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Issue No.02 - April-June (2008 vol.7)
pp: 42-50
Thomas Stiefmeier , ETH Zurich
Daniel Roggen , ETH Zurich
Georg Ogris , University of Passau
Paul Lukowicz , University of Passau
Gerhard Tröster , ETH Zurich
ABSTRACT
In an industrial scenario, a context-aware wearable computing system could support a production or maintenance worker. The system could recognize the worker's actions and deliver just-in-time information about activities the worker is to perform. This article reports on an ongoing effort to develop and test such real-life industrial activity-tracking systems within the European Union wearIT@work project. Two case studies conducted in cooperation with the European car manufacturer Skoda demonstrate how the system supports the training of assembly workers and quality assurance in the assembly line. The lessons learned from these studies are applicable in other areas. This article is part of a special issue on activity-based computing.
INDEX TERMS
artificial intelligence, wearable AI, pattern recognition, models, applications, mobile applications, computers in education
CITATION
Thomas Stiefmeier, Daniel Roggen, Georg Ogris, Paul Lukowicz, Gerhard Tröster, "Wearable Activity Tracking in Car Manufacturing", IEEE Pervasive Computing, vol.7, no. 2, pp. 42-50, April-June 2008, doi:10.1109/MPRV.2008.40
REFERENCES
1. P. Lukowicz et al., "The wearIT@work Project: Toward Real-World Industrial Wearable Computing," IEEE Pervasive Computing, vol. 6, no. 4, 2007, pp. 8–13.
2. T. Stiefmeier et al., "Event-Based Activity Tracking in Work Environments," Proc. 3rd Int'l Forum Applied Wearable Computing, Springer, 2006, pp. 91–100.
3. J.A. Ward et al., "Activity Recognition of Assembly Tasks Using Body-Worn Microphones and Accelerometers," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 28, no. 10, 2006, pp. 1553–1567.
4. D. Bannach et al., "Distributed Modular Toolbox for Multimodal Context Recognition," Proc. Architecture of Computing Systems Conf., LNCS 3894, Springer, 2006, pp. 99–113.
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