TY - JOUR
T1 - Development and validation of a smart HVAC control system for multi-occupant offices by using occupants’ physiological signals from wristband
AU - Deng, Zhipeng
AU - Chen, Qingyan
N1 - Funding Information:
The authors would like to thank Dr. Orkan Kurtulus of the Center for High Performance Buildings at Purdue University for his kind assistance in setting the building automation system in the HLAB building. We would also like to thank all the occupants in the offices for their participation and assistance in obtaining the data reported in this study.
Publisher Copyright:
© 2020 Elsevier B.V.
PY - 2020/5/1
Y1 - 2020/5/1
N2 - Since people spend most of their time indoors, it is important to create comfortable indoor environments for building occupants. However, unsuitable thermostat settings lead to energy waste and an undesirable indoor environment, especially in multi-occupant rooms. This study aimed to develop and validate a control strategy for the HVAC systems in multi-occupant offices using physiological parameters measured by wristbands. We used an ANN model to predict thermal sensation from indoor environmental and physiological parameters such as air temperature, relative humidity, clothing level, wrist skin temperature, skin relative humidity and heart rate. The model was trained by data collected in seven multi-occupant offices in the course of a year, and it was able to predict the thermal sensation with high accuracy. Next, we developed a control strategy for the HVAC system to improve the thermal comfort of all the occupants in the room. The control system was smart and could adjust the thermostat set point automatically in real time. We validated the system by means of both experiments and numerical simulations. In most cases, we improved the occupants’ thermal comfort level. After using the wristband control, over half of the occupants experienced a neutral sensation, and fewer than 5% still felt uncomfortable. The energy consumption by the HVAC system with the wristband control was almost the same as when the constant set point was used. After coupling with occupancy-based control by means of lighting sensors or wristband Bluetooth, the heating and cooling loads were reduced by 90% and 30%, respectively, in interior offices. Therefore, the smart HVAC control system can effectively control the indoor environment for thermal comfort and energy saving.
AB - Since people spend most of their time indoors, it is important to create comfortable indoor environments for building occupants. However, unsuitable thermostat settings lead to energy waste and an undesirable indoor environment, especially in multi-occupant rooms. This study aimed to develop and validate a control strategy for the HVAC systems in multi-occupant offices using physiological parameters measured by wristbands. We used an ANN model to predict thermal sensation from indoor environmental and physiological parameters such as air temperature, relative humidity, clothing level, wrist skin temperature, skin relative humidity and heart rate. The model was trained by data collected in seven multi-occupant offices in the course of a year, and it was able to predict the thermal sensation with high accuracy. Next, we developed a control strategy for the HVAC system to improve the thermal comfort of all the occupants in the room. The control system was smart and could adjust the thermostat set point automatically in real time. We validated the system by means of both experiments and numerical simulations. In most cases, we improved the occupants’ thermal comfort level. After using the wristband control, over half of the occupants experienced a neutral sensation, and fewer than 5% still felt uncomfortable. The energy consumption by the HVAC system with the wristband control was almost the same as when the constant set point was used. After coupling with occupancy-based control by means of lighting sensors or wristband Bluetooth, the heating and cooling loads were reduced by 90% and 30%, respectively, in interior offices. Therefore, the smart HVAC control system can effectively control the indoor environment for thermal comfort and energy saving.
KW - Air temperature
KW - Artificial neural network
KW - Heart rate
KW - Skin relative humidity
KW - Skin temperature
KW - Thermal comfort
KW - Thermostat set point
KW - Wearable device
UR - http://www.scopus.com/inward/record.url?scp=85079901922&partnerID=8YFLogxK
U2 - 10.1016/j.enbuild.2020.109872
DO - 10.1016/j.enbuild.2020.109872
M3 - Journal article
AN - SCOPUS:85079901922
SN - 0378-7788
VL - 214
JO - Energy and Buildings
JF - Energy and Buildings
M1 - 109872
ER -