Counting public transport passenger using WiFi signatures of mobile devices

Myrvoll, Tor André; Håkegård, Jan Erik; Matsui, Tomoko; Septier, François

doi:10.1109/itsc.2017.8317687

Cited by 45 publications

(30 citation statements)

References 3 publications

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“…Nevertheless, current Wi-Fi-based APCS based on MAC identification can effectively work only for obsolete operating systems (earlier than Android 5.0, iOS 7 and Windows Phone 8). In fact, with the aim to protect their users' privacy against device tracking, the main mobile operating system providers have introduced software randomization of MAC addresses [16]: the MAC address included in Probe Request frames is not the real MAC address associated to the Wi-Fi interface anymore, but it rather is randomly generated and it periodically changes.…”

Section: System Descriptionmentioning

confidence: 99%

“…However, they can effectively work only for obsolete operating systems (earlier than Android 5.0, iOS 7 and Windows Phone 8). In fact, with the aim to protect their users' privacy against device tracking, Google, Apple and Microsoft introduced software randomization of MAC addresses [16]: the claimed MAC address is randomly generated by a software, and it periodically changes.The impact of MAC address randomization on mobile device tracking is studied in [17], where the authors analyze the performance of different radomization techniques implemented for several different commercial off-the-shelf operating systems. Therefore, tracking devices is becoming not feasible anymore, as it is confirmed by [15], where TfL claims that they were unable to construct journeys when MAC addresses were randomized.…”

Section: Introductionmentioning

confidence: 99%

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iABACUS: A Wi-Fi-Based Automatic Bus Passenger Counting System

et al. 2020

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Since the early stages of the Internet-of-Things (IoT), one of the application scenarios that have been affected the most by this new paradigm is mobility. Smart Cities have greatly benefited from the awareness of some people’s habits to develop efficient mobility services. In particular, knowing how people use public transportation services and move throughout urban infrastructure is crucial in several areas, among which the most prominent are tourism and transportation. Indeed, especially for Public Transportation Companies (PTCs), long- and short-term planning of the transit network requires having a thorough knowledge of the flows of passengers in and out vehicles. Thanks to the ubiquitous presence of Internet connections, this knowledge can be easily enabled by sensors deployed on board of public transport vehicles. In this paper, a Wi-Fi-based Automatic Bus pAssenger CoUnting System, named iABACUS, is presented. The objective of iABACUS is to observe and analyze urban mobility by tracking passengers throughout their journey on public transportation vehicles, without the need for them to take any action. Test results proves that iABACUS efficiently detects the number of devices with an active Wi-Fi interface, with an accuracy of 100% in the static case and almost 94% in the dynamic case. In the latter case, there is a random error that only appears when two bus stops are very close to each other.

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Section: System Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

iABACUS: A Wi-Fi-Based Automatic Bus Passenger Counting System

et al. 2020

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“…2) Using probability density functions: In [9], a statistical approach is proposed as alternative to hard thresholds. Rather than using hard thresholds, m and ∆t are assumed to follow statistical distributions, conditional on whether the device is on the bus or not.…”

Section: Estimation Of Od Matrix Using Wi-fi and Apc Datamentioning

confidence: 99%

“…The contribution of this paper is to apply the method proposed by the authors in [9] to estimate the OD matrix based on monitoring data of Wi-Fi data traffic and APC passenger load data. Wi-Fi monitoring equipment is installed in 32 buses in Stavanger, Norway, and continuously collects Wi-Fi data traffic.…”

Section: Introductionmentioning

confidence: 99%

Statistical Modelling for Estimation of OD Matrices for Public Transport Using Wi-Fi and APC Data

Håkegård

Myrvoll

Skoglund

2018

2018 21st International Conference on Intelligent Transportation Systems (ITSC)

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In this paper, statistical models are proposed to estimate trip level origin-destination (OD) matrices for public transport based on Wi-Fi data traffic. Wi-Fi monitoring equipment installed in 32 buses in Stavanger, Norway, collected Wi-Fi data during several months. The median received signal level of frames transmitted by a device and the time interval between the first and last frame are modelled as statistical distributions, conditional on whether the Wi-Fi device is on the bus or not. Based on these models and using passenger load data from Automatic Passenger Counting (APC) systems installed in the buses, the probability for each detected device being on or off the bus is estimated. When tested on large data sets, the proposed statistical method is more accurate than when hard thresholds for median received signal level and time interval of observation are applied.

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“…• Mass transit management: Unlike traffic monitoring, mass transit management focuses on understanding the usage of mass transportation systems (buses, trains). For their project, the authors [83] placed a sensor inside a bus that counted when people came on and when they left the bus. They confirmed the results by manually counting people that entered…”

Section: Wifi Remote-positioning Use Cases 29mentioning

confidence: 99%

Crowd data analytics as seen from WiFi

Chilipirea¹

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of this thesis may be reproduced, stored in a retrieval system or transmitted in any form or by any means without permission of the author. Alle rechten voorbehouden. Niets uit deze uitgave mag worden vermenigvuldigd, in enige vorm of op enige wijze, zonder voorafgaande schriftelijke toestemming van de auteur. CROWD DATA ANALYTICS AS SEEN FROM WIFI A CRITICAL REVIEW DISSERTATION to obtain a joint degree, namely the degree of doctor at the Universiteit Twente on the authority of the rector magnificus of the

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Counting public transport passenger using WiFi signatures of mobile devices

Cited by 45 publications

References 3 publications

iABACUS: A Wi-Fi-Based Automatic Bus Passenger Counting System

iABACUS: A Wi-Fi-Based Automatic Bus Passenger Counting System

Statistical Modelling for Estimation of OD Matrices for Public Transport Using Wi-Fi and APC Data

Crowd data analytics as seen from WiFi

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