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REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health

Introduction: The field of artificial intelligence (AI) is rapidly expanding, with many applications seen routinely in health care, industry, and education, and increasingly in workplaces. Although there is growing evidence of applications of AI in workplaces across all industries to simplify and/or...

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Autores principales: Pishgar, Maryam, Issa, Salah Fuad, Sietsema, Margaret, Pratap, Preethi, Darabi, Houshang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8296875/
https://www.ncbi.nlm.nih.gov/pubmed/34206378
http://dx.doi.org/10.3390/ijerph18136705
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author Pishgar, Maryam
Issa, Salah Fuad
Sietsema, Margaret
Pratap, Preethi
Darabi, Houshang
author_facet Pishgar, Maryam
Issa, Salah Fuad
Sietsema, Margaret
Pratap, Preethi
Darabi, Houshang
author_sort Pishgar, Maryam
collection PubMed
description Introduction: The field of artificial intelligence (AI) is rapidly expanding, with many applications seen routinely in health care, industry, and education, and increasingly in workplaces. Although there is growing evidence of applications of AI in workplaces across all industries to simplify and/or automate tasks there is a limited understanding of the role that AI contributes in addressing occupational safety and health (OSH) concerns. Methods: This paper introduces a new framework called Risk Evolution, Detection, Evaluation, and Control of Accidents (REDECA) that highlights the role that AI plays in the anticipation and control of exposure risks in a worker’s immediate environment. Two hundred and sixty AI papers across five sectors (oil and gas, mining, transportation, construction, and agriculture) were reviewed using the REDECA framework to highlight current applications and gaps in OSH and AI fields. Results: The REDECA framework highlighted the unique attributes and research focus of each of the five industrial sectors. The majority of evidence of AI in OSH research within the oil/gas and transportation sectors focused on the development of sensors to detect hazardous situations. In construction the focus was on the use of sensors to detect incidents. The research in the agriculture sector focused on sensors and actuators that removed workers from hazardous conditions. Application of the REDECA framework highlighted AI/OSH strengths and opportunities in various industries and potential areas for collaboration. Conclusions: As AI applications across industries continue to increase, further exploration of the benefits and challenges of AI applications in OSH is needed to optimally protect worker health, safety and well-being.
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spelling pubmed-82968752021-07-23 REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health Pishgar, Maryam Issa, Salah Fuad Sietsema, Margaret Pratap, Preethi Darabi, Houshang Int J Environ Res Public Health Review Introduction: The field of artificial intelligence (AI) is rapidly expanding, with many applications seen routinely in health care, industry, and education, and increasingly in workplaces. Although there is growing evidence of applications of AI in workplaces across all industries to simplify and/or automate tasks there is a limited understanding of the role that AI contributes in addressing occupational safety and health (OSH) concerns. Methods: This paper introduces a new framework called Risk Evolution, Detection, Evaluation, and Control of Accidents (REDECA) that highlights the role that AI plays in the anticipation and control of exposure risks in a worker’s immediate environment. Two hundred and sixty AI papers across five sectors (oil and gas, mining, transportation, construction, and agriculture) were reviewed using the REDECA framework to highlight current applications and gaps in OSH and AI fields. Results: The REDECA framework highlighted the unique attributes and research focus of each of the five industrial sectors. The majority of evidence of AI in OSH research within the oil/gas and transportation sectors focused on the development of sensors to detect hazardous situations. In construction the focus was on the use of sensors to detect incidents. The research in the agriculture sector focused on sensors and actuators that removed workers from hazardous conditions. Application of the REDECA framework highlighted AI/OSH strengths and opportunities in various industries and potential areas for collaboration. Conclusions: As AI applications across industries continue to increase, further exploration of the benefits and challenges of AI applications in OSH is needed to optimally protect worker health, safety and well-being. MDPI 2021-06-22 /pmc/articles/PMC8296875/ /pubmed/34206378 http://dx.doi.org/10.3390/ijerph18136705 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Pishgar, Maryam
Issa, Salah Fuad
Sietsema, Margaret
Pratap, Preethi
Darabi, Houshang
REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health
title REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health
title_full REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health
title_fullStr REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health
title_full_unstemmed REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health
title_short REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health
title_sort redeca: a novel framework to review artificial intelligence and its applications in occupational safety and health
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8296875/
https://www.ncbi.nlm.nih.gov/pubmed/34206378
http://dx.doi.org/10.3390/ijerph18136705
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