Automation in Construction最新文献_第7页

Semi-supervised method for automated detection and quantitative assessment of corrosion states in structural members 结构构件腐蚀状态自动检测和定量评估的半监督方法

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-04-03 DOI: 10.1016/j.autcon.2025.106155

Yonghui An , Lingxue Kong , Chuanchuan Hou , Jinping Ou

{"title":"Semi-supervised method for automated detection and quantitative assessment of corrosion states in structural members","authors":"Yonghui An , Lingxue Kong , Chuanchuan Hou , Jinping Ou","doi":"10.1016/j.autcon.2025.106155","DOIUrl":"10.1016/j.autcon.2025.106155","url":null,"abstract":"<div><div>Accurate detection and comprehensive assessment of corrosion states are essential for bridge safety and durability. Deep learning-based semantic segmentation methods show significant potential for corrosion detection. However, supervised methods confront substantial challenges in labor-intensive annotation and limited datasets. To address these challenges, a semi-supervised method for corrosion state segmentation (Model A) and structural member segmentation (Model B) is proposed. It adopts the weak-to-strong semi-supervised framework with SE attention and a random cut strategy, outperforming supervised methods with only 40 % labeled corrosion and 20 % labeled member images. New evaluation metrics are established to evaluate the integrated results of Model A and Model B. A smartphone-based mobile detection platform is developed to achieve automatic corrosion detection and quantitative assessments. The proposed method achieves high accuracy with limited manual annotations, offering an advanced and intelligent solution for detecting, quantifying, and managing corrosion states on bridge structural members.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"174 ","pages":"Article 106155"},"PeriodicalIF":9.6,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143759093","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

Towards an integrative framework for BIM and artificial intelligence capabilities in smart architecture, engineering, construction, and operations projects 为智能建筑、工程、施工和运营项目中的 BIM 和人工智能能力制定综合框架

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-04-03 DOI: 10.1016/j.autcon.2025.106168

Josivan Leite Alves , Rachel Perez Palha , Adiel Teixeira de Almeida Filho

{"title":"Towards an integrative framework for BIM and artificial intelligence capabilities in smart architecture, engineering, construction, and operations projects","authors":"Josivan Leite Alves , Rachel Perez Palha , Adiel Teixeira de Almeida Filho","doi":"10.1016/j.autcon.2025.106168","DOIUrl":"10.1016/j.autcon.2025.106168","url":null,"abstract":"<div><div>The Architecture, Engineering, Construction, and Operations (AECO) sector gains significant advantages through generating and effectively managing BIM data. This increased available data can be fundamental in deriving innovative advances by processing them through artificial intelligence (AI) models. In this context, this paper investigates how BIM and AI capabilities can benefit the development of smart AECO projects. The research design is a systematic literature review, applying bibliometric and content analysis. First, the paper explores the relationships between the topics of AI and BIM applications, identifies seven core domains of BIM and AI finds application, explores research contributions, the problems addressed, and their primary outcomes. Second, the paper maps out 14 BIM and 16 AI capabilities fundamental to developing smart projects. Third, three propositions that sustain an integrative framework are suggested. The article also suggests that practitioners identify critical organizational capabilities to be built and strengthened.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"174 ","pages":"Article 106168"},"PeriodicalIF":9.6,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143759095","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 in architectural design: Application, data, and evaluation methods 建筑设计中的生成式人工智能：应用、数据和评估方法

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-04-03 DOI: 10.1016/j.autcon.2025.106174

Suhyung Jang, Hyunsung Roh, Ghang Lee

引用次数: 0

IFC framework for inspection and maintenance representation in facility management 国际金融公司在设施管理中检查和维护代表的框架

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-04-02 DOI: 10.1016/j.autcon.2025.106157

Fernando Gussão Bellon, Ana Carolina Pereira Martins, José Maria Franco de Carvalho, Christian Alexandre Feitosa de Souza, José Carlos Lopes Ribeiro, Kléos Magalhães Lenz César Júnior, Diôgo Silva de Oliveira

{"title":"IFC framework for inspection and maintenance representation in facility management","authors":"Fernando Gussão Bellon, Ana Carolina Pereira Martins, José Maria Franco de Carvalho, Christian Alexandre Feitosa de Souza, José Carlos Lopes Ribeiro, Kléos Magalhães Lenz César Júnior, Diôgo Silva de Oliveira","doi":"10.1016/j.autcon.2025.106157","DOIUrl":"10.1016/j.autcon.2025.106157","url":null,"abstract":"<div><div>Effectively managing inspection and maintenance data in facility management remains challenging due to the lack of structured and interoperable data representation. This paper explores how the IFC schema can be leveraged to standardize inspection, damage, maintenance, and maintenance cost data representation. To this end, an IFC-based framework was developed to ensure semantic consistency and interoperability in the representation of inspection and maintenance data. The framework was validated through IFC schema verification and semantic evaluation of generated case studies across multiple BIM software, demonstrating its applicability for facility management, maintenance planning, and asset monitoring of buildings, industrial plants, and infrastructure projects. By enabling and standardizing structured information exchange, the proposed framework enhances decision-making in facility management workflows. Future work should focus on extending its application in real-world scenarios, specifically through integration with facility management systems and automated data acquisition technologies.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"174 ","pages":"Article 106157"},"PeriodicalIF":9.6,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143746565","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

Dynamic optimization of maintenance strategy for bridges in regional transportation network through semi-Markov processes 基于半马尔可夫过程的区域交通网络桥梁养护策略动态优化

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-04-02 DOI: 10.1016/j.autcon.2025.106175

