국제학술발표논문집 (International conference on construction engineering and project management)

한국건설관리학회 (Korea Institute of Construction Engineering and Management)
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Comprehensive System Framework for Visual Fatigue and Cognitive Performance Management based on Predictive Models

  • Dahyun JUNG (Department of Architecture and Architectural Engineering, Yonsei University) ;
  • Hakpyeong KIM (Department of Architecture and Architectural Engineering, Yonsei University) ;
  • Seunghoon JUNG (Department of Architecture and Architectural Engineering, Yonsei University) ;
  • Hyuna KANG (Department of Architecture and Architectural Engineering, Yonsei University) ;
  • Seungkeun YEOM (Department of Architecture and Architectural Engineering, Yonsei University) ;
  • Juui KIM (Department of Civil and Environmental Engineering, Yonsei University) ;
  • Taehoon HONG (Department of Architecture and Architectural Engineering, Yonsei University)
  • 발행 : 2024.07.29
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초록

With the modern workplace's increasing dependence on computer-based tasks, traditional lighting standards have been identified as insufficient for optimal occupant comfort and productivity. Therefore, this paper presents a comprehensive system framework designed to manage visual fatigue and cognitive performance within office environments. Classification and regression models using gradient boosting machine and random forest to predict visual fatigue and cognitive performance were developed based on data collected from 16 subjects in experiments. To this end, the proposed system consists of two modules: the first module predicts visual fatigue and cognitive performance levels using classification models, offering immediate feedback to occupants. The second module, targeted at facility managers, uses regression models and a genetic algorithm to identify optimal lighting settings, aiming to minimize visual fatigue and enhance cognitive performance. This system can help to manage visual fatigue and cognitive performance simultaneously, contributing to improvement of eye health and productivity.

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과제정보

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT; Ministry of Science and ICT) (NRF-2021R1A3B1076769).

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