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

Hui Deng (), Yu Wang (), Yichuan Deng () and Genjie Zhang ()
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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

A chapter in Proceedings of the 24th International Symposium on Advancement of Construction Management and Real Estate, 2021, pp 2185-2198 from Springer

Abstract: 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.

Keywords: Multi-sensor; Computer vision; Deep learning; Fuzzy reasoning; Comfort evaluation (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-15-8892-1_153

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DOI: 10.1007/978-981-15-8892-1_153

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