Next-Generation CPR Training System: Real-Time Insights and AI-Driven Solutions for Employee Safety in Industry 4.0
K. Ramasamy, V Vasanthi, Karthigai · 2025
The Cardiopulmonary Resuscitation (CPR) is a crucial intervention to save life. However, traditional training approaches become inadequate if they do not provide accuracy, real-time feedback, and interactive participation to the trainees. Reducing mortality during cardiac emergencies must be approached at the level of training and correct delivery of CPR. This paper details an artificial intelligence (AI) based CPR training system that uses state-of-the-art methodologies following the Industrial $\mathbf{4. 0}$ principles to successfully improve training by real-time observation and feedback. The system proposes to install IoT-enabled sensors inside the practice manikin as an interface to measure mainly human-generated variables like chest compression depth, rate, duration and recoil. The data are then fed into ML algorithms which will provide timely feedback as well as professional quality performance evaluation. The content has also been technologically improved by a metaverse-based tutorial that reproduces realistic CPR scenarios and assists CPR to the learner’s step by step in a surrounded by environment. Based on experimental evaluations, the compression precision was improved by 70% and the demo instructors and learners stick to CPR procedures during the whole training process. The system demonstrated impeccably high accuracy in recording the primary indices (98 percent) and thus highly reinforced skills as well as user engagement. The system has applications in a wide spectrum of areas such as health care, safety at the workplace, and educational institutions. In this situation, technologically upgraded CPR instruction signifies a revolutionary method that significantly enhances emergency preparation and mitigates cardiac-related mortality globally.