---
_id: '9358'
abstract:
- lang: eng
  text: Real-time human-centered assistance in industrial processes depends on the
    individual history of the work person’s activities in the work system and requires
    adequate methods for tracking the person’s actions. Most research in human activity
    recognition is based on recognizing actions from video data using computer vision
    methods. Digital equipment, standardized machine data interfaces, and smart wearable
    devices extend the possibilities to describe the current state of the work system.
    Petri nets have already been applied to human activity recognition, however, without
    the requirement of detecting actions in real-time. This paper proposes a Petri
    net architecture that enables hierarchical description-based human activity recognition
    in industrial work processes. We present an extension, a Partitioned Colored Petri
    Net, based on the colored Petri net formalism that infers activities from state
    transitions of the work system in real-time. In a case study, we demonstrate the
    Petri net’s application for an error-based learning system that visualizes error
    consequences in augmented reality using experimentable digital twins.
article_type: original
author:
- first_name: Jan-Phillip
  full_name: Herrmann, Jan-Phillip
  id: '75846'
  last_name: Herrmann
- first_name: Alexander
  full_name: Atanasyan, Alexander
  last_name: Atanasyan
- first_name: Felix
  full_name: Casser, Felix
  last_name: Casser
- first_name: Sven
  full_name: Tackenberg, Sven
  id: '71470'
  last_name: Tackenberg
citation:
  ama: Herrmann J-P, Atanasyan A, Casser F, Tackenberg S. A Petri Net Architecture
    for Real-Time Human Activity Recognition in Work Systems. <i>Procedia Computer
    Science</i>. 2023;217:1188-1199. doi:<a href="https://doi.org/10.1016/j.procs.2022.12.317">https://doi.org/10.1016/j.procs.2022.12.317</a>
  apa: Herrmann, J.-P., Atanasyan, A., Casser, F., &#38; Tackenberg, S. (2023). A
    Petri Net Architecture for Real-Time Human Activity Recognition in Work Systems.
    <i>Procedia Computer Science</i>, <i>217</i>, 1188–1199. <a href="https://doi.org/10.1016/j.procs.2022.12.317">https://doi.org/10.1016/j.procs.2022.12.317</a>
  bjps: <b>Herrmann J-P <i>et al.</i></b> (2023) A Petri Net Architecture for Real-Time
    Human Activity Recognition in Work Systems. <i>Procedia Computer Science</i> <b>217</b>,
    1188–1199.
  chicago: 'Herrmann, Jan-Phillip, Alexander Atanasyan, Felix Casser, and Sven Tackenberg.
    “A Petri Net Architecture for Real-Time Human Activity Recognition in Work Systems.”
    <i>Procedia Computer Science</i> 217 (2023): 1188–99. <a href="https://doi.org/10.1016/j.procs.2022.12.317">https://doi.org/10.1016/j.procs.2022.12.317</a>.'
  chicago-de: 'Herrmann, Jan-Phillip, Alexander Atanasyan, Felix Casser und Sven Tackenberg.
    2023. A Petri Net Architecture for Real-Time Human Activity Recognition in Work
    Systems. <i>Procedia Computer Science</i> 217: 1188–199. doi:<a href="https://doi.org/10.1016/j.procs.2022.12.317,">https://doi.org/10.1016/j.procs.2022.12.317,</a>
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Herrmann, Jan-Phillip</span>
    ; <span style="font-variant:small-caps;">Atanasyan, Alexander</span> ; <span style="font-variant:small-caps;">Casser,
    Felix</span> ; <span style="font-variant:small-caps;">Tackenberg, Sven</span>:
    A Petri Net Architecture for Real-Time Human Activity Recognition in Work Systems.
    In: <i>Procedia Computer Science</i> Bd. 217. Amsterdam, Elsevier (2023), S. 1188–199'
  havard: J.-P. Herrmann, A. Atanasyan, F. Casser, S. Tackenberg, A Petri Net Architecture
    for Real-Time Human Activity Recognition in Work Systems, Procedia Computer Science.
    217 (2023) 1188–199.
  ieee: J.-P. Herrmann, A. Atanasyan, F. Casser, and S. Tackenberg, “A Petri Net Architecture
    for Real-Time Human Activity Recognition in Work Systems,” <i>Procedia Computer
    Science</i>, vol. 217, pp. 1188–199, 2023.
  mla: Herrmann, Jan-Phillip, et al. “A Petri Net Architecture for Real-Time Human
    Activity Recognition in Work Systems.” <i>Procedia Computer Science</i>, vol.
    217, Elsevier, 2023, pp. 1188–99, doi:<a href="https://doi.org/10.1016/j.procs.2022.12.317">https://doi.org/10.1016/j.procs.2022.12.317</a>.
  short: J.-P. Herrmann, A. Atanasyan, F. Casser, S. Tackenberg, Procedia Computer
    Science 217 (2023) 1188–199.
  ufg: '<b>Herrmann, Jan-Phillip et. al. (2023)</b>: A Petri Net Architecture for
    Real-Time Human Activity Recognition in Work Systems, in: <i>Procedia Computer
    Science</i> <i>217</i>, S. 1188–199.'
  van: Herrmann J-P, Atanasyan A, Casser F, Tackenberg S. A Petri Net Architecture
    for Real-Time Human Activity Recognition in Work Systems. Procedia Computer Science.
    2023;217:1188–99.
conference:
  end_date: 04.11.2022
  location: Österreich
  name: 4th International Conference on Industry 4.0 and Smart Manufacturing
  start_date: 02.11.2022
date_created: 2023-01-25T13:18:36Z
date_updated: 2023-03-15T13:50:17Z
department:
- _id: DEP7020
doi: https://doi.org/10.1016/j.procs.2022.12.317
intvolume: '       217'
keyword:
- Colored Petri net
- Human-centered Assistance
- Experimentable Digital Twins
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.sciencedirect.com/science/article/pii/S1877050922024024
oa: '1'
page: 1188-199
place: Amsterdam
publication: Procedia Computer Science
publication_identifier:
  issn:
  - 1877-0509
publication_status: published
publisher: Elsevier
quality_controlled: '1'
status: public
title: A Petri Net Architecture for Real-Time Human Activity Recognition in Work Systems
type: scientific_journal_article
user_id: '15514'
volume: 217
year: 2023
...