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Advanced Visualization and Accessibility to Heterogeneous Monitoring Data
Structural health monitoring (SHM) is a promising tool for better management of infrastructure. However, failure to manage large amounts of SHM data properly is a big barrier for its widespread application. Data management is especially challenging when heterogeneous data are involved and combined w...
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Published in: | Computer-aided civil and infrastructure engineering 2014-05, Vol.29 (5), p.382-398 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Structural health monitoring (SHM) is a promising tool for better management of infrastructure. However, failure to manage large amounts of SHM data properly is a big barrier for its widespread application. Data management is especially challenging when heterogeneous data are involved and combined with camera images. Various sensors based on different technologies can measure many parameters such as strain, tilt, weather, etc., whereas live cameras can visualize traffic response. In addition, all the data streams can be registered both statically and dynamically. Data management is even more complex if multiple users access the data and have diverse backgrounds and interests (e.g., the owner/manager of the structure, operator, responsible engineer, and academic). In this article, general principles for SHM data management are researched, established, and proposed by the authors, and an original solution for data management based on these principles is presented. For validation purposes, the proposed principles were implemented in novel data management software and applied to a signature bridge. Feedback from interested groups including the managers, operators, engineers of record, and academics is used for validation. Thus, this article details the researched and proposed accessibility and visualization principles, and conceptual development of novel solution for data management, which combines computer science, internet omnipresence, and structural engineering. |
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ISSN: | 1093-9687 1467-8667 |
DOI: | 10.1111/mice.12060 |