IoTDM4BPMN: An IoT-Enhanced Decision Making Framework for BPMN 2.0

Kirikkayis, Yusuf and Gallik, Florian and Reichert, Manfred (2022) IoTDM4BPMN: An IoT-Enhanced Decision Making Framework for BPMN 2.0. In: International Conference on Service Sciences (ICSS 2022), May 13-15, 2022, China, Zhuhai.

[thumbnail of ICSS_2022_paper_43.pdf] PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (928kB)


The relevance of the Internet of Things (IoT) for Business Process Management (BPM) support is increasing. IoT devices enable the collection and exchange of data over the Internet, whereby each physical device is uniquely identifiable through its embedded computing system. BPM, in turn, is concerned with analyzing, discovering, modeling, executing, and monitoring (digitized) business processes. By enhancing BPM systems with IoT capabilities, real-world data can be gathered and considered during process execution to enhance process monitoring as well as IoT-driven decision making. In this context, the aggregation of low-level IoT data into high-level process-relevant data constitutes a fundamental step towards IoT-driven decisions in business processes. This paper presents IoT Decision Making for Business Process Model and Notation (IoTDM4BPMN) a webbased framework for modeling, executing, and monitoring IoTdriven decisions in real-time. We give insights into the design and implementation of IoTDM4BPMN and provide a case study as a first validation that applies IoTDM4BPMN to the modeling, executing, and monitoring of a real-world IoT-driven decision process.

Item Type: Conference or Workshop Item (Paper)
Subjects: DBIS Research > Publications
Divisions: Faculty of Engineering, Electronics and Computer Science > Institute of Databases and Informations Systems > DBIS Research and Teaching > DBIS Research > Publications
Depositing User: M.Sc. Yusuf Kirikkayis
Date Deposited: 25 Jan 2023 15:17
Last Modified: 25 Jan 2023 15:17

Actions (login required)

View Item
View Item