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IFIP Conference on Human-Computer Interaction

INTERACT 2021: Human-Computer Interaction – INTERACT 2021 pp 426–448Cite as

Strategically Using Applied Machine Learning for Accessibility Documentation in the Built Environment

Part of the Lecture Notes in Computer Science book series (LNISA,volume 12933)

Abstract

There has been a considerable amount of research aimed at automating the documentation of accessibility in the built environment. Yet so far, there has been no fully automatic system that has been shown to reliably document surface quality barriers in the built environment in real-time. This is a mixed problem of HCI and applied machine learning, requiring the careful use of applied machine learning to address the real-world concern of practical documentation. To address this challenge, we offer a framework for designing applied machine learning approaches aimed at documenting the (in)accessibility of the built environment. This framework is designed to take into account the real-world picture, recognizing that the design of any accessibility documentation system has to take into account a range of factors that are not usually considered in machine learning research. We then apply this framework in a case study, illustrating an approach which can obtain a f-ratio of 0.952 in the best-case scenario.

Keywords

  • Accessibility
  • Built-Environment
  • Documentation

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Authors and Affiliations

  1. University of Bremen, Bibliothekstr. 1, 28359, Bremen, Germany

    Marvin Lange

  2. Monash University, Wellington Road, Clayton, VIC, 3800, Australia

    Reuben Kirkham

  3. City University of Applied Sciences Bremen, Flughafenallee 10, 28199, Bremen, Germany

    Benjamin Tannert

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  1. Marvin Lange
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  2. Reuben Kirkham
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Correspondence to Benjamin Tannert .

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Editors and Affiliations

  1. Department of Electrical and Information Engineering, Polytechnic University of Bari, Bari, Italy

    Carmelo Ardito

  2. Computer Science Department, University of Bari Aldo Moro, Bari, Italy

    Rosa Lanzilotti

  3. Computer Science Department, University of Pisa, Pisa, Italy

    Alessio Malizia

  4. Department of Computer Science, University of York, York, UK

    Helen Petrie

  5. Computer Science Department, University of Bari Aldo Moro, Bari, Italy

    Antonio Piccinno

  6. Computer Science Department, University of Bari Aldo Moro, Bari, Italy

    Dr. Giuseppe Desolda

  7. Microsoft Research, Redmond, WA, USA

    Kori Inkpen

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Lange, M., Kirkham, R., Tannert, B. (2021). Strategically Using Applied Machine Learning for Accessibility Documentation in the Built Environment. In: Ardito, C., et al. Human-Computer Interaction – INTERACT 2021. INTERACT 2021. Lecture Notes in Computer Science(), vol 12933. Springer, Cham. https://doi.org/10.1007/978-3-030-85616-8_25

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