A systematic review of computer vision-based personal protective equipment compliance in industry practice: advancements, challenges and future directions

Computerized compliance of Personal Protective Equipment (PPE) is an emerging topic in academic literature that aims to enhance workplace safety through the automation of compliance and prevention of PPE misuse (which currently relies on manual employee supervision and reporting). Although trends in...

Full description

Saved in:
Bibliographic Details
Published in:The Artificial intelligence review 2024-10, Vol.57 (12), p.319, Article 319
Main Authors: Vukicevic, Arso M., Petrovic, Milos, Milosevic, Pavle, Peulic, Aleksandar, Jovanovic, Kosta, Novakovic, Aleksandar
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Compliance
Computer Science
Computer vision
Cybersecurity
Datasets
Environmental management
Object recognition
Occupational safety
Personal protective equipment
Pose estimation
Real time
Systematic review
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Computerized compliance of Personal Protective Equipment (PPE) is an emerging topic in academic literature that aims to enhance workplace safety through the automation of compliance and prevention of PPE misuse (which currently relies on manual employee supervision and reporting). Although trends in the scientific literature indicate a high potential for solving the compliance problem by employing computer vision (CV) techniques, the practice has revealed a series of barriers that limit their wider applications. This article aims to contribute to the advancement of CV-based PPE compliance by providing a comparative review of high-level approaches, algorithms, datasets, and technologies used in the literature. The systematic review highlights industry-specific challenges, environmental variations, and computational costs related to the real-time management of PPE compliance. The issues of employee identification and identity management are also discussed, along with ethical and cybersecurity concerns. Through the concept of CV-based PPE Compliance 4.0, which encapsulates PPE, human, and company spatio-temporal variabilities, this study provides guidelines for future research directions for addressing the identified barriers. The further advancements and adoption of CV-based solutions for PPE compliance will require simultaneously addressing human identification, pose estimation, object recognition and tracking, necessitating the development of corresponding public datasets.
ISSN:1573-7462
0269-2821
1573-7462
DOI:10.1007/s10462-024-10978-x