CONFERENCE (INTERNATIONAL) Data-driven Simulation of Wireless Communication Signal Strength in Indoor Environments

Takuhiro Shimokawa (Tokyo Institute of Technology), Kota Tsubouchi, Yoshihiro Kawahara (The University of Tokyo), Hiroaki Murakami (The University of Tokyo), Masamichi Shimosaka (Tokyo Institute of Technology)

The thirteenth edition of the International Conference on Indoor Positioning and Indoor Navigation (IPIN 2023)

December 08, 2023

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.

Paper : Data-driven Simulation of Wireless Communication Signal Strength in Indoor Environmentsopen into new tab or window (external link)