This study provides a comprehensive bibliometric and thematic analysis of Artificial Intelligence (AI) applications in Personal Protective Equipment (PPE) from 2020 to 2025. Driven by the acceleration caused by the COVID-19 pandemic and the convergence of AI, IoT, and edge computing, the integration of intelligent systems into PPE has evolved from experimental prototypes to mature, real-time safety platforms. Drawing on 91 peer-reviewed publications systematically retrieved from Web of Science, Scopus, and IEEE Xplore using PRISMA guidelines, this study employs bibliometric analysis and manual thematic coding to identify four primary application clusters: (1) PPE detection and compliance, (2) smart PPE design and manufacturing, (3) AI-based training and safety management, and (4) predictive maintenance. A multi-dimensional technology maturity matrix and trend analysis reveal that detection and compliance systems-particularly edge AI platforms-are reaching industrial deployment, while predictive analytics and smart textiles remain emergent. The study also examines the implications of the EU Artificial Intelligence Act (Reg. 2024/1689), which classifies many AI-PPE systems as 'high-risk,' imposing mandatory requirements for transparency, data governance, and human oversight. This work contributes a structured framework for future research and implementation, highlighting technological opportunities, regulatory constraints, and ethical challenges. It concludes by outlining future trajectories including digital twins, generative AI, and federated learning for privacy-preserving, personalized, and adaptive PPE solutions.
Artificial Intelligence Applications in Personal Protective Equipment: Bibliometric Insights and Evolution Patterns (2020-2025)
Schena E.;Massaroni C.;
2025-01-01
Abstract
This study provides a comprehensive bibliometric and thematic analysis of Artificial Intelligence (AI) applications in Personal Protective Equipment (PPE) from 2020 to 2025. Driven by the acceleration caused by the COVID-19 pandemic and the convergence of AI, IoT, and edge computing, the integration of intelligent systems into PPE has evolved from experimental prototypes to mature, real-time safety platforms. Drawing on 91 peer-reviewed publications systematically retrieved from Web of Science, Scopus, and IEEE Xplore using PRISMA guidelines, this study employs bibliometric analysis and manual thematic coding to identify four primary application clusters: (1) PPE detection and compliance, (2) smart PPE design and manufacturing, (3) AI-based training and safety management, and (4) predictive maintenance. A multi-dimensional technology maturity matrix and trend analysis reveal that detection and compliance systems-particularly edge AI platforms-are reaching industrial deployment, while predictive analytics and smart textiles remain emergent. The study also examines the implications of the EU Artificial Intelligence Act (Reg. 2024/1689), which classifies many AI-PPE systems as 'high-risk,' imposing mandatory requirements for transparency, data governance, and human oversight. This work contributes a structured framework for future research and implementation, highlighting technological opportunities, regulatory constraints, and ethical challenges. It concludes by outlining future trajectories including digital twins, generative AI, and federated learning for privacy-preserving, personalized, and adaptive PPE solutions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
