Virtual Environments for Visualizing Structural Health Monitoring Sensor Networks, Data, and Metadata
Visualization of sensor networks, data, and metadata is becoming one of the most pivotal aspects of the structural health monitoring (SHM) process. Without the ability to communicate efficiently and effectively between disparate groups working on a project, an SHM system can be underused, misunderstood, or even abandoned. For this reason, this work seeks to evaluate visualization techniques in the field, identify flaws in current practices, and devise a new method for visualizing and accessing SHM data and metadata in 3D. More precisely, the work presented here reflects a method and digital workflow for integrating SHM sensor networks, data, and metadata into a virtual reality environment by combining spherical imaging and informational modeling. Both intuitive and interactive, this method fosters communication on a project enabling diverse practitioners of SHM to efficiently consult and use the sensor networks, data, and metadata. The method is presented through its implementation on a case study, Streicker Bridge at Princeton University campus. To illustrate the efficiency of the new method, the time and data file size were compared to other potential methods used for visualizing and accessing SHM sensor networks, data, and metadata in 3D. Additionally, feedback from civil engineering students familiar with SHM is used for validation. Recommendations on how different groups working together on an SHM project can create SHM virtual environment and convey data to proper audiences, are also included.
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- Record URL:
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/14248220
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Supplemental Notes:
- © 2018 Rebecca Napolitano et al.
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Authors:
- Napolitano, Rebecca
- Blyth, Anna
- Glisic, Branko
- Publication Date: 2018-1
Language
- English
Media Info
- Media Type: Web
- Features: Figures; Photos; References; Tables;
- Pagination: 14p
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Serial:
- Sensors
- Volume: 18
- Issue Number: 1
- Publisher: MDPI AG
- ISSN: 1424-8220
- Serial URL: http://www.mdpi.com/journal/sensors
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Publication flags:
Open Access (libre)
Subject/Index Terms
- TRT Terms: Case studies; Data analysis; Footbridges; Metadata; Networks; Sensors; Structural health monitoring; Visualization
- Identifier Terms: Princeton University
- Subject Areas: Bridges and other structures; Data and Information Technology; Highways;
Filing Info
- Accession Number: 01669858
- Record Type: Publication
- Files: TRIS
- Created Date: May 22 2018 5:20PM