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An Integrated Architecture for IoT-Aware Business Process Execution

Title data

Schönig, Stefan ; Ackermann, Lars ; Jablonski, Stefan ; Ermer, Andreas:
An Integrated Architecture for IoT-Aware Business Process Execution.
In: Gulden, Jens (ed.): Enterprise, Business-Process and Information Systems Modeling. - Cham : Springer , 2018 . - pp. 19-34
ISBN 978-3-319-91703-0
DOI: https://doi.org/10.1007/978-3-319-91704-7_2

Abstract in another language

Business processes are frequently executed within application systems that involve humans, computer systems as well as objects of the Internet of Things (IoT). While several works are emerging on combining BPM and the IoT, the exploitation of IoT technology for system supported process execution is still constrained by the absence of a common system architecture that manages the communication between both worlds. In this paper, we introduce an integrated approach for IoT-aware business process execution that exploits IoT for BPM by providing IoT data in a process-aware way, providing an IoT data provenance framework, considering IoT data for interaction in a pre-defined process model, and providing wearable user interfaces with context specific IoT data provision. The approach has been implemented and evaluated extensively in production industry. The results show that the application of IoT enhanced BPM leads to less machine stops.

Further data

Item Type: Article in a book
Refereed: Yes
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science IV > Chair Applied Computer Science IV - Univ.-Prof. Dr.-Ing. Stefan Jablonski
Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science IV
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 05 Apr 2018 10:59
Last Modified: 07 Aug 2018 05:25
URI: https://eref.uni-bayreuth.de/id/eprint/43213