Daylight harvesting systems are becoming predictive rather than purely reactive. By integrating with weather forecast APIs and using machine learning models trained on historical data, a building management system can anticipate the amount of available sunlight for the coming hours. It can then preemptively adjust blinds and dim electric lighting in a coordinated manner to optimize for both energy savings and visual comfort, minimizing disruptive adjustments throughout the day. This proactive approach creates a smoother, more stable indoor light environment while maximizing the use of free natural light, representing an intelligent synergy between the building envelope, weather intelligence, and the electric lighting system.
