Building heating management based on the belief functions theory

This paper presents a data fusion system, which models and handles uncertainties in buildings, in order to design a smart heating system. The data fusion model provides a temperature trend that will be inserted in smart and predictive heating systems in order to reduce energy consumption in the building. The multilevel data fusion model is based on the belief functions theory. Different simulations were carried out and give very satisfactory results, in spite of the complexity of the data.

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