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Capturing Human-Machine Interaction Events from Radio Sensors in Industry 4.0 Environments

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Business Process Management Workshops (BPM 2019)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 362))

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Abstract

In manufacturing environments, human workers interact with increasingly autonomous machinery. To ensure workspace safety and production efficiency during human-robot cooperation, continuous and accurate tracking and perception of workers’ activities is required. The RadioSense project intends to move forward the state-of-the-art in advanced sensing and perception for next generation manufacturing workspace. In this paper, we describe our ongoing efforts towards multi-subject recognition cases with multiple persons conducting several simultaneous activities. Perturbations induced by moving bodies/objects on the electromagnetic wavefield can be processed for environmental perception by leveraging next generation (5G) New Radio (NR) technologies, including MIMO systems, high performance edge-cloud computing and novel (or custom designed) deep learning tools.

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Notes

  1. 1.

    http://ambientintelligence.aalto.fi/radiosense/.

  2. 2.

    We remark that localization might still be possible from phase information.

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Author information

Authors and Affiliations

  1. Aalto University, Espoo, Finland

    Stephan Sigg, Sameera Palipana, Stefano Savazzi & Sanaz Kianoush

  2. Consiglio Nazionale delle Ricerche (CNR), IEIIT institute, Piazza Leonardo da Vinci 32, 20133, Milano, Italy

    Stefano Savazzi & Sanaz Kianoush

Authors
  1. Stephan Sigg
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  2. Sameera Palipana
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  3. Stefano Savazzi
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  4. Sanaz Kianoush
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Corresponding author

Correspondence to Sameera Palipana .

Editor information

Editors and Affiliations

  1. Fondazione Bruno Kessler, Trento, Italy

    Chiara Di Francescomarino

  2. Eindhoven University of Technology, Eindhoven, The Netherlands

    Remco Dijkman

  3. University of Vienna, Vienna, Austria

    Uwe Zdun

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Sigg, S., Palipana, S., Savazzi, S., Kianoush, S. (2019). Capturing Human-Machine Interaction Events from Radio Sensors in Industry 4.0 Environments. In: Di Francescomarino, C., Dijkman, R., Zdun, U. (eds) Business Process Management Workshops. BPM 2019. Lecture Notes in Business Information Processing, vol 362. Springer, Cham. https://doi.org/10.1007/978-3-030-37453-2_35

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  • DOI: https://doi.org/10.1007/978-3-030-37453-2_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37452-5

  • Online ISBN: 978-3-030-37453-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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