Design strategy of green intelligent building using deep belief network

Ting Yu (), Xiao Yang () and Peidong Sang ()
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Ting Yu: Shandong Jianzhu University
Xiao Yang: China Construction First Bureau Group Co, Ltd.
Peidong Sang: Shandong Jianzhu University

International Journal of System Assurance Engineering and Management, 2023, vol. 14, issue 1, No 19, 196-205

Abstract: Abstract The purpose is to study and discuss the design of green intelligent buildings based on biophysical design concepts under the background of the Internet of Things (IoT). Firstly, the biomimetic concept is applied to the design and exploration of children's medical building space, and the biophilia color design method is proposed for children's medical building space and green building lighting system based on the IoT. Meanwhile, the influencing factors of biophilia skin color are studied on children's psychological stress relief. The children's medical building designed with Deep Belief Network in the Deep Learning field can effectively detect human motion in various areas, and the lighting system can be automatically activated by passers-by. Then, Questionnaire Survey method is used to understand the practicability and preference of users and verify the effect of biophilia color design. Consequently, an intelligent dimming lighting system is designed by ZigBee technology. The experiment results indicate that the illuminance error is small for the proposed medical green intelligent building lighting system based on the IoT. Therefore, the implantation of biophilia color in children's s medical building space can promote children’s physical and mental health recovery and have a positive impact on people's s emotions, thereby achieving the role of environmental therapy. Moreover, the proposed medical green intelligent building lighting system based on the IoT can detect the position illuminance of children's s medical buildings and realize intelligent dimming.

Keywords: Internet of Things; Biophilia; Green intelligent building; Deep belief network; ZigBee technology (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s13198-021-01513-0

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