Industrial Internet of Things for Assembly Line Worker’s Work Fatigue Recognition

Venkata Pabolu, Divya Shrivastava, Makarand Kulkarni

2024

Abstract

The fourth industrial revolution or Industry 4.0 is based on the Internet of Things (IoT) and other intelligent technologies. IoT is mature enough to make seamless real-time communication between data-grasping sensors and intelligent machines. Recognition and prevention of workers’ work fatigue remain challenging for manufacturing industries. The objective of this research is to develop an IoT-based worker’s work fatigue recognition system to recognize the real-time fatigue status of assembly line workers. A learning-based knowledge model is prepared from the historical worker’s work fatigue status to classify the worker’s work fatigue status (as ‘Yes’ or ‘No’) using the real-time monitoring system. Where a sensor-connected IoT framework is adopted for monitoring the real-time state of an assembly worker. Finally, an intelligent system is proposed to recognize the real-time worker’s fatigue status from the IoT real-time monitored data using the learning-based worker’s work fatigue recognition model. A use-case illustration is given to demonstrate the research scope for a manual assembly line.

Paper Citation

in Harvard Style

Pabolu V., Shrivastava D. and Kulkarni M. (2024). Industrial Internet of Things for Assembly Line Worker’s Work Fatigue Recognition. In Proceedings of the 9th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS; ISBN 978-989-758-699-6, SciTePress, pages 302-309. DOI: 10.5220/0012726200003705

in Bibtex Style

@conference{iotbds24,
author={Venkata Pabolu and Divya Shrivastava and Makarand Kulkarni},
title={Industrial Internet of Things for Assembly Line Worker’s Work Fatigue Recognition},
booktitle={Proceedings of the 9th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS},
year={2024},
pages={302-309},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012726200003705},
isbn={978-989-758-699-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS
TI - Industrial Internet of Things for Assembly Line Worker’s Work Fatigue Recognition
SN - 978-989-758-699-6
AU - Pabolu V.
AU - Shrivastava D.
AU - Kulkarni M.
PY - 2024
SP - 302
EP - 309
DO - 10.5220/0012726200003705
PB - SciTePress