The Journal of the Korea institute of electronic communication sciences (한국전자통신학회논문지)

Korea Institute of Electronic Communication Science (한국전자통신학회)
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A Method for Determining the Peak Level of Risk in Root Industry Work Environment using Machine Learning

기계학습을 이용한 뿌리산업 작업 환경 위험도 피크레벨 결정방법

  • 이상민 (포항공과대학교 IT융합공학과) ;
  • 김준영 (포항공과대학교 IT융합공학과) ;
  • 강석찬 (포항공과대학교 IT융합공학과) ;
  • 김경준 (포항공과대학교 IT융합공학과)
  • Received : 2023.12.22
  • Accepted : 2024.02.17
  • Published : 2024.02.29
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Abstract

Because the hazardous working environments and high labor intensity of the root industry can potentially impact the health of workers, current regulations have focused on measuring and controlling environmental factors, on a semi-annual basis. However, there is a lack of quantitative criteria addressing workers' health conditions other than the physical work environment. This gap makes it challenging to prevent occupational diseases resulting from continuous exposure to harmful substances below regulatory thresholds. Therefore, this paper proposes a machine learning-based method for determining the peak level of risk in root industry work environments and enables real-time safety assessment in workplaces utilizing this approach.

뿌리산업의 유해한 작업 환경과 높은 작업 강도는 작업자의 건강에 영향을 미칠 수 있기 때문에 기존에는 유해한 물질로부터 현장 작업자를 보호하기 위해 반년 단위로 작성한 환경을 측정하여 규제하고 있다. 그러나 작업환경 외에 작업자 건강 상태 등에 대해서는 정량화된 관련 기준이 부재하여 상시로 피해를 주는 임계치 이하 유해 물질의 지속적인 노출에 따른 직업병을 예방하는데 어려움이 상존하고 있다. 따라서 본 논문에서는 기계학습을 이용한 뿌리산업 작업 환경의 위험도 피크레벨 결정방법을 제안하고 이를 토대로 작업장의 실시간 안전 평가를 가능하게 하였다.

Keywords

Acknowledgement

이 논문은 2023년도 정부(과학기술정보통신부)의 재원으로 정보통신기획평가원의 지원(No. 2022-0-00120)으로 수행되었음.

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