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contributor authorXuyan Tan
contributor authorWeizhong Chen
contributor authorJianping Yang
contributor authorXianjun Tan
date accessioned2023-08-16T19:21:31Z
date available2023-08-16T19:21:31Z
date issued2023/02/01
identifier otherJPCFEV.CFENG-4046.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4293146
description abstractThe intelligent management of infrastructure is crucial to maintain structural stability. Although much more attention has been paid to the development of intelligent systems, the cooperation and efficiency of different components in the system is still a remaining problem. Along this line, an optimized intelligent information system (IIS) driven by big-data technology is proposed for the smart management of infrastructure. First, the integration framework of IIS is proposed, including data collection and storage, data analysis, and data expression modules. According to this framework, the remaining problems existing in each component are pointed out and the corresponding optimization measures are given. Especially for the processing technology of massive monitoring data, some trained machine learning algorithms are introduced for data analysis. As a case study, the devised system was adopted in an underwater shield tunnel for real-time monitoring, big data analysis, and information visualization. The intelligent system and advanced data-driven models presented in this study are suitable for most infrastructures, affording useful smart management experience and data processing technology for other underground projects and promoting the intelligent development of civil engineering.
publisherAmerican Society of Civil Engineers
titleApplication of a Data-Driven Intelligent Information System in Infrastructure: Underwater Tunnel Case Study
typeJournal Article
journal volume37
journal issue1
journal titleJournal of Performance of Constructed Facilities
identifier doi10.1061/JPCFEV.CFENG-4046
journal fristpage04022069-1
journal lastpage04022069-12
page12
treeJournal of Performance of Constructed Facilities:;2023:;Volume ( 037 ):;issue: 001
contenttypeFulltext


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