Optimizing indoor temperatures - thanks to AI

The Empa spin-off viboo has developed a self-learning algorithm for controlling the indoor climate. This enables predictive cooling or heating of buildings, thus saving around one third of energy. Following successful experiments at NEST, Empa's and Eawag's research and innovation building, the first pilot projects are now being implemented with industrial partners. Conventional thermostats, which are commonplace in many residential buildings today, only react when the temperature falls below or exceeds a certain threshold. The reaction is therefore always too late and too severe, as the desired temperature is to be reached again as fast as possible. This costs energy and ultimately money. The solution: a thermostat that looks ahead and regulates the room temperature with foresight.