Unsupervised Machine Learning for Pattern Identification in Occupational Accidents

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Davoudi Kakhki, Fatemeh
Major Professor
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AHFE International
Freeman, Steven
University Professor
Mosher, Gretchen
Associate Professor
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Agricultural and Biosystems Engineering

Since 1905, the Department of Agricultural Engineering, now the Department of Agricultural and Biosystems Engineering (ABE), has been a leader in providing engineering solutions to agricultural problems in the United States and the world. The department’s original mission was to mechanize agriculture. That mission has evolved to encompass a global view of the entire food production system–the wise management of natural resources in the production, processing, storage, handling, and use of food fiber and other biological products.

In 1905 Agricultural Engineering was recognized as a subdivision of the Department of Agronomy, and in 1907 it was recognized as a unique department. It was renamed the Department of Agricultural and Biosystems Engineering in 1990. The department merged with the Department of Industrial Education and Technology in 2004.

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  • Department of Agricultural Engineering (1907–1990)

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Creating safe work environment is significant in saving workers’ lives, improving corporates’ social responsibility and sustainable development. Pattern identification in occupational accidents is vital in elaborating efficient safety counter-measures aiming at improving prevention and mitigating outcomes of future incidents. The objective of this study is to identify patterns related to the occurrence of occupational accidents in non-farm agricultural work environments based on workers’ compensation claims data, using latent class clustering method as an un-supervised machine learning modeling approach. The result showed injury profiles and incident dynamics have low, average, and high levels of risks based on the main causes and outcomes of the injuries and the affected body part(s).
This is a manuscript of a proceeding published as Kakhki, Fatemeh Davoudi, Steven A. Freeman, and Gretchen A. Mosher. "Unsupervised Machine Learning for Pattern Identification in Occupational Accidents." In: Tareq Ahram, Waldemar Karwowski, Pepetto Di Bucchianico, Redha Taiar, Luca Casarotto and Pietro Costa (eds) Intelligent Human Systems Integration (IHSI 2022): Integrating People and Intelligent Systems. AHFE (2022) International Conference. AHFE Open Access, vol 22. AHFE International, USA. DOI: 10.54941/ahfe1001089. Copyright 2022 The Authors. Attribution 4.0 International (CC BY 4.0). Posted with permission.