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

Kirikkayis, Yusuf; Gallik, Florian; Reichert, Manfred

doi:10.1007/978-3-031-17604-3_7

Cited by 7 publications

(12 citation statements)

References 42 publications

(63 reference statements)

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“…A process model is considered as IoT-aware when it describes and depicts the influence of the Internet of Things on the process model [4,29,35,45]. IoT-aware process models consider the integration of individual IoT devices such as sensors, actuators, and objects.…”

Section: Iot-aware Process Modelsmentioning

confidence: 99%

“…As the electronic components of IoT devices are becoming cheaper, smaller, and more powerful, the IoT trend is progressing [2,3]. IoT devices are used in different domains such as cyber-physical systems, smart cities, and smart healthcare [4][5][6]. As IoT devices are typically equipped with actuators, sensors, network interfaces, and software, data can be collected from the physical environment and exchanged over the network.…”

Section: Introductionmentioning

confidence: 99%

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A User Study on Modeling IoT-Aware Processes with BPMN 2.0

Kirikkayis,

Winter,

Reichert

2024

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Integrating the Internet of Things (IoT) into business process management (BPM) aims to increase the automation level, efficiency, transparency, and comprehensibility of the business processes taking place in the physical world. The IoT enables the seamless networking of physical devices, allowing for the enrichment of processes with real-time data about the physical world and, thus, for optimized process automation and monitoring. To realize these benefits, the modeling of IoT-aware processes needs to be appropriately supported. Despite the great attention paid to this topic, more clarity is needed about the current state of the art of corresponding modeling solutions. Capturing IoT characteristics in business process models visually or based on labels is essential to ensure effective design and communication of IoT-aware business processes. A clear discernibility of IoT characteristics can enable the precise modeling and analysis of IoT-aware processes and facilitate collaboration among different stakeholders. With an increasing number of process model elements, it becomes crucial that process model readers can understand the IoT aspects of business processes in order to make informed decisions and to optimize the processes with respect to IoT integration. This paper presents the results of a large user study (N = 249) that explored the perception of IoT aspects in BPMN 2.0 process models to gain insights into the IoT’s involvement in business processes that drive the successful implementation and communication of IoT-aware processes.

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Section: Iot-aware Process Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A User Study on Modeling IoT-Aware Processes with BPMN 2.0

Kirikkayis,

Winter,

Reichert

2024

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“…The introduction of IoT technology into the BPM domain has been vibrantly discussed in recent years. Related work addresses a broad range of aspects to augment the modeling [24][25][26][27], execution [17,[28][29][30], monitoring [14,[31][32][33], and mining [2,4,11] of business processes with data and concepts from the IoT and CPS. Our work can be considered as a pre-processing stage of process mining where process-awareness of IoT data is increased and subsequently used for event extraction, event abstraction and event correlation [34].…”

Section: Bpm Meets Iotmentioning

confidence: 99%

An Interactive Method for Detection of Process Activity Executions from IoT Data

2023

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The increasing number of IoT devices equipped with sensors and actuators pervading every domain of everyday life allows for improved automated monitoring and analysis of processes executed in IoT-enabled environments. While sophisticated analysis methods exist to detect specific types of activities from low-level IoT data, a general approach for detecting activity executions that are part of more complex business processes does not exist. Moreover, dedicated information systems to orchestrate or monitor process executions are not available in typical IoT environments. As a consequence, the large corpus of existing process analysis and mining techniques to check and improve process executions cannot be applied. In this work, we develop an interactive method guiding the analysis of low-level IoT data with the goal of detecting higher-level process activity executions. The method is derived following the exploratory data analysis of an IoT data set from a smart factory. We propose analysis steps, sensor-actuator-activity patterns, and the novel concept of activity signatures that are applicable in many IoT domains. The method shows to be valuable for the early stages of IoT data analyses to build a ground truth based on domain knowledge and decisions of the process analyst, which can be used for automated activity detection in later stages.

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“…As shown in Figure 1, IoT devices and physical context play a crucial role when executing and monitoring IoT-driven BPs. However, when modeling the latter with BPMN 2.0, it does not become clear which tasks are IoT-related and which are not [9]. Instead, the process model viewer needs to interpret the task label to assess this.…”

Section: Problem Identification and Motivationmentioning

confidence: 99%

“…While certain IoT devices return raw sensor data, others deliver JSON-formatted results. Consequently, a process engine must be able to cope with IoT device characteristics [9]. On one hand, tools are needed to control and monitor the process, on the other, mechanisms are required to execute the IoT actions (i.e., sensing and actuating).…”

Section: Problem Identification and Motivationmentioning

confidence: 99%

BPMNE4IoT: A Framework for Modeling, Executing and Monitoring IoT-Driven Processes

et al. 2023

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The Internet of Things (IoT) enables a variety of smart applications, including smart home, smart manufacturing, and smart city. By enhancing Business Process Management Systems with IoT capabilities, the execution and monitoring of business processes can be significantly improved. Providing a holistic support for modeling, executing and monitoring IoT-driven processes, however, constitutes a challenge. Existing process modeling and process execution languages, such as BPMN 2.0, are unable to fully meet the IoT characteristics (e.g., asynchronicity and parallelism) of IoT-driven processes. In this article, we üresent BPMNE4IoT—A holistic framework for modeling, executing and monitoring IoT-driven processes. We introduce various artifacts and events based on the BPMN 2.0 metamodel that allow realizing the desired IoT awareness of business processes. The framework is evaluated along two real-world scenarios from two different domains. Moreover, we present a user study for comparing BPMNE4IoT and BPMN 2.0. In particular, this study has confirmed that the BPMNE4IoT framework facilitates the support of IoT-driven processes.

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

Cited by 7 publications

References 42 publications

A User Study on Modeling IoT-Aware Processes with BPMN 2.0

A User Study on Modeling IoT-Aware Processes with BPMN 2.0

An Interactive Method for Detection of Process Activity Executions from IoT Data

BPMNE4IoT: A Framework for Modeling, Executing and Monitoring IoT-Driven Processes

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