Xiaoling Liu , Ying Liu , Zhe Sun , Bing Wang , Yinfei Zhao

引用次数: 0

Vision-based damage identification for beam-type structures using area scanning without calibration 基于视觉的无标定区域扫描梁式结构损伤识别

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-04-01 DOI: 10.1016/j.autcon.2025.106156

Panjie Li , Shuaihui Yan , Menghao Hu , Can Cui , Jinke Li , Yuyang Pang

引用次数: 0

Generative adversarial network for real-time identification and pixel-level annotation of highway pavement distresses 基于生成对抗网络的公路路面损伤实时识别与像素级标注

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-04-01 DOI: 10.1016/j.autcon.2025.106122

Mark Amo-Boateng, Yaw Adu-Gyamfi

{"title":"Generative adversarial network for real-time identification and pixel-level annotation of highway pavement distresses","authors":"Mark Amo-Boateng, Yaw Adu-Gyamfi","doi":"10.1016/j.autcon.2025.106122","DOIUrl":"10.1016/j.autcon.2025.106122","url":null,"abstract":"<div><div>Efficient analysis of road pavement distresses is crucial for infrastructure management and safety. Traditional methods are labor-intensive, and recent deep-learning approaches face challenges such as overlapping bounding boxes and poor pixel localization. This paper presents PaveGAN, a real-time method to identify and annotate pavement distresses using generative adversarial networks. While trained on several loss functions, PaveGAN achieved its best mean absolute percentage errors of 1.49%, 1.15%, and 3.26% for the mean squared error, Huber loss, and structured similarity index, respectively, at the pixel level. With intersection over union scores exceeding 90% for several distresses, and operating at 89.15 frames per second, PaveGAN is suitable for real-time applications. Independent evaluations show its annotation accuracy aligns closely with human experts, achieving 84% accuracy versus 86% for manual annotations. By automating pixel-level annotation in widely used formats such as COCO and LabelMe, PaveGAN provides a scalable, cost-effective solution for pavement distress monitoring.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"174 ","pages":"Article 106122"},"PeriodicalIF":9.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143746563","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

Asphalt concrete density monitoring during compaction using roller-mounted GPR 用滚轮式探地雷达监测压实过程中沥青混凝土的密度

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-04-01 DOI: 10.1016/j.autcon.2025.106158

Lama Abufares, Yihan Chen, Imad L. Al-Qadi

引用次数: 0

Lifecycle framework for AI-driven parametric generative design in industrialized construction 工业化建筑中人工智能驱动参数生成设计的生命周期框架

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-03-31 DOI: 10.1016/j.autcon.2025.106146

Maggie Y. Gao , Chao Li , Frank Petzold , Robert L.K. Tiong , Yaowen Yang

{"title":"Lifecycle framework for AI-driven parametric generative design in industrialized construction","authors":"Maggie Y. Gao , Chao Li , Frank Petzold , Robert L.K. Tiong , Yaowen Yang","doi":"10.1016/j.autcon.2025.106146","DOIUrl":"10.1016/j.autcon.2025.106146","url":null,"abstract":"<div><div>In the Architecture, Engineering, and Construction (AEC) industry, design processes remain fragmented across architectural, structural, and mechanical domains, limiting integration and optimization opportunities throughout building lifecycles. This paper investigates how artificial intelligence can be leveraged to create a comprehensive framework for parametric generative design in industrialized construction that integrates multiple design disciplines and optimization criteria. The methodology employs knowledge graph question answering (KGQA) enabled by large language models (LLMs) to acquire design requirements and constraints, implements multi-objective optimization algorithms to balance competing criteria, and establishes a three-tier priority hierarchy to resolve conflicts in cross-domain design processes. The framework demonstrates significant improvements in a real-world case study, achieving 15.8 % reduction in lifecycle costs, 21.2 % decrease in energy consumption, and significantly reducing preliminary design modelling time. These findings provide valuable insights for AEC practitioners seeking to implement human-AI collaborative design workflows and illustrate pathways for integrating domain-specific knowledge with advanced AI systems.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"174 ","pages":"Article 106146"},"PeriodicalIF":9.6,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143746560","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

Parametric modeling and evolutionary method for predictive maintenance of marine reinforced concrete structures 海洋钢筋混凝土结构预测维修的参数化建模与演化方法

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2025-03-29 DOI: 10.1016/j.autcon.2025.106154

Ren-jie Wu , Jin-quan Wang , Jin Xia

{"title":"Parametric modeling and evolutionary method for predictive maintenance of marine reinforced concrete structures","authors":"Ren-jie Wu , Jin-quan Wang , Jin Xia","doi":"10.1016/j.autcon.2025.106154","DOIUrl":"10.1016/j.autcon.2025.106154","url":null,"abstract":"<div><div>The absence of an efficient maintenance method has incurred substantial additional costs, emerging as the primary impediment to the advancement of marine reinforced concrete (RC) structures. This paper proposes a parametric modeling and evolutionary optimization method to improve the cost-effectiveness ratio of structural maintenance. The deterioration risk distribution of the entire structural system is established through parametric modeling. An evolutionary optimization method grounded in genetic algorithm (GA) is utilized to determine the optimal maintenance sizes, followed by the space-time-dependent survival probability route (STSPR) method to refine the maintenance times for each specific maintenance size. The Hangzhou Bay cross-sea Bridge in China is used to illustrate the practicality of the proposed method. The results indicate a cost-effectiveness ratio reduction of 63.3 %, 58.1 %, and 3.1 % and a lifetime extension of 9.1 %, 24.7 %, and 1.7 % for bridge piers, bridge wet joints, and bridge caps, respectively, compared to the sequential failure limit method.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"174 ","pages":"Article 106154"},"PeriodicalIF":9.6,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725242","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