{"title":"Artificial intelligence in construction: Topic-based technology mapping based on patent data","authors":"Guangbin Wang, Yiwei Zhou, Dongping Cao","doi":"10.1016/j.autcon.2025.106073","DOIUrl":null,"url":null,"abstract":"<div><div>Artificial intelligence (AI) is spreading rapidly in the construction domain with high expectations and distinct innovation challenges. While many scholars have conducted literature reviews on the development status of AI in construction, patent data, which can objectively reflect technological evolution, is rarely analyzed. This paper conducted the patent analysis to reveal the application hotspots and evolutionary trends of AI in construction. Descriptive analysis showed that China held the majority of patents and the United States played a crucial role in knowledge transfer. The results further indicated that machine learning and computer vision were the most prevalent technologies, while structural health monitoring and safety management were the hottest topics. Additionally, this paper depicted the technology transfer landscape, and forecasted the evolutionary trends of AI technologies. This paper provides valuable insights into AI in construction from a new perspective of patent, and offers references to engineers, managers and policymakers in this field.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"172 ","pages":"Article 106073"},"PeriodicalIF":9.6000,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automation in Construction","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S092658052500113X","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial intelligence (AI) is spreading rapidly in the construction domain with high expectations and distinct innovation challenges. While many scholars have conducted literature reviews on the development status of AI in construction, patent data, which can objectively reflect technological evolution, is rarely analyzed. This paper conducted the patent analysis to reveal the application hotspots and evolutionary trends of AI in construction. Descriptive analysis showed that China held the majority of patents and the United States played a crucial role in knowledge transfer. The results further indicated that machine learning and computer vision were the most prevalent technologies, while structural health monitoring and safety management were the hottest topics. Additionally, this paper depicted the technology transfer landscape, and forecasted the evolutionary trends of AI technologies. This paper provides valuable insights into AI in construction from a new perspective of patent, and offers references to engineers, managers and policymakers in this field.
期刊介绍:
Automation in Construction is an international journal that focuses on publishing original research papers related to the use of Information Technologies in various aspects of the construction industry. The journal covers topics such as design, engineering, construction technologies, and the maintenance and management of constructed facilities.
The scope of Automation in Construction is extensive and covers all stages of the construction life cycle. This includes initial planning and design, construction of the facility, operation and maintenance, as well as the eventual dismantling and recycling of buildings and engineering structures.