Intelligent Thermal Comfort Controlling System for Buildings Based on IoT and AI

Yafei Zhao, Paolo Vincenzo Genovese and Zhixing Li
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Yafei Zhao: School of Architecture, Tianjin University, Tianjin300072, China
Paolo Vincenzo Genovese: School of Architecture, Tianjin University, Tianjin300072, China
Zhixing Li: School of Architecture, Tianjin University, Tianjin300072, China

Future Internet, 2020, vol. 12, issue 2, 1-18

Abstract: With the improvement of technologies, people’s demand for intelligent devices of indoor and outdoor living environments keeps increasing. However, the traditional control system only adjusts living parameters mechanically, which cannot better meet the requirements of human comfort intelligently. This article proposes a building intelligent thermal comfort control system based on the Internet of Things and intelligent artificial intelligence. Through the literature review, various algorithms and prediction methods are analyzed and compared. The system can automatically complete a series of operations through IoT hardware devices which are located at multiple locations in the building with key modules. The code is developed and debugged by Python to establish a model for energy consumption prediction with environmental factors such as temperature, humidity, radiant temperature, and air velocity on thermal comfort indicators. By using the simulation experiments, 1700 data sets are used for training. Then, the output PMV predicted values are compared with the real figure. The results show that the performance of this system is superior to traditional control on energy-saving and comfort.

Keywords: Internet of Things; thermal comfort; control system; energy consumption; artificial intelligence (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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