Estimating Bluetooth mac scanner based pedestrian flow characteristic by taking the through pedestrian flow as a case study

Qing Lan,Bowen Gao,Sicong Zhu,Zhigui Chen,M Figueira,J Rześny,G Lodewijks,R Montemanni

doi:10.1051/matecconf/201712401007

Qing Lan, Bowen Gao + Show 6 more

Open Access

https://doi.org/10.1051/matecconf/201712401007

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Abstract

The Bluetooth scanner has been widely used as vehicle traffic detector in recent years. A new solution based on the Bluetooth scanner has been deliver to detect pedestrian traffic by estimating the pedestrian flow characteristic. The equipment is tuned to scan Bluetooth devices more frequently. Consequentially, the unique Bluetooth MAC can be detected multiple times by the scanner. The numeric simulation also suggests median detection is the chosen one to calculate traveling time. In this study, Bluetooth MAC scanning, as a non-intrusive technology, is tested in a pedestrian transfer tunnel, including antenna compatibility working within buildings. The penetration rate also increases slightly. Finally, the proposed solution offers a mature technology for pedestrian study, integrating scanner configuration, antenna selection and the traveling time calculation method.

Highlights

Rapid deployment of smartphones as all-purpose mobile communication systems has led to the fast adoption of wireless communication systems such as Wi-Fi and Bluetooth
The media access control (MAC) of Bluetooth devices can be viewed as a unique identification
By making these assumptions, when the Bluetooth device is within the range of the scanner, 18 frequencies of the total 32 frequencies that belong to the Bluetooth spread spectrum will be scanned during a single inquiry period, of which the probability is equal to 56.25% [10]

Summary

Introduction

The Bluetooth scanner utilized as a traffic detection technology has emerged in the past decade [1]. Networks of Bluetooth MAC scanners, which detect and match the MAC addresses of Bluetooth devices within wireless networks, have been widely utilized to collect vehicle traffic data [2] [3]. The organization of pedestrian flows in large public buildings presents a major challenge. In traffic terminals, such as railway stations and subway stations, systems with information about current crowd flows are able to support the control and management of pedestrian flows and can reduce traveling time and management cost [4]. The traveling time can be calculated by using logarithmic differentiation of detection time collected by two proximate Bluetooth scanners

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