Enhancing Indoor Altitude Estimation on Smartphones: Resolving Ventilation Fan Effects

The demand for indoor altitude estimation using smartphone barometers is increasing. It is known that disturbances such as changes in temperature and ventilation systems affect altitude estimations using barometric values. In this paper, we propose a correction method to compensate for the disturbance caused by ventilation systems. The amount of depressurization in a room due to a ventilation system varies depending on the ventilation capacity and the room conditions, making it difficult to determine precisely when the ventilation system is operating based on the extent of depressurization. Our approach uses machine learning to detect only the transitions in the ventilation environment in a data-driven way and performs a correction by calculating the depressurization level from the preceding data at the time of detection. We conducted experiments in real-world environments that showed the proposed method is significantly superior in performance to previous correction methods.