Ontologies-Based Domain Knowledge Modeling and Heterogeneous Sensor Data Integration for Bridge Health Monitoring Systems
| Autor: | Ren Li, Tong Li, Yiming Liu, Shixin Jiang, Tianjin Mo, Jianxi Yang |
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| Rok vydání: | 2021 |
| Předmět: |
Computer science
business.industry Information sharing Distributed computing 020208 electrical & electronic engineering Big data 02 engineering and technology Ontology (information science) computer.software_genre Bridge (interpersonal) Computer Science Applications Data modeling Control and Systems Engineering 0202 electrical engineering electronic engineering information engineering Ontology Domain knowledge Structural health monitoring Electrical and Electronic Engineering business Semantic Web computer Information Systems Data integration |
| Zdroj: | IEEE Transactions on Industrial Informatics. 17:321-332 |
| ISSN: | 1941-0050 1551-3203 |
| Popis: | Structural health monitoring (SHM) systems have been extensively used to ensure the operational safety of long-span bridges. Large-scale bridge structural response and loading data observed from various sensors show obvious big data characteristics. However, serious “data island” problems, which exist in the conventional SHM solutions, inevitably limit the effects of sensory data analysis and information sharing. A unified bridge SHM semantic representation model is much in demand. By taking the advantages of Semantic Web technologies, this article presents a novel model, called the bridge structure and health monitoring ontology, to achieve fine-grained modeling of bridge structures, SHM systems, sensors, and sensory data from multiple perspectives. A bridge SHM big data platform is used to demonstrate the usefulness. Several representative data accessing and rule-based reasoning scenarios are employed as to illustrate the advantages of the proposed manner. |
| Databáze: | OpenAIRE |
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