Dynamic Building Occupancy Forecasting Using Non-Personal Real Time Data

摘要

Aspects of the disclosure relate to using machine learning techniques for dynamic occupancy prediction. A computing platform may receive first data that is non-personalized and is associated with a first specific physical space, and may receive second data associated with a second specific physical space. The computing platform may normalize, for a common subspace of the first specific physical space and the second specific physical space, the first data and the second data. Using the normalized data, the computing platform may generate a predicted occupancy value for the common subspace. The computing platform may send commands directing a local HVAC control system, deployed at the common subspace, to perform a resource control action for the common subspace, which may cause the local HVAC control system to perform the resource control action for the common subspace.