Wi-Fi Signal Analysis via Smartphones for Estimating Passenger Counts

Abstract

Smartphones have become integral to daily life, offering innovative applications across various domains. This study introduces a novel method for counting passengers by analyzing Wi-Fi signals emitted by their mobile devices. The research evaluates the effectiveness of leveraging Wi-Fi data to estimate occupancy, addressing a critical issue in public transportation management. The proposed system involves three core processes: signal detection, data filtering, and passenger count estimation. Key results indicate high accuracy in moderately crowded scenarios, with average deviations of 20% from actual counts and accuracy rates between 90% and 100%. However, under high-density conditions, the system tends to overestimate, occasionally doubling the real count. While further research is required to improve precision in such settings, this study lays a foundation for leveraging digital technologies to enhance transportation operations and service delivery.

Keywords: Public transportation, digital environment, passenger estimation, signal capturing, Wi-Fi

DOI: 10.54941/ahfe1005901