NDLI: A context-aware assistance system for maintenance applications in smart factories based on augmented reality and indoor localization

Content Provider	IEEE Xplore Digital Library
Author	Flatt, H. Koch, N. Rocker, C. Gunter, A. Jasperneite, J.
Copyright Year	2015
Description	Author affiliation: Applic. Center Ind. Autom., Fraunhofer IOSB-INA, Lemgo, Germany (Flatt, H.; Koch, N.; Rocker, C.; Gunter, A.; Jasperneite, J.)
Abstract	The term Industrie 4.0 carries the vision of smart factories, which automatically adapt to changes and assist the human as much as possible during operation and maintenance. This includes smart human machine interfaces, which reduce the chances of errors and help to make the right decisions. This paper presents an approach to equip the maintenance software running on a tablet PC with augmented reality functionality to be able to place virtual sticky notes at production modules. Additionally, these sticky notes are enriched with position information. The central element of this approach is an ontology-based context-aware framework, which aggregates and processes data from different sources. As a result, a tablet PC application was implemented, which allows displaying maintenance information as well as live plant process data in the form of augmented reality. More than 100 of those sticky notes can be placed using this system, whereas each note requires a file size of 12 to 16 kilo bytes. After placing a sticky note, the system recognizes it even if the camera's position is not exactly the same as during the placing process.
Starting Page	1
Ending Page	4
File Size	2134100
Page Count	4
File Format	PDF
e-ISBN	9781467379298
DOI	10.1109/ETFA.2015.7301586
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-08
Publisher Place	Luxembourg
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Maintenance engineering Augmented reality Context Context modeling Production facilities Cameras
Content Type	Text
Resource Type	Article

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