Augmented Reality-Based Embedded Sensor Location Recognition and Data Visualization Technique for Concrete Structural Health Monitoring

Woong Ki Park; Hyun Uk Kim; Chang Gil Lee; Seung Hee Park

doi:10.4028/www.scientific.net/AMM.281.593

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Auto-Mesh Generation Technique of Near Field Zone for Soil-Structure Interaction Analysis Using Coupled FE-IE Methodology
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Augmented Reality-Based Embedded Sensor Location Recognition and Data Visualization Technique for Concrete Structural Health Monitoring
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 281Augmented Reality-Based Embedded Sensor Location...

Augmented Reality-Based Embedded Sensor Location Recognition and Data Visualization Technique for Concrete Structural Health Monitoring

Abstract:

In recent years, numerous mega-sized and complex civil infrastructures are being constructed all over the world. Therefore, more precise construction and maintenance technologies are required for these complicated construction projects. So a variety of sensors-based structural health monitoring (SHM) techniques have been studied, but these techniques could not manage the sensors efficiently access the database obtained from the sensors. Recently, Quick response (QR) code and AR-based data access technologies have been developed. In this paper, an AR-based concrete curing strength monitoring technique for sensor management and efficient access of the measured data is introduced. It is confirmed that the AR-based concrete curing strength monitoring technique is useful for construction process. In addition, it is concluded that both efficient sensor location recognition and data visualization at anytime, anywhere, and any smart PC devices are promising.

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Periodical:

Applied Mechanics and Materials (Volume 281)

Pages:

593-596

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.281.593

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Online since:

January 2013

Authors:

Woong Ki Park, Hyun Uk Kim, Chang Gil Lee, Seung Hee Park

Keywords:

Augmented Reality (AR), Data Visualization, Sensor Location Recognition, Structure Health Monitoring

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