This report details the design, development, and validation of an integral real-time physiological monitoring system specifically engineered to enhance occupational safety for workers engaged in high-risk industrial tasks. This initiative directly addresses a recognized critical gap in the continuous, non-invasive monitoring of vital signs within such hazardous environments. The system’s design reflects a broader industry trend towards proactive, data-driven safety management in hazardous environments, moving beyond traditional reactive measures. The core objective is to shift from merely responding to incidents to actively preventing them by providing immediate physiological insights into the operator’s condition. The proposed system integrates several key technologies. It utilizes non-invasive sensors, data processing is handled by an ESP32 microcontroller, followed by wireless transmission via Wi-Fi and the MQTT protocol to a cloud-hosted broker. The design, implementation, and laboratory testing stages are detailed, the preliminary results demonstrate the technical feasibility of the system and its ability to detect relevant biometric parameters in real time. This tool represents a valuable complement for accident prevention and the protection of operator’s health in high-risk conditions.

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Real-Time Physiological Monitoring System for High-Risk Industrial Operations

  • M. Castañeira,
  • N. Abuin,
  • D. Rubio,
  • F. Madrid,
  • M. Roberti,
  • M. Caggioli,
  • S. Ponce

摘要

This report details the design, development, and validation of an integral real-time physiological monitoring system specifically engineered to enhance occupational safety for workers engaged in high-risk industrial tasks. This initiative directly addresses a recognized critical gap in the continuous, non-invasive monitoring of vital signs within such hazardous environments. The system’s design reflects a broader industry trend towards proactive, data-driven safety management in hazardous environments, moving beyond traditional reactive measures. The core objective is to shift from merely responding to incidents to actively preventing them by providing immediate physiological insights into the operator’s condition. The proposed system integrates several key technologies. It utilizes non-invasive sensors, data processing is handled by an ESP32 microcontroller, followed by wireless transmission via Wi-Fi and the MQTT protocol to a cloud-hosted broker. The design, implementation, and laboratory testing stages are detailed, the preliminary results demonstrate the technical feasibility of the system and its ability to detect relevant biometric parameters in real time. This tool represents a valuable complement for accident prevention and the protection of operator’s health in high-risk conditions.