{"title":"物联网增强的BPMN 2.0决策框架","authors":"Yusuf Kirikkayis, Florian Gallik, M. Reichert","doi":"10.1109/ICSS55994.2022.00022","DOIUrl":null,"url":null,"abstract":"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 web-based framework for modeling, executing, and monitoring IoT-driven 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.","PeriodicalId":327964,"journal":{"name":"2022 International Conference on Service Science (ICSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"IoTDM4BPMN: An IoT-Enhanced Decision Making Framework for BPMN 2.0\",\"authors\":\"Yusuf Kirikkayis, Florian Gallik, M. Reichert\",\"doi\":\"10.1109/ICSS55994.2022.00022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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 web-based framework for modeling, executing, and monitoring IoT-driven 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.\",\"PeriodicalId\":327964,\"journal\":{\"name\":\"2022 International Conference on Service Science (ICSS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Service Science (ICSS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSS55994.2022.00022\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Service Science (ICSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSS55994.2022.00022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
IoTDM4BPMN: An IoT-Enhanced Decision Making Framework for BPMN 2.0
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 web-based framework for modeling, executing, and monitoring IoT-driven 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.