An Augmented Reality-Based Warning System for Enhanced Safety in Industrial Settings

Tolegen Akhmetov, Huseyin Atakan Varol

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

Operator inattention can lead to accidents in industry, resulting in injury, death, and financial loss. To prevent this, we present a warning system that leverages artificial intelligence and augmented reality. In order to compare our warning system with the business-as-usual (safety mat) and no warning conditions, we conducted experiments with nine participants using quantitative measurements. Additionally, augmented reality warning types (auditory, visual, and audiovisual) were compared in an experiment with 30 participants. Several hypotheses were tested using subjective questionnaires: participants accept the warning system as beneficial overall (H1), participants prefer auditory warnings to visual warnings (H2), and the audiovisual system would be the most preferred warning system (H3). Participants' acceptance of the system was high, and they preferred audiovisual warnings to the other types of warnings. Participants ranked the visual warning as preferable to the auditory warning. The results can be utilized to design warning systems to reduce industrial accidents.

Original languageEnglish
Pages (from-to)7966-7977
Number of pages12
JournalIEEE Transactions on Industrial Informatics
Volume19
Issue number7
DOIs
Publication statusPublished - Jul 1 2023

Keywords

  • Artificial intelligence (AI)
  • augmented reality
  • eye tracking
  • industrial safety
  • warning system

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Electrical and Electronic Engineering

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