AI Article Synopsis

  • * The proposed system uses Bluetooth low-energy (BLE) signals from passengers' mobile devices to estimate bus congestion without compromising passenger privacy or increasing installation costs.
  • * An experiment conducted with Nara Kotsu Co., Ltd. demonstrated the system's effectiveness, achieving a mean absolute error of 2.49 passengers, which corresponds to a 38.8% error rate in estimating passenger numbers.

Article Abstract

Information on congestion of buses, which are one of the major public transportation modes, can be very useful in light of the current COVID-19 pandemic. Because it is unrealistic to manually monitor the number of riders on all buses in operation, a system that can automatically monitor congestion is necessary. The main goal of this paper's work is to automatically estimate the congestion level on a bus route with acceptable performance. For practical operation, it is necessary to design a system that does not infringe on the privacy of passengers and ensures the safety of passengers and the installation sites. In this paper, we propose a congestion estimation system that protects passengers' privacy and reduces the installation cost by using Bluetooth low-energy (BLE) signals as sensing data. The proposed system consists of (1) a sensing mechanism that acquires BLE signals emitted from passengers' mobile terminals in the bus and (2) a mechanism that estimates the degree of congestion in the bus from the data obtained by the sensing mechanism. To evaluate the effectiveness of the proposed system, we conducted a data collection experiment on an actual bus route in cooperation with Nara Kotsu Co., Ltd. The results showed that the proposed system could estimate the number of passengers with a mean absolute error of 2.49 passengers (error rate of 38.8%).

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838786PMC
http://dx.doi.org/10.3390/s22030881DOI Listing

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