A review of the applications of artificial intelligence and big data to buildings for energy-efficiency and a comfortable indoor living environment - Mehmood, Muhammad Uzair; Chun, Daye; Zeeshan; Han, Hyunjoo; Jeon, Gyuyeob; Chen, Kuan (Energy and Buildings, 2019)
After decades of evolution and improvements, Artificial Intelligence (AI) is now taking root in our daily lives, and is starting to profoundly influence the fields of architecture and sustainability. The applications of AI to sustainable architecture include energy-efficient building design, forecasting and minimizing energy consumption, strategizing for mitigating impacts on environment and climate, and enhancements in the safety and comfort of the living environment. Due to the significant increases in internet speed and accessibility and the drops in computer prices and data storage costs in recent years, Big Data (BD) nowadays plays an important supplementary role to AI. Algorithms and computer codes have been developed for data mining and analysis. BD rejuvenates AI methods and applications in many areas, including sustainable architecture. The present paper starts with an introduction to AI history and techniques. This is followed by a discussion on how AI and BD can be used to design and operate energy–efficient commercial buildings and residential houses, followed by a review of recent applications of AI and BD to energy-efficient buildings with an emphasis on the use of machine learning (ML) and large databases. Future research topics are suggested at the end of this paper. It is reemphasized in the present paper that AI, when combined with BD, can tremendously increase the energy efficiency and cost effectiveness of buildings which are designed to provide occupants with a comfortable indoor living environment.
Keywords: Artificial intelligence; Big data; Green buildings; Sustainable architecture; _z:class:countries; _z:class:themes; oa:topic:T10121 Building Energy Efficiency and Thermal Comfort Optimization; oa:topic:T11954 Energy Efficiency in Manufacturing and Industry Sector; oa:topic:T11963 Impact of Nighttime Light Data on Various Fields; openalex:n:1; openalex:yes