A humanized adaptive baseline information technology (HABIT) algorithm for a building management system

A building management system (BMS) established to control the system of building services would not incorporate records of occupants' views nor integrate real-time occupants' response for any system fine tuning to satisfy individual demands in a dynamic manner. This study proposes a humanized adaptive baseline information technology (HABIT) algorithm to enable such fine tuning according to the occupants' feedback to optimize the acceptance of the indoor environment. Apart from solving the complaints from occupants, the proposed algorithm also integrates the collective real-time feedback from endusers with a balance of the imposed design conditions to determine the optimum operation condition of the system. In the study, the temperature set point of an air-conditioning system in certain Hong Kong offices was used as an illustrative example to demonstrate the operation of the algorithm. Survey results on occupants' views and indoor environmental conditions of the offices were used to determine the input parameters of the algorithm. With the proposed algorithm, HABIT could be used for updating the design set point of the existing BMS. Practical application: This study provides a new notion of humanized adaptive baseline information technology (HABIT) for air-conditioned spaces of a single temperature set point. The occupants' views and indoor environmental conditions of the offices are used as input parameters of the algorithm in determining the optimum temperature set point for maximizing the occupants' satisfaction. The algorithm could be built into existing building management systems (BMS) for determining the air temperature set point of a centralized air conditioning system.