Automatic Decomposition of IoT Aware Business Processes – a Pattern Approach

Domingos, Dulce; Respício, Ana; Martins, Francisco; Melo, Breno

doi:10.1016/j.procs.2019.12.188

Cited by 8 publications

(1 citation statement)

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“…Another approach is the definition of patterns for modeling IoT behavior. These patterns could, for example, reduce the number of message flows between the central pool and the IoT-aware pools by using the computing capacities of the IoT devices [51].…”

Section: C3 -Reducing the Complexity Of Iot-driven Business Rulesmentioning

confidence: 99%

Modeling, Executing and Monitoring IoT-Driven Business Rules with BPMN and DMN: Current Support and Challenges

Kirikkayis

Gallik

Reichert

2022

Lecture Notes in Computer Science

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The involvement of the Internet of Things (IoT) in Business Process Management (BPM) solutions is continuously increasing. While BPM enables the modeling, implementation, execution, monitoring, and analysis of business processes, IoT fosters the collection and exchange of data over the Internet. By enriching BPM solutions with real-world IoT data both process automation and process monitoring can be improved. Furthermore, IoT data can be utilized during process execution to realize IoT-driven business rules that consider the state of the physical environment. The aggregation of low-level IoT data into processrelevant, high-level IoT data is a paramount step towards IoT-driven business processes and business rules respectively. In this context, Business Process Modeling and Notation (BPMN) and Decision Model and Notation (DMN) provide support to model, execute, and monitor IoTdriven business rules, but some challenges remain. This paper derives the challenges that emerge when modeling, executing, and monitoring IoT-driven business rules using BPMN 2.0 and DMN standards.

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Section: C3 -Reducing the Complexity Of Iot-driven Business Rulesmentioning

confidence: 99%