Title: Design and Implementation of a Connection between Augmented Reality and Sensors

Abstract

Wireless sensor networks (WSN) are used by engineers to record the behavior of structures. The sensors provide data to be used by engineers to make informed choices and prioritize decisions concerning maintenance procedures, required repairs, and potential infrastructure replacements. However, reliable data collection in the field remains a challenge. The information obtained by the sensors in the field frequently needs further processing, either at the decision-making headquarters or in the office. Although WSN allows data collection and analysis, there is often a gap between WSN data analysis results and the way decisions are made in industry. The industry depends on inspectors’ decisions, so it is of vital necessity to improve the inspectors’ access in the field to data collected from sensors. This paper presents the results of an experiment that shows the way Augmented Reality (AR) may improve the availability of WSN data to inspectors. AR is a tool which overlays the known attributes of an object with the corresponding position on the headset screen. In this way, it allows the integration of reality with a virtual representation provided by a computer in real time. These additional synthetic overlays supply data that may be unavailable otherwise, but it may alsomore » display additional contextual information. The experiment reported in this paper involves the application of a smart Strain Gauge Platform, which automatically measures strain for different applications, using a wireless sensor. In this experiment, an AR headset was used to improve actionable data visualization. The results of the reported experiment indicate that since the AR headset makes it possible to visualize information collected from the sensors in a graphic form in real time, it enables automatic, effective, reliable, and instant communication from a smart low-cost sensor strain gauge to a database. Moreover, it allows inspectors to observe augmented data and compare it across time and space, which then leads to appropriate prioritization of infrastructure management decisions based on accurate observations.« less

Authors:

Aguero, Marlon; Maharjan, Dilendra; Rodriguez, Maria del Pilar; Mascarenas, David Dennis Lee; Moreu, Fernando

• Search DOE PAGES for author "Moreu, Fernando"
• Search DOE PAGES for ORCID "0000-0002-7105-7843"
• Search orcid.org for ORCID "0000-0002-7105-7843"

Publication Date:

2020-01-01

Sponsoring Org.:

USDOE

OSTI Identifier:

1581024

Grant/Contract Number:  

493274

Resource Type:

Published Article

Journal Name:

Robotics

Additional Journal Information:

Journal Name: Robotics Journal Volume: 9 Journal Issue: 1; Journal ID: ISSN 2218-6581

Publisher:

MDPI AG

Country of Publication:

Country unknown/Code not available

Language:

English