Artificial Intelligence and Environmental Protection of Buildings

Abstract

Global environmental pollution has an extremely negative impact on the population of the planet and threatens the future of mankind. One of the main sources of waste and toxic emissions into the atmosphere is the construction sector. It is necessary to find ways to minimize the damage caused to nature. Currently, artificial intelligence technologies are among the most promising ways to improve the environment. Automatic control systems solve a number of problems related to reducing costs and resources, full use of renewable energy sources, improving the safety of energy systems, and many others. The purpose of this article is to determine the functionality of artificial intelligence technologies and ways of their application in green construction. To solve this problem, methods of analysis and synthesis of existing information models were applied. The article discloses automatic control systems in the design, construction, and operation of buildings. These include well-known methods, such as Building Information Model, Machine Learning, Deep Learning, and narrow-profile ones: Response Surface Methodology, Multi-Agent System, Digital Twins, etc. In addition, the study states that when planning and arranging green buildings must adhere to the following principles: high energy efficiency, rational use of natural resources, adaptation to the environment and climate, ensuring comfort and safety for residents. The article presents the standards of green construction existing in the world. This work can serve as a guide when choosing information models and is of practical value in the development of green buildings.