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Building Adaption Model in Assessing Adaption Potential of Old Residential Quarters Read chapter Read first chapter

2021 | OriginalPaper | Chapter

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

Authors : Hui Deng, Yu Wang, Yichuan Deng, Genjie Zhang

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

Publisher: Springer Singapore

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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.

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Metadata
Title
Automatic Evaluation Mechanism for Comfort Level of Construction Workers Base on Multi-sensor and Deep Learning
Authors
Hui Deng
Yu Wang
Yichuan Deng
Genjie Zhang
Copyright Year
2021
Publisher
Springer Singapore
Book
Proceedings of the 24th International Symposium on Advancement of Construction Management and Real Estate

Print ISBN: 978-981-15-8891-4

Electronic ISBN: 978-981-15-8892-1

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-15-8892-1_153