Existing energy management control relies heavily on manual control with inefficient baseline settings, which could waste up to 20% of building operation budgets. Carnot has unlocked the power of AI to optimize and automate HVAC energy patterns, involving relevant setpoints, chiller staging and sequencing, pumps, and air handling units, etc.
In conventional BMS system, equipment faults can be left unnoticed and cause a knock-on effect in the HVAC system. Consequently, a lack of fault detection/equipment health status can lead to extra energy consumption of 5 to 10%. Carnot utilize AI machine learning models to detect abnormal deviation of data from normal operation pattern, thus offers prescriptive insights e.g. maintenance notifications for facilities' managers to act upon.
proven reduction in energy costs over existing BMS controls
hidden faults uncovered
reduction in key operation faults