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Re-thinking the Prediction of Construction Hazard Identification Based on Multimodal Data

In: Proceedings of the 28th International Symposium on Advancement of Construction Management and Real Estate

Author

Listed:
  • Jiaming Wang

    (Tsinghua University)

  • Mei Liu

    (Beijing University of Civil)

  • Mingxuan Liang

    (Department of Built Environment, School of Desian and Engineering, National University of Singapore)

  • Pin-Chao Liao

    (Tsinghua University)

Abstract

Predicting hazard identification performance (HIP) is important in improving engineering project management. However, prediction based on unimodal data may overlook certain important information. Therefore, this study aims to predict HIP using multimodal data. After an experimental study, we found that (1) the prediction results of hazard identification change over time and the optimal time segments for predicting the identification performance of different hazard types are different; (2) the identification of electrical-related and fire-related hazards requires more attentional resources and longer time than fall-related hazards; (3) the physiological mechanism of hazard identification is that the occipital lobe of the brain processes visual information first, while the occipital lobe of the brain transmits visual information later. This study further explores the basic principles of hazard identification and provides a reference for improving safety management in engineering projects.

Suggested Citation

  • Jiaming Wang & Mei Liu & Mingxuan Liang & Pin-Chao Liao, 2024. "Re-thinking the Prediction of Construction Hazard Identification Based on Multimodal Data," Lecture Notes in Operations Research, in: Dezhi Li & Patrick X. W. Zou & Jingfeng Yuan & Qian Wang & Yi Peng (ed.), Proceedings of the 28th International Symposium on Advancement of Construction Management and Real Estate, chapter 0, pages 1837-1847, Springer.
    • Handle: RePEc:spr:lnopch:978-981-97-1949-5_128
    DOI: 10.1007/978-981-97-1949-5_128
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