IoT meets BPM: a bidirectional communication architecture for IoT-aware process execution
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SPECIAL SECTION PAPER
IoT meets BPM: a bidirectional communication architecture for IoT-aware process execution Stefan Schönig1 · Lars Ackermann2 · Stefan Jablonski2 · Andreas Ermer3 Received: 29 October 2018 / Revised: 31 October 2019 / Accepted: 21 February 2020 © The Author(s) 2020
Abstract Business processes are frequently executed within application systems that involve humans, computer systems as well as objects of the Internet of Things (IoT). Nevertheless, the usage 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-compatible 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 on top of contemporary BPM modeling concepts and system technology. The introduced technique has evaluated extensively in different use cases in industry. Keywords Process Execution · Internet of Things · Wearables
1 Introduction Business process management (BPM) is considered as powerful technology to operate, control, design, document, and improve cooperative processes [1]. Processes are executed within application systems that are part of the real world involving humans, cooperative computer systems as well as physical objects [2]. Internet of Things (IoT) as well as cyber-physical systems (CPS), denoting the internetworking of all kinds of physical devices, have become very popular these days [3–6]. Data sets grow rapidly, in part because they are increasingly gathered by cheap and
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Stefan Schönig [email protected] Lars Ackermann [email protected] Stefan Jablonski [email protected] Andreas Ermer [email protected]
1
Institute of Management Information Systems, University of Regensburg, Regensburg, Germany
2
Institute for Computer Science, University of Bayreuth, Bayreuth, Germany
3
Maxsyma GmbH & Co. KG, Floß, Germany
numerous information-sensing IoT devices such as mobile devices, aerial (remote sensing), software logs, cameras, microphones, radio-frequency identification (RFID) readers, and wireless sensor networks. Therefore, IoT contributes to the recent trend known as big data. Handling big data requires techniques with new forms of integration to reveal insights from datasets that are diverse, complex, and of a massive scale [7–9]. Process execution, monitoring and analytics based on IoT big data can enable a more comprehensive view on processes. Embedding intelligence by way of real-time data gathering from devices and sensors and consuming them through BPM technology helps businesses to achieve cost savings and efficiency. Let us consider a production process where raw material is processed by different machines under the super
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