Application of a Data-Driven Intelligent Information System in Infrastructure: Underwater Tunnel Case Study
Publication: Journal of Performance of Constructed Facilities
Volume 37, Issue 1
Abstract
The 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.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work is supported by the National Natural Science Foundation of China under Grant Nos. U1806226, 51991395, and 51991392 and Key deployment projects of Chinese Academy of Sciences No. ZDRW-ZS-2021-3-3. The authors are grateful to the reviewers and editors for their valuable comments and suggestions that helped to improve the quality of the paper.
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Information & Authors
Information
Published In
Journal of Performance of Constructed Facilities
Volume 37 • Issue 1 • February 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Nov 29, 2021
Accepted: Sep 13, 2022
Published online: Nov 8, 2022
Published in print: Feb 1, 2023
Discussion open until: Apr 8, 2023
ASCE Technical Topics:
- Artificial intelligence and machine learning
- Case studies
- Computer programming
- Computing in civil engineering
- Data analysis
- Engineering fundamentals
- Geotechnical engineering
- Information management
- Information systems
- Infrastructure
- Methodology (by type)
- Research methods (by type)
- Structural engineering
- Structures (by type)
- Systems engineering
- Tunnels
- Underwater structures
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