Bo Xiao , Yifan Wang , Yongpan Zhang , Chen Chen , Amos Darko
{"title":"Automated daily report generation from construction videos using ChatGPT and computer vision","authors":"Bo Xiao , Yifan Wang , Yongpan Zhang , Chen Chen , Amos Darko","doi":"10.1016/j.autcon.2024.105874","DOIUrl":null,"url":null,"abstract":"<div><div>Daily reports are important in construction management, informing project teams about status, enabling timely resolutions of delays and budget issues, and serving as official records for disputes and litigation. However, current practices are manual and time-consuming, requiring engineers to physically visit sites for observations. To fill this gap, this paper proposes an automated framework to generate daily construction reports from on-site videos by integrating ChatGPT and computer vision (CV)-based methods. The framework utilizes CV methods to analyze video footage and extract relevant productivity and activity information, which is then fed into ChatGPT using proper prompts to generate daily reports. A web application is developed to implement and validate the framework on a real construction site in Hong Kong, generating daily reports over a month. This research enhances construction management by significantly reducing documentation efforts through generative artificial intelligence, with potential applications in jobsite safety management, quality reporting, and stakeholder communication.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"168 ","pages":"Article 105874"},"PeriodicalIF":9.6000,"publicationDate":"2024-11-21","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/S0926580524006101","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
Daily reports are important in construction management, informing project teams about status, enabling timely resolutions of delays and budget issues, and serving as official records for disputes and litigation. However, current practices are manual and time-consuming, requiring engineers to physically visit sites for observations. To fill this gap, this paper proposes an automated framework to generate daily construction reports from on-site videos by integrating ChatGPT and computer vision (CV)-based methods. The framework utilizes CV methods to analyze video footage and extract relevant productivity and activity information, which is then fed into ChatGPT using proper prompts to generate daily reports. A web application is developed to implement and validate the framework on a real construction site in Hong Kong, generating daily reports over a month. This research enhances construction management by significantly reducing documentation efforts through generative artificial intelligence, with potential applications in jobsite safety management, quality reporting, and stakeholder communication.
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.