen, Chi-Yun Liu","doi":"10.1016/j.autcon.2025.106412","DOIUrl":"10.1016/j.autcon.2025.106412","url":null,"abstract":"<div><div>Construction projects often experience elevated accident and fatality rates due to their scale and complexity. This paper aims to enhance safety management by addressing falls caused by visual obstructions through the application of amodal instance segmentation (AIS). A You Only Look Once (YOLO) instance segmentation model, trained on the Site Object Detection Dataset along with local personnel images, is used to detect and segment personnel on-site. The Pilgrimage Walk Optimization (PWO)-Lite algorithm is utilized to optimize the model's hyperparameters, thereby enhancing accuracy and performance. To mitigate occlusion issues, segmented masks generated by the PWO-Lite-YOLO model are occluded to produce training data for an amodal mask generation model. This model uses the Pix2Pix framework with conditional Generative Adversarial Networks (cGANs) to generate complete masks of partially obscured personnel. By addressing image occlusion, AIS enhances personnel monitoring and visibility, significantly improving site safety through real-time alerts and better planning, thereby reducing the risk of falls.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"178 ","pages":"Article 106412"},"PeriodicalIF":11.5,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144724330","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