Boosting Safety Protocol Compliance with Eye-Tracking in Chemical Plants

In high-risk industrial environments such as chemical plants, where operators are frequently exposed to time-sensitive hazards, ensuring strict safety protocol compliance is essential. Traditional safety training approaches often fail to effectively engage workers in cognitively demanding tasks, hig...

Full description

Saved in:
Bibliographic Details
Main Authors: Yangyi Xia, Yulin Zhao, Wu Song
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/15/10/5368
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In high-risk industrial environments such as chemical plants, where operators are frequently exposed to time-sensitive hazards, ensuring strict safety protocol compliance is essential. Traditional safety training approaches often fail to effectively engage workers in cognitively demanding tasks, highlighting the need for immersive and feedback-driven alternatives. This study investigates the integration of extended reality (XR) and real-time eye-tracking feedback into safety training programs. Participants were divided into two groups: XR-only training and XR with real-time gaze feedback. The compliance assessment is based on five key metrics: reaction time, operational accuracy, attention focus, error count, and corrective response time. Results showed that eye-tracking-enhanced training reduced reaction time by 25%, improved accuracy by 15%, increased attention focus by 20%, and decreased errors by 30%. Additionally, real-time gaze feedback improved corrective response time by 40%, particularly benefiting inexperienced operators. These findings demonstrate that integrating gaze-tracking into XR-based training enhances cognitive engagement, reduces human error, and improves compliance with safety protocols. This study provides empirical evidence supporting the adoption of XR with eye-tracking for industrial safety training, with potential applications in other high-risk fields.
ISSN:2076-3417