Abstract
AbstractCentrally controlled heating, ventilation, and air conditioning (HVAC) systems in commercial buildings are operated by building management systems (BMS) based on the predefined operational settings and a set of assumptions. Despite the high rate of energy consumption by HVAC systems in commercial buildings, observations showed that a significant portion of the occupants remain dissatisfied with thermal conditions. One of the main reasons is that HVAC systems do not take into account personalized comfort preferences in their operational rules. This study proposes a framework to integrate building occupants in the HVAC control loop, learn their comfort profiles, and control the HVAC system based on occupants’ personalized comfort profiles. The framework fuses occupants’ comfort perception indices (i.e., comfort votes provided by users and mapped to a numerical value), collected through participatory sensing, and ambient temperature data, collected through a sensor network, and computes occupants’ co...
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