Home and Building Automation Systems (HBASs) are com- puter-based systems installed in indoor environments for the monitoring and control of electrical and mechanical devices, such as heating, ventila- tion and air-conditioning (HVAC). The main goal of a HBAS is to control efficiently and precisely the indoor environment, in such a way the thermal comfort of the users is maintained constantly at an ideal state and the energy consumption is minimized in order to save costs and reducing pollution. As shown in previous studies, these two objectives are conflicting, because of the existing relation between thermal comfort, energy consumption and energy costs. Thus, their contemporary satisfaction is impossible to achieve. Hence, a search for a set of solutions representing a trade-off between the two objectives is necessary. The main issue in this optimization is represented by the modeling of the user thermal comfort, which, in the current solutions, is predicted through sensors measurements and computations that are difficult to perform, which do not really consider how the user is actually feeling. To overcome these limitations, the proposed solution presents an approach which does not rely on any external measurements, but only on the subjective feeling of the users, collected by asking them directly how they feel instead of predicting their thermal comfort. An environmental specification, which represents the control variables to use over the actuation system, is inferred through Fuzzy Inference from the user-provided thermal comfort, and is then optimized through Genetic Algorithms with the main goal to both maximize the thermal comfort of all the building occupants, and to minimize the corresponding energy consumption. A software architecture for the implementation of the model and a work plan for its development are presented, as well as a testing and an assessment plan for the evaluation of the results.

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