Kipsum

Kipsum optimizes energy consumption associated with the heating/cooling needs of buildings and processes via AI and digital twin. The Kipsum solution requires collecting data related to the building and its use case to build a thermal, hydraulic, and energy model of the building. Then, Kipsum will install sensors in different areas of the building, where the main collected data will be temperature, internal humidity, occupancy rate, etc. This data will feed our learning algorithms to determine the building's characteristics (thermal inertia, infiltration rates...). It takes 2 to 4 weeks of learning to identify the building's thermal behavior. Then, this model will be integrated into a digital twin that predicts the building's heating/cooling needs. Kipsum will run this twin parallel to the control system to send an optimal command every 15 minutes, incorporating upcoming weather and occupancy load.