Building ventilation system needs to be controlled in a smart way to maintain indoor air quality while reducing energy use. Although many demand-controlled methods have been developed, the design of ventilation schedule has to be customized depending on local climate, occupant behavior and system capacity. This article introduces an easy-to-use control strategy based on mathematical modeling, clustering and genetic algorithm. Experimental results improve the performance of current system in an example house and provide a data-driven framework. © 2024 Elsevier Inc. All rights are reserved.