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Abstract: The wind industry has grown over the years along with the collective desire to produce clean energy. High wind potential sites are often located in northern regions where harsh climatic conditions arise. The performance of anemometers, which provide essential measurements to wind turbine operation and wind resource assessment, is then jeopardized by ice build-up and snow accumulation. These conditions result in the need for heated instruments able to remain ice-free regardless of weather conditions while minimizing energy consumption. The main objective of this work was to develop an intelligent heating control for a new generation of ice-free anemometers. The controller is based on vision recognition of ice build-up on the cups of the anemometer using a neural network. Heating power is applied according to the icing state and the icing history of the instrument. Primary results have shown that, for a completely ice-free performance, the developed controller uses an average of less than two thirds of the energy consumed by common control systems similar to those used by other ice-free anemometers available on the market. [Copyright &y& Elsevier]