۱٫ AI evolution, classification, and techniques

۲٫ Big data and artificial intelligence

۳٫ Applications of AI and BD to energy-efficient buildings

۴٫ Recent applications of AI and BD to energy efficient buildings

۵٫ Summary

Declaration of Competing Interest

Acknowledgements

References

Abstract

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.

AI evolution, classification, and techniques

Minsky and McCarthy described AI as “the ability of a machine or a program to perform a task, which would require some kind of intelligence if it was carried out by a human being” [۱]. Wang thought that AI could be defined on the basis of structure, behavior, capabilities, function and principles [2]. Nilsson defined AI as the “activity devoted to making machines intelligent, and intelligence is the quality that enables an entity to function appropriately and with foresight in its environment” [۳]. Lacking a precise and universally accepted definition might in fact help the advancement of the field of AI. Some of the capabilities of AI systems that can be associated with human intelligence are problem solving, knowledge representation, reasoning, learning, and to some lesser extent, social intelligence, and creativity.

The concept of AI is based on the assumption that the human thought process can be mechanized. Even before the industrial era, speculations of AI could be seen in different civilizations. However, its first practical application was seen during World War II. Alan Turing, a noted British mathematician and computer scientist, and his teammates created the Bombe machine to decipher the Enigma code, leading to the foundation of ML (Machine Learning).