Preliminary Experimental Assessment of an IoT-Based Fatigue Monitoring System for Industrial Operators

Enrico Picariello, Francesco Picariello, Ioan Tudosa

Abstract

Operators’ well-being is essential to implement the Industry 5.0 framework. To this end, this paper presents the first experimental results of a wearable IoT system for monitoring the muscle fatigue of operators on assembly lines. The system is completely modular and composed of 4 subsystems: i) a system for the acquisition of physiological signals, an IMU-based system for the acquisition of inertial data, an RFID glove for tag recognition, and an Indoor Positioning System for the evaluation of operators’ movement. For each task, operators can express a fatigue rating from 1 to 5, and a bagged decision tree classifier was used for the classification of muscle fatigue. From the results obtained, it is possible to note that the model can predict muscle fatigue with an accuracy higher than 90%.

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IMEKO-TC6-2025-031.pdf

DOI

10.21014/tc6-2025.031

IMEKO TC

TC6 - Digitalization

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