Enhanced digital twin for on-site inspections using distributed optical fiber sensors and augmented reality
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| Název: | Enhanced digital twin for on-site inspections using distributed optical fiber sensors and augmented reality |
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| Autoři: | Fernandez, Ignasi, 1984, Gil Berrocal, Carlos, 1986, Johansson, Mikael, 1987, Roupé, Mattias, 1975, Rempling, Rasmus, 1976 |
| Zdroj: | Automation in Construction. 181 |
| Témata: | Augmented reality, Distributed optic fiber sensors, Enhanced visualization, Inspections, Infrastructure management, Edge computing |
| Popis: | Infrastructure inspections are still largely manual, episodic, and subjective, which delays damage detection and limits data-informed decision making. The paper introduces a Digital Twin framework designed to enhance infrastructure inspections using Distributed Optical Fiber Sensors (DOFS) and Augmented Reality (AR). The framework integrates advanced sensing technologies, edge computing, and web-based applications to provide real-time and historical data visualization during inspections. DOFS technology, known for its high spatial resolution and sensitivity to strain and temperature variations, is utilized to capture high-resolution strain data for continuous structural health monitoring. The framework combines DOFS data with Building Information Modelling (BIM) and AR to create a virtual representation of the assets, enabling precise and efficient on-site inspections. Two case studies demonstrate the practical application of this system: one focusing on historical data visualization and the other on real-time sensor data visualization. The results highlight the framework's ability to provide valuable insights into infrastructure health, improve inspection accuracy, and enhance decision-making processes. |
| Popis souboru: | electronic |
| Přístupová URL adresa: | https://research.chalmers.se/publication/548944 https://research.chalmers.se/publication/548944/file/548944_Fulltext.pdf |
| Databáze: | SwePub |
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Nájsť tento článok vo Web of Science | Abstrakt: | Infrastructure inspections are still largely manual, episodic, and subjective, which delays damage detection and limits data-informed decision making. The paper introduces a Digital Twin framework designed to enhance infrastructure inspections using Distributed Optical Fiber Sensors (DOFS) and Augmented Reality (AR). The framework integrates advanced sensing technologies, edge computing, and web-based applications to provide real-time and historical data visualization during inspections. DOFS technology, known for its high spatial resolution and sensitivity to strain and temperature variations, is utilized to capture high-resolution strain data for continuous structural health monitoring. The framework combines DOFS data with Building Information Modelling (BIM) and AR to create a virtual representation of the assets, enabling precise and efficient on-site inspections. Two case studies demonstrate the practical application of this system: one focusing on historical data visualization and the other on real-time sensor data visualization. The results highlight the framework's ability to provide valuable insights into infrastructure health, improve inspection accuracy, and enhance decision-making processes. |
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| ISSN: | 09265805 |
| DOI: | 10.1016/j.autcon.2025.106602 |