Working with a building’s energy profile, our solution combines these energy equations with deep learning and time-series data to calculate how each zone will react to changing conditions (e.g. weather) over time. More specifically, our deep learning neural networks can look into the future and predict the state of a zone in a building in 5 minutes, 10 minutes, 3 hours and 6 hours with 99.6% accuracy. In fact, even at 1000 hours, our AI engine is still making predictions with astonishing precision.

From these predictions, our AI engine determines the best way to manage the energy flow for every zone in your building by ensuring the greatest energy savings and occupant comfort.

Using over 25 customized algorithms working in real-time, the BrainBox AI engine then writes back directly to the controller of your existing HVAC system, instructing it on how to operate more intelligently and efficiently.

The AI decision-making process is based on the hundreds of thousands of data points that are continuously collected from existing building systems (e.g. BMS and access control systems) and third-party sources (e.g. weather and occupancy) as well as the desired comfort levels selected by the building owner or tenants.