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

Stephan Sigg, Sameera Palipana*, Stefano Savazzi, Sanaz Kianoush

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

3 Citations (Scopus)
188 Downloads (Pure)


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.

Original languageEnglish
Title of host publicationBusiness Process Management Workshops - BPM 2019 International Workshops, Revised Selected Papers
EditorsChiara Di Francescomarino, Remco Dijkman, Uwe Zdun
Number of pages6
ISBN (Print)9783030374525
Publication statusPublished - 1 Jan 2019
MoE publication typeA4 Conference publication
EventInternational Conference on Business Process Management - Vienna, Austria
Duration: 1 Sept 20196 Sept 2019
Conference number: 17

Publication series

NameLecture Notes in Business Information Processing
Volume362 LNBIP
ISSN (Print)1865-1348
ISSN (Electronic)1865-1356


ConferenceInternational Conference on Business Process Management
Abbreviated titleBPM


  • 5G
  • Collaborative Robotics
  • Industry 4.0
  • Radio sensing


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