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Automated People Counting in Public Transport

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Part of the EAI/Springer Innovations in Communication and Computing book series (EAISICC)

Abstract

This paper is elaborating on problems in public transport in the context of Smart Cities and Internet of Things (IoT). The means of public transport are commonly overcrowded and on the other hand some lines could be designed inefficiently. This affects passengers’ comfort and also the financial site of public transport companies. The field of counting people in public transport is specific with its variety and limitations regarding setup in vehicles, which we took into account while designing the embedded system. We propose a solution—an embedded system with an array of infrared sensors. Approach uses image processing means (gauss filter, sliding average, and thresholding) for object detection, followed by the detection of direction by correspondence of objects positions across images. We performed controlled experiments with one and four participants in different scenarios which were compared to other similar solutions. We have achieved satisfying results up to 95%.

Keywords

  • Counting
  • Public transport
  • Infrared sensors
  • Smart cities
  • Embedded systems

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  • DOI: 10.1007/978-3-030-92968-8_5
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Correspondence to Pištek Peter .

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Peter, P., Simon, H., Michal, V. (2023). Automated People Counting in Public Transport. In: Cagáňová, D., Horňáková, N. (eds) Industry 4.0 Challenges in Smart Cities. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-92968-8_5

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  • DOI: https://doi.org/10.1007/978-3-030-92968-8_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-92967-1

  • Online ISBN: 978-3-030-92968-8

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