系统回顾基于计算机视觉的个人防护设备在工业实践中的合规性:进步、挑战和未来方向

IF 10.7 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Arso M. Vukicevic, Milos Petrovic, Pavle Milosevic, Aleksandar Peulic, Kosta Jovanovic, Aleksandar Novakovic
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引用次数: 0

摘要

个人防护设备(PPE)的计算机合规性是学术文献中的一个新兴课题,其目的是通过自动化合规性和防止个人防护设备的滥用(目前依赖于员工的人工监督和报告)来提高工作场所的安全性。尽管科学文献中的趋势表明,采用计算机视觉(CV)技术解决合规性问题的潜力很大,但实践中发现的一系列障碍限制了其更广泛的应用。本文旨在通过对文献中使用的高级方法、算法、数据集和技术进行比较综述,推动基于 CV 的个人防护设备合规性的发展。系统综述强调了与个人防护设备合规性实时管理相关的特定行业挑战、环境变化和计算成本。此外,还讨论了员工识别和身份管理问题,以及道德和网络安全问题。基于 CV 的个人防护设备合规性 4.0 概念囊括了个人防护设备、人类和公司的时空变化,通过这一概念,本研究为解决已识别障碍的未来研究方向提供了指导。要进一步推进和采用基于 CV 的个人防护设备合规性解决方案,就必须同时解决人体识别、姿势估计、物体识别和跟踪等问题,这就需要开发相应的公共数据集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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 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.

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来源期刊
Artificial Intelligence Review
Artificial Intelligence Review 工程技术-计算机:人工智能
CiteScore
22.00
自引率
3.30%
发文量
194
审稿时长
5.3 months
期刊介绍: Artificial Intelligence Review, a fully open access journal, publishes cutting-edge research in artificial intelligence and cognitive science. It features critical evaluations of applications, techniques, and algorithms, providing a platform for both researchers and application developers. The journal includes refereed survey and tutorial articles, along with reviews and commentary on significant developments in the field.
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