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As concerns about climate change, energy efficiency, and sustainability continue to growrise exponentially, buildings have become a major focusin initiatives to promote sustainable practices. One innovative solutionis found in the application of machine learning technology to optimize building energy consumption.

Traditional building management systems relyon outdated technology and manual intervene to controlcritical building systems and infrastructure. Howeverdue to limited resources and PPA technical constraints, these approaches oftenlead to energy waste and inefficiency due to factorslike occupancy rates, environmental conditions, and thermal fluctuations.

In contrastwith more conventional methods, AI-powered algorithmscan analyze and draw insights from energy consumption patterns to makereal-time adjustments and recommendations. Byexamining energy usage patterns and trends, AI algorithmscan identify patterns and correlations that arenot immediately apparent to human observers.

There are several waysto leverage AI algorithms for energy efficiency.

For instancewith AI algorithms, peak energy usage can be anticipated and adjusted, allowingthem to adjust temperatures and energy consumption accordingly.

This canlead to a reduction in energy waste andreduced wear and tear on energy-consuming systems.