Traditional building management systems relyon outdated technology and manual intervene to controlHVAC systems, lighting, and other energy-intensive equipment.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 oftenresult in suboptimal energy usage due to factorsincluding changing building use, PPA weather patterns, and temperature variations.
In contrastwith more conventional methods, AI-powered algorithmsare capable of analyzing energy usage data to makeprecision-tuned adjustments and suggestions. Byanalyzing data points on energy consumption, occupancy rates, and environmental conditions, AI algorithmscan identify patterns and 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, allowingthe AI system to fine-tune energy usage.
This canlead to a reduction in energy waste andreduced wear and tear on energy-consuming systems.