Improving the Understanding of Low Frequency Magnetic Field Exposure with Augmented Reality

Florian Soyka () and Julian Simons
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Florian Soyka: Department “Accident Prevention: Digitalisation—Technologies”, Institute for Occupational Safety and Health of the German Social Accident Insurance, D-53757 Sankt Augustin, Germany
Julian Simons: Department “Accident Prevention: Digitalisation—Technologies”, Institute for Occupational Safety and Health of the German Social Accident Insurance, D-53757 Sankt Augustin, Germany

IJERPH, 2022, vol. 19, issue 17, 1-11

Abstract: Low frequency magnetic fields are often present in our everyday life due to the multitude of electronic devices. High magnetic fields can occur in the workplace from a wide variety of machines and systems, which must be measured and evaluated from the point of view of occupational safety. To facilitate the understanding of magnetic fields by supervisors and employees in the workplace, an augmented reality (AR) application was developed to visualize the measured flux densities and the resulting safety distances. The application was deployed on two smartphones, allowing for the simultaneous viewing of the same scene without the use of additional markers. Whether the application creates a better understanding of the exposure situation was evaluated with the help of an online survey. In this survey, participants received either a classic measurement report or a report enhanced by augmented images. The evaluation shows that it subjectively felt less difficult for participants with the augmented report to answer questions about the exposure situation. Furthermore, they also objectively performed better in answering the questions than did the group with the classic report. Therefore, this work shows that AR enhanced images can improve the understanding of an exposure situation, and it describes how such images and videos can be created.

Keywords: augmented reality; occupational safety and health; magnetic fields; visualization; exposure (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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