The application of artificial intelligence in optimizing the energy performance of sustainable buildings (focus on technology)

mohammad mehdi irandoust¹ sajedeh hajinezhad bamroud²

1) PhD student in Architecture, Islamic Azad University, Birjand branch
2) Master of Architecture, Islamic Azad University of Research Sciences, Tehran (Zahedan)

IOI Code : AZEK-AZFDCF
Publication : 4th International Conference on New Research & Achievements in Science, Engineering & Technologies(setbconf.com)
Abstract :
    Considering the ever-increasing energy consumption in buildings and the necessity of moving towards sustainability, optimizing the energy performance of buildings has become one of the main challenges in the field of architecture and engineering. Artificial intelligence (AI) with machine learning capabilities, big data processing and optimization algorithms offers great potential to improve the energy performance of sustainable buildings. This article examines the applications of artificial intelligence in optimizing the energy performance of sustainable buildings, focusing on related technologies. At first, an overview of the key concepts of artificial intelligence in the building field is presented, and then its various applications in energy consumption prediction, HVAC system control, building shell design optimization and renewable energy management are examined. Also, the challenges and limitations of using artificial intelligence in this field and the solutions to deal with them will be discussed. Finally, by presenting case studies and practical examples, the impact of artificial intelligence in reducing energy consumption and improving the performance of sustainable buildings is evaluated. The results of this research show that the use of artificial intelligence can play an effective role in the design, construction and management of buildings with high energy efficiency and the least negative impact on the environment.

Keywords : artificial intelligence energy optimization sustainable buildings machine learning hvac systems renewable energy