Journal of Korea Society of Industrial Information Systems (한국산업정보학회논문지)

Korea Society of Industrial Information Systems (한국산업정보학회)
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Worker Detection Based on Ensemble Boosting Model Using a Low-cost Radar and IMU for Smart Safety System in Manufacturing

산업제조현장 스마트 안전 시스템용 레이다 및 IMU 센서를 이용한 앙상블 부스팅 모델 기반 작업자 탐지 기술

  • 송승언 (대구경북과학기술원 첨단레이다연구소) ;
  • 김상동 (대구경북과학기술원 첨단레이다연구소) ;
  • 김봉석 (대구경북과학기술원 첨단레이다연구소) ;
  • 류정탁 (대구대학교 전자전기공학부) ;
  • 이종훈 (대구경북과학기술원 첨단레이다연구소)
  • Received : 2024.10.01
  • Accepted : 2024.10.14
  • Published : 2024.10.30
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Abstract

This paper proposes a smart safety system that combines low-cost CW(Continuous Wave) radar and IMU sensors to enhance blind spots that pose safety risks to workers in industrial manufacturing environments. The system employs a 24 GHz radar and a 6-axis IMU sensor to detect worker movements and utilizes a machine learning model to recognize worker situations in vibrating manufacturing sites. The ensemble boosting tree-based model achieved over 92.8% worker detection accuracy, demonstrating its effectiveness in improving safety in industrial settings.

본 논문은 산업 제조 현장에서 작업자의 안전을 위협하는 사각지대를 해결하기 위해서 저가형 CW(Continuous Wave) 레이다와 IMU(Inertial Measurement Unit)센서를 결합한 스마트안전시스템을 제안하였다. 24GHz 레이다와 6축 IMU 센서를 사용하여 작업자의 움직임을 감지하고, 기계 학습 모델을 통해 작업자 상황을 인식할 수 있었다. 레이다와 IMU 특징점과 앙상블 부스팅 트리 기반 기계학습모델을 사용한 결과, 92.8% 이상의 작업자 탐지율을 확보하였다.

Keywords

Acknowledgement

이 논문은 2024년 행정안전부에서 지원하는 재난안전산업 기술사업화 지원사업(RS-2024-00416793)과 2024년 과학기술정보통신부 재원으로 DGIST 기관사업 (2024-IT-01)의 지원에 의해 연구되었음.

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