Abstract
This paper presents the development of a smart Cardiopulmonary Resuscitation (CPR) training kit based on Internet of Things (IoT) principles. The system, designed to optimize chest compression techniques, integrates force and distance sensors, local processing through an ESP32 microcontroller, and MQTT wireless communication for remote monitoring and data analysis. Experimental validation with 20 novice participants showed improvements of 35% in compression depth and 28% in frequency within the recommended range (100–120 CPM) compared to standard commercial mannequins. Results showed an average feedback latency of 150ms and 94% accuracy in depth measurement, establishing the feasibility of this IoT solution to improve CPR training quality, especially in resource-limited environments
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Copyright (c) 2026 Patricia Nataly Flores Ponce , Eynar Calle Viles, Edgar Roberto Ramos Silvestre, Rommer Alex Ortega-Martinez (Author)