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Abstract

To realize the comprehensive intelligent upgrade of the Three Gorges Dam safety intelligent monitoring system (IMS), we focus on three core pillars real-time information processing, professional analytical evaluation, and digital management control systematically overcoming critical technical bottlenecks. By deeply integrating artificial intelligence (AI), Internet of Things (IOT), big data analysis, and geographic information system + building information modeling (GIS + BIM) ecosystems, we conducted a holistic diagnosis of existing monitoring systems to precisely identify operational pain points. Leveraging our proprietary innovations, including a GIS + BIM digital base, smart algorithm matrix, and BIM-based finite element computing system, we successfully developed the Three Gorges Dam intelligent monitoring platform, delivering five core value propositions: (1) Achieve real-time and historical aggregation of comprehensive data with dam safety management as the core, fully encompassing various types of environmental monitoring data. (2) Utilizing “GIS + BIM” as the technical foundation, construct a digital twin geometric model of the hub monitoring physical world, enabling intuitive and precise representation of engineering status. (3) Implement online rapid structural calculation, analysis, and early warning based on “BIM + Finite Element” technology, providing timely and reliable support for safety decision-making. (4) Establish a monitoring data analysis model through machine learning intelligent algorithms, deeply mining data value to enable intelligent prediction of potential safety hazards. (5) Promote digital transformation of manual inspection workflows using “IOT + Micro-INS” technology, enhancing inspection efficiency and accuracy. Additionally, our workflow engine ensures full-process digital collaboration across safety monitoring operations, guaranteeing seamless interdepartmental coordination. These innovations have not only enhanced safety management efficiency but also cemented the Three Gorges Dam’s global leadership in hydraulic engineering. As a landmark achievement in national strategic infrastructure, it exemplifies the digital transformation of mega-scale engineering projects in the modern era.

Details

1009240
Title
Online Intelligent Monitoring System and Key Technologies for Dam Operation Safety
Author
Li, Shuangping 1 ; Zhang, Bin 1 ; Tong, Guangqin 2 ; Li, Yonghua 1   VIAFID ORCID Logo  ; Liu, Zuqiang 1 ; Shi, Bo 1 ; Geng, Jun 2 ; Liu, Dingming 2 ; Wang, Huawei 1 ; Ai, Qingsong 3   VIAFID ORCID Logo  ; Ding, Jianxin 4 ; Gan, Zheng 1 

 Changjiang Spatial Information Technology Engineering Co., Ltd. Wuhan Hubei China; Hubei Water Conservancy Information Perception and Big Data Engineering Technology Research Center Wuhan Hubei China 
 China Three Gorges Corporation River Basin Complex Administration Center Yichang Hubei China; Hubei Key Laboratory of Operation Safety of High Dam and Large Reservoir Yichang Hubei China 
 Changjiang Spatial Information Technology Engineering Co., Ltd. Wuhan Hubei China; Hubei Water Conservancy Information Perception and Big Data Engineering Technology Research Center Wuhan Hubei China; Changjiang Institute of Survey, Planning, Design and Research Co., Ltd. Wuhan Hubei China 
 Changjiang Institute of Survey, Planning, Design and Research Co., Ltd. Wuhan Hubei China 
Editor
Xing Wang
Publication title
Volume
2025
Publication year
2025
Publication date
2025
Publisher
John Wiley & Sons, Inc.
Place of publication
New York
Country of publication
United States
Publication subject
ISSN
16878086
e-ISSN
16878094
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Milestone dates
2024-09-21 (Received); 2025-02-28 (Accepted); 2025-03-26 (Pub)
ProQuest document ID
3186839119
Document URL
https://www.proquest.com/scholarly-journals/online-intelligent-monitoring-system-key/docview/3186839119/se-2?accountid=208611
Copyright
Copyright © 2025 Shuangping Li et al. Advances in Civil Engineering published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License (the “License”), which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0/
Last updated
2025-07-22
Database
ProQuest One Academic