Abstract
The Internet of Things (IoT) enables a variety of smart applications, including smart home, smart factory, and smart health. As Business Process Management (BPM) can also benefit from IoT technologies, the combined use of BPM and IoT has attracted considerable research works. Providing integrated lifecycle support for modeling, executing, and monitoring IoT-aware business processes constitutes a challenge. Existing process modeling and execution languages such as BPMN 2.0 are unable to fully meet the requirements of IoT-aware processes. In this paper, we present an extension of BPMN 2.0 for modeling, executing, and monitoring IoT-aware business processes. We introduce specific artifacts and events that enable IoT awareness during the execution and monitoring of IoT-driven business processes. The resulting framework is illustrated along a real-world scenario.
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References
Chang, C., Srirama, S.N., Buyya, R.: Mobile cloud business process management systems for the internet of things: a survey. ACM Comput. Surv. 49, 1–42 (2016)
Ashton, K.: That ‘internet of things’ thing. RFID J. 22, 97–114 (2009)
Kirikkayis, Y., Gallik, F., Reichert, M.: Towards a comprehensive BPMN extension for modeling IoT-aware processes in business process models. In: Guizzardi, R., Ralyté, J., Franch, X. (eds.) RCIS 2022. LNBIP, vol. 446, pp. 711–718. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-05760-1_47
Valderas, P., Torres, V., Serral, E.: Modelling and executing IoT-enhanced business processes through BPMN and microservices. J. Syst. Softw. 184, 111139 (2022)
Janiesch, C., et al.: The internet of things meets business process management: a manifesto. Syst. Man Cybern. Mag. 6, 34–44 (2020)
Hasić, F., Serral, E.: Executing IoT processes in BPMN 2.0: current support and remaining challenges. In: RCIS (2019)
Cheng, Y., et al.: Modeling and deploying iot-aware business process applications in sensor networks (2019)
Meyer, S., Ruppe, A., Hilty, L.: The things of the internet of things in BPMN. In: Conference in Advanced Information Systems Engineering Workshops (2015)
Sungur, C.T., et al.: Extending BPMN for wireless sensor networks. In: Business Informatics (2013)
Petrasch, R., Hentschke, R.: Process modeling for industry 4.0 applications towards an industry 4.0 process modeling language and method. In: Computer Science and Software Engineering (2016)
Alaaeddine, et al.: uBPMN: a BPMN extension for modeling ubiquitous business processes. Inf. Softw. Technol. 74, 55–68 (2016)
Torres, V., Serral, E., Valderas, P., Pelechano, V., Grefen, V.: Modeling of IoT devices in business processes: a systematic mapping study. In: CBI (2020)
Marrella, A., Mecella, M., Sardina, S.: SmartPM: an adaptive process management system through situation calculus, IndiGolog, and classical planning. In: Principles of Knowledge Representation and Reasoning (2014)
Kirikkayis, Y., Gallik, F., Reichert, M.: Modeling, executing and monitoring IoT-driven business rules with BPMN and DMN: current support and challenges. In: Almeida, J.P.A., Karastoyanova, D., Guizzardi, G., Montali, M., Maggi, F.M., Fonseca, C.M. (eds.) EDOC 2022. LNCS, vol. 13585, pp. 111–127. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-17604-3_7
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Kirikkayis, Y., Gallik, F., Reichert, M. (2023). A Holistic Framework for IoT-Aware Business Processes. In: Cabanillas, C., Garmann-Johnsen, N.F., Koschmider, A. (eds) Business Process Management Workshops. BPM 2022. Lecture Notes in Business Information Processing, vol 460. Springer, Cham. https://doi.org/10.1007/978-3-031-25383-6_8
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DOI: https://doi.org/10.1007/978-3-031-25383-6_8
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