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Automatic Evaluation Mechanism for Comfort Level of Construction Workers Base on Multi-sensor and Deep Learning

In: Proceedings of the 24th International Symposium on Advancement of Construction Management and Real Estate

Author

Listed:
  • Hui Deng

    (South China University of Technology)

  • Yu Wang

    (South China University of Technology)

  • Yichuan Deng

    (South China University of Technology)

  • Genjie Zhang

    (South China University of Technology)

Abstract

In construction stage of a building, thermal comfort and clutter lever are essential for the health and productivity of workers. To improve the comfort level of construction workers, this paper proposes a mobile mechanism base on multi-sensor and deep learning, which can automatically evaluate the workers’ comfort level in real time. The mechanism for comfort level can be divided into the following four aspects: firstly, BIM provides spatial information on construction sites, which can be used to plan the route for comfort inspection for safety managers. Secondly, the Raspberry Pi was used to acquire the thermal comfort in real time by wireless transmission. Thirdly, a library of waste affecting the clutter level was established, and the convolutional neural network was used to identify the on-site clutter. Finally, fuzzy reasoning algorithms were used to integrate the data on thermal comfort and clutter lever and the comfort level was automatically evaluated. The proposed mobile mechanism was verified through a case study.

Suggested Citation

  • Hui Deng & Yu Wang & Yichuan Deng & Genjie Zhang, 2021. "Automatic Evaluation Mechanism for Comfort Level of Construction Workers Base on Multi-sensor and Deep Learning," Springer Books, in: Gui Ye & Hongping Yuan & Jian Zuo (ed.), Proceedings of the 24th International Symposium on Advancement of Construction Management and Real Estate, pages 2185-2198, Springer.
    • Handle: RePEc:spr:sprchp:978-981-15-8892-1_153
    DOI: 10.1007/978-981-15-8892-1_153
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