Real-Time Control of HVAC Systems Using Artificial Intelligence

The regulation and supervision of heat transfer, improving the efficiency of energy and green building operations, depend on the supervision and oversight of heating, ventilation, and air-conditioning (HVAC) systems. Conventional HVAC systems usually reduce energy efficiency, system responsiveness, and adaptability in controlling environmental conditions. A unique approach to improve the overall efficiency of the system is the incorporation of artificial intelligence into HVAC strategies, which provide data-centric, intelligent, and adaptable methodologies. This study aims to investigate how artificial intelligence techniques, such as deep learning, predictive analysis, and machine learning, can be integrated into the framework of HVAC control systems. Analyzing the inputs from the environmental sensors, climatic variables technology enables the real-time modulation of temperature, humidity, and airflow parameters. Advanced technologies such as artificial intelligence and machine learning in HVAC systems can significantly decrease energy consumption.