Information sources providing real-time status of physical objects have drastically increased in recent times. So far, research in business process monitoring has mainly focused on checking the completion of tasks. However, the availability of real-time information allows for a more detailed tracking of individual business tasks. This paper describes a framework for controlling the safe execution of tasks and signalling possible misbehaviours at runtime. It outlines a real use case on smart logistics and the preliminary results of its application. © 2014 Springer International Publishing Switzerland.
CITATION STYLE
Cabanillas, C., Di Ciccio, C., Mendling, J., & Baumgrass, A. (2014). Predictive task monitoring for business processes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8659 LNCS, pp. 424–432). Springer Verlag. https://doi.org/10.1007/978-3-319-10172-9_31
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