Enhancing worker well-being by utilising Data Analytics and Machine Learning approaches for fatigue detection

Joseph Ambrose, Anish Romario (2023) Enhancing worker well-being by utilising Data Analytics and Machine Learning approaches for fatigue detection. Masters thesis, Dublin, National College of Ireland.

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Abstract

This research addresses the imperative of employee well-being through the exploration and development of machine learning and data analytics for early detection of fatigue in diverse workplace environments. Utilizing models such as Decision Tree, Feed-forward Neural Network, Deep Learning, K-Nearest Neighbours (KNN), XG Boost, and Random Forest, we aim to identify early signs of fatigue and stress across various industries.

Our primary objectives include the creation of predictive models capable of analysing multiple data sources to discern patterns associated with fatigue. Noteworthy achievements include the Feed-forward Neural Network and Deep Learning algorithms portraying superior predictive capabilities with low Mean Squared Error values and High R-squared values. Moreover, this study assesses the broader impact of data-driven fatigue detection systems on workplace safety, employee well-being, job performance, and job satisfaction.

The findings emphasize the efficiency of the Random Forest model in promoting workplace safety. By addressing these objectives, this research contributes valuable insights to the development of proactive strategies for detecting and mitigating employee fatigue, ultimately fostering healthier and more productive work environments.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Qayum, Abdul UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning R Medicine > RA Public aspects of medicine > RA790 Mental Health H Social Sciences > HD Industries. Land use. Labor > Issues of Labour and Work > Quality of Work Life / Job Satisfaction H Social Sciences > HF Commerce > Industrial Psychology > Workplace Stress
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	09 May 2025 09:51
Last Modified:	09 May 2025 09:51
URI:	https://norma.ncirl.ie/id/eprint/7535

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