Wearable Sensor Node for Safety Improvement in Workplaces: Technology Assessment in a Simulated Environment.

Area of Science:

• Occupational Health and Safety
• Wearable Technology
• Internet of Things (IoT)

Background:

• Personal protective equipment (PPE) is crucial for worker safety.
• Traditional PPE lacks real-time monitoring capabilities.
• Integrating IoT into PPE offers advanced safety solutions.

Purpose of the Study:

• To develop and evaluate a smart PPE system with a sensor node.
• To monitor workers and their environment for potential hazards.
• To utilize AI for recognizing risky worker activities.

Main Methods:

• Designed a sensor node with sensors for gases (VOC, CO2, CO, O2), particulate matter (PM), temperature, humidity, location, audio, and gestures.
• Implemented artificial intelligence algorithms for pattern recognition of risky situations.
• Conducted gas tests, indoor/outdoor positioning tests, and simulated lab environment tests.

Main Results:

• The smart PPE sensor node demonstrated high performance in all tested scenarios.
• The system accurately identified and signaled all simulated risky situations.
• Positional capabilities were validated in both indoor and outdoor settings.

Conclusions:

• The developed smart PPE system effectively monitors workers and their surroundings.
• The system's AI capabilities can proactively identify and alert to hazardous conditions.
• This technology has the potential to significantly improve workplace safety and emergency response.