TY - CHAP
T1 - Exploring the Potential of Adaptive Behavior as a Tool Intended for Comfort and Saving Energy
AU - Al-Khatri, Hanan
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - Thermal adaptation processes involve all the actions taken by people to acclimatize themselves to their thermal surroundings. Based on the adaptive principle of thermal comfort, it is possible to view these processes as a tool that architects and engineers can use to satisfy indoor thermal comfort demands. Nevertheless, doubts arise in doing this because of the complexity of quantifying the adaptive behavior impact on energy savings. The need to understand when, where, and how to use each adaptive action requires artificial intelligence because its techniques can intelligently control adaptive measures to satisfy the competing demands of achieving indoor thermal comfort and saving energy. The narrative review in this chapter indicated the potential role of adaptive actions in removing the barrier of satisfying thermal comfort demands in public buildings with minimum energy consumption. The expanded application of artificial intelligence in thermal comfort research is promising in quantifying adaptive behavior’s role as an intended design tool to achieve indoor thermal comfort. Fuzzy logic and neural networks are the most useful among the different artificial intelligence techniques. Research is required to explore the role of other adaptive actions besides operating windows that captured several researchers’ interest.
AB - Thermal adaptation processes involve all the actions taken by people to acclimatize themselves to their thermal surroundings. Based on the adaptive principle of thermal comfort, it is possible to view these processes as a tool that architects and engineers can use to satisfy indoor thermal comfort demands. Nevertheless, doubts arise in doing this because of the complexity of quantifying the adaptive behavior impact on energy savings. The need to understand when, where, and how to use each adaptive action requires artificial intelligence because its techniques can intelligently control adaptive measures to satisfy the competing demands of achieving indoor thermal comfort and saving energy. The narrative review in this chapter indicated the potential role of adaptive actions in removing the barrier of satisfying thermal comfort demands in public buildings with minimum energy consumption. The expanded application of artificial intelligence in thermal comfort research is promising in quantifying adaptive behavior’s role as an intended design tool to achieve indoor thermal comfort. Fuzzy logic and neural networks are the most useful among the different artificial intelligence techniques. Research is required to explore the role of other adaptive actions besides operating windows that captured several researchers’ interest.
KW - Adaptive behavior
KW - Artificial intelligence
KW - Thermal adaptation
KW - Thermal comfort
UR - http://www.scopus.com/inward/record.url?scp=85159386130&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85159386130&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/c84a89ee-03a0-3e30-8def-cf1a69359537/
U2 - 10.1007/978-3-031-24208-3_10
DO - 10.1007/978-3-031-24208-3_10
M3 - Chapter
AN - SCOPUS:85159386130
T3 - Green Energy and Technology
SP - 133
EP - 143
BT - Green Energy and Technology
PB - Springer Science and Business Media Deutschland GmbH
ER -