@inproceedings{4318,
  abstract     = {{Recent advances in the field of industrial digitization and automation lead to an increasing need for assistance systems to support workers in various fields of activity, such as assembly, logistics and maintenance. Current assistance systems for the maintenance area are usually based on a single visualization technology. However, in our view, this is not practicable in terms of real activities, as these operations involve various subtasks for which different interaction concepts would be advantageous. Therefore, in this paper, we propose a concept for a multi-device assistive system, which combines multiple devices to provide workers with relevant information over different subtasks of a maintenance operation and present our first prototype for such a system.}},
  author       = {{Heinz, Mario and Dhiman, Hitesh and Röcker, Carsten}},
  booktitle    = {{Machine Learning and Knowledge Extraction :Second IFIP TC 5, TC 8/WG 8.4, 8.9, TC 12/WG 12.9 International Cross-Domain Conference, CD-MAKE 2018}},
  editor       = {{Holzinger, Andreas and Kieseberg, Peter and Tjoa, A Min and Weippl, Edgar}},
  isbn         = {{978-3-319-99739-1}},
  keywords     = {{Human-machine-interaction, Multimodal feedback, Assistive systems, Augmented-reality, Smart factory}},
  location     = {{Hamburg}},
  pages        = {{239 -- 247}},
  publisher    = {{Springer}},
  title        = {{{A Multi-Device Assistive System for Industrial Maintenance Operations}}},
  doi          = {{10.1007/978-3-319-99740-7_16}},
  volume       = {{11015}},
  year         = {{2018}},
}

@inproceedings{4324,
  abstract     = {{On the long term, the current wave of digitization and automation in the industrial environment will result in a progressively higher complexity and heterogeneity in the industrial environment. In this context, a growing need arises for the development of digital assistance systems to support workers in various fields of activities. Current systems are generally limited to visualizations and visual feedback. Therefore, in the scope of this paper, we take a look at the major challenges and opportunities for the integration of multimodal feedback systems in today’s and future industrial environments. It shows that the integration of multimodal feedback is subject to a complex combination of technical, user-cenric and legal aspects.}},
  author       = {{Heinz, Mario and Röcker, Carsten}},
  booktitle    = {{Machine Learning and Knowledge Extraction :Second IFIP TC 5, TC 8/WG 8.4, 8.9, TC 12/WG 12.9 International Cross-Domain Conference, CD-MAKE 2018}},
  editor       = {{Holzinger, Andreas and  Kieseberg, Peter and Tjoa, A Min and Weippl, Edgar}},
  isbn         = {{978-3-319-99739-1}},
  keywords     = {{Human-machine-interaction, Multimodal feedback, Assistive systems, Augmented-reality, Smart factory}},
  location     = {{Hamburg}},
  publisher    = {{Springer}},
  title        = {{{Feedback Presentation for Workers in Industrial Environments–Challenges and Opportunities}}},
  doi          = {{10.1007/978-3-319-99740-7_17}},
  volume       = {{11015}},
  year         = {{2018}},
}