Traditional building management systems relyon outdated technology and manual intervene to controlHVAC systems, lighting, and other energy-intensive equipment. Howeverdue to limited resources and technical constraints, these approaches oftenlead to energy waste and inefficiency due to factorssuch as changing occupancy, external weather conditions, and varying thermal loads.
In contrastto these traditional approaches, AI-powered algorithmsare capable of analyzing energy usage data to makecustomized adjustments based on data analysis. Bystudying building energy data, AI algorithmscan identify patterns and PPA correlations that arenot immediately apparent to human observers.
There are several waysto leverage AI algorithms for energy efficiency.
For instance, AI algorithms can predict when a building is likely to experience peak demand for heating or cooling, allowingthem to adjust temperatures and energy consumption accordingly.
This canhelp to minimize energy consumption andreduced energy costs.