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In this study, we propose a new control algorithm based on occupancy status for indoor environmental devices to maintain thermal comfort while saving energy of residential buildings. The algorithm consists of two parts: an environmental data driven model for the occupancy status detection and an integrated comfort algorithm for operating the indoor devices. To detect the occupancy status, a multinomial logistic regression model is developed based on the data obtained from passive infrared (PIR) sensors, a door sensor, CO₂ concentrations, and lighting electricity consumption. The occupancy status is categorized into three classes: away, active, and inactive (sleep).

The new control algorithm integrates and operates air-conditioning, ventilation, and humidification systems by considering the outdoor environment, and ensuring indoor thermal comfort and energy savings at each occupancy status. The control …