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Floor Selection Proposal for Automated Travel with Smart Elevator

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Databases and Information Systems (DB&IS 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1243))

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Abstract

Elevators have been used for centuries to convey material and people, with a history going back to 19th century. Modern elevators as we use them today became widely used some 150 years ago, and regardless of many improvements and technological advancements, the general concept has remained the same. The typical elevator still needs traveller’s input to take the passenger from one floor to another. In this paper we explore the possibility to predict elevator passenger destination floor. For this task we use passenger profiles established through deep learning, and elaborate on the passenger’s trip history to predict the floor the passenger desires to travel. The study is based on a smart elevator system set up in a typical office building. The aim is to provide personalised elevator service in the context of a smart elevator.

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Author information

Authors and Affiliations

  1. Tallinn University of Technology, 12618, Tallinn, Estonia

    Uljana Reinsalu, Tarmo Robal & Mairo Leier

Authors
  1. Uljana Reinsalu
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  2. Tarmo Robal
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  3. Mairo Leier
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Corresponding author

Correspondence to Uljana Reinsalu .

Editor information

Editors and Affiliations

  1. Department of Computer Systems, Tallinn University of Technology, Tallinn, Estonia

    Tarmo Robal

  2. Department of Software Science, Tallinn University of Technology, Tallinn, Estonia

    Hele-Mai Haav

  3. Department of Software Science, Tallinn University of Technology, Tallinn, Estonia

    Jaan Penjam

  4. Institute of Computer Science, University of Tartu, Tartu, Estonia

    Raimundas Matulevičius

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Reinsalu, U., Robal, T., Leier, M. (2020). Floor Selection Proposal for Automated Travel with Smart Elevator. In: Robal, T., Haav, HM., Penjam, J., Matulevičius, R. (eds) Databases and Information Systems. DB&IS 2020. Communications in Computer and Information Science, vol 1243. Springer, Cham. https://doi.org/10.1007/978-3-030-57672-1_4

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  • DOI: https://doi.org/10.1007/978-3-030-57672-1_4

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-57672-1

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