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

Author

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  • Michele Nitti

    (Department of Electrical and Electronic Engineering (DIEE), University of Cagliari, 09123 Cagliari, Italy
    National Telecommunication Inter University Consortium (CNIT), Research Unit of Cagliari, 09123 Cagliari, Italy)

  • Francesca Pinna

    (Department of Electrical and Electronic Engineering (DIEE), University of Cagliari, 09123 Cagliari, Italy)

  • Lucia Pintor

    (Department of Electrical and Electronic Engineering (DIEE), University of Cagliari, 09123 Cagliari, Italy)

  • Virginia Pilloni

    (Department of Electrical and Electronic Engineering (DIEE), University of Cagliari, 09123 Cagliari, Italy
    National Telecommunication Inter University Consortium (CNIT), Research Unit of Cagliari, 09123 Cagliari, Italy)

  • Benedetto Barabino

    (Department of Civil Engineering, Architecture, Land, Environment and Mathematics (DICATAM), University of Brescia, 25123 Brescia, Italy)

Abstract

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.

Suggested Citation

  • Michele Nitti & Francesca Pinna & Lucia Pintor & Virginia Pilloni & Benedetto Barabino, 2020. "iABACUS: A Wi-Fi-Based Automatic Bus Passenger Counting System," Energies, MDPI, vol. 13(6), pages 1-21, March.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:6:p:1446-:d:334628
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    References listed on IDEAS

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    2. Marta C. González & César A. Hidalgo & Albert-László Barabási, 2009. "Understanding individual human mobility patterns," Nature, Nature, vol. 458(7235), pages 238-238, March.
    3. Editorial Article, 0. "The Information for Authors," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 3.
    4. Editorial Article, 0. "The Information for Authors," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 2.
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    Cited by:

    1. Fabio Borghetti & Cristian Giovanni Colombo & Michela Longo & Renato Mazzoncini & Leonardo Cesarini & Luigi Contestabile & Claudio Somaschini, 2021. "15-Min Station: A Case Study in North Italy City to Evaluate the Livability of an Area," Sustainability, MDPI, vol. 13(18), pages 1-18, September.
    2. Fabre, Léa & Bayart, Caroline & Bonnel, Patrick & Mony, Nicolas, 2023. "The potential of Wi-Fi data to estimate bus passenger mobility," Technological Forecasting and Social Change, Elsevier, vol. 192(C).
    3. Plückebaum, Thomas & Sörries, Bernd & Wissner, Matthias & Elbanna, Ahmed & Strube Martins, Sonia & Godlovitch, Ilsa, 2021. "Green WiFi," Study Series, WIK Wissenschaftliches Institut für Infrastruktur und Kommunikationsdienste GmbH, number 251548, December.

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