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

被引:6
作者
Kirikkayis, Yusuf [1 ]
Gallik, Florian [1 ]
Reichert, Manfred [1 ]
机构
[1] Ulm Univ, Inst Databases & Informat Syst, Ulm, Germany
来源
ENTERPRISE DESIGN, OPERATIONS, AND COMPUTING, EDOC 2022 | 2022年 / 13585卷
关键词
IoT; BPM; BPMN; DMN; Business rules; Challenges; OUTLIER DETECTION; INTERNET; THINGS;
D O I
10.1007/978-3-031-17604-3_7
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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 process-relevant, 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 IoT-driven 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.
引用
收藏
页码:111 / 127
页数:17
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[1]   A Survey of Outlier Detection Techniques in IoT: Review and Classification [J].
Al Samara, Mustafa ;
Bennis, Ismail ;
Abouaissa, Abdelhafid ;
Lorenz, Pascal .
JOURNAL OF SENSOR AND ACTUATOR NETWORKS, 2022, 11 (01)
[2]  
[Anonymous], 2010, Business Process Model and Notation (BPMN). Version 2.0
[3]  
[Anonymous], 2022, CAMUNDA PROCESS ENGI
[4]  
Ashton K., 2009, RFID J, V22, P97
[5]  
Barin S., 2022, ENG SCI TECHNOL INT, V34, P101174, DOI [10.3390/biophysica2030025, 10.1016/j.jestch.2022.101174]
[6]   From BPMN process models to DMN decision models [J].
Bazhenova, Ekaterina ;
Zerbato, Francesca ;
Oliboni, Barbara ;
Weske, Mathias .
INFORMATION SYSTEMS, 2019, 83 :69-88
[7]   Outlier Detection in Indoor Localization and Internet of Things (IoT) using Machine Learning [J].
Bhatti, Mansoor Ahmed ;
Riaz, Rabia ;
Rizvi, Sanam Shahla ;
Shokat, Sana ;
Riaz, Farina ;
Kwon, Se Jin .
JOURNAL OF COMMUNICATIONS AND NETWORKS, 2020, 22 (03) :236-243
[8]   An Architecture and Its Tools for Integrating IoT and BPMN in Agriculture Scenarios [J].
Celestrini, Jordano R. ;
Rocha, Renato N. ;
Saleme, Estevao B. ;
Santos, Celso A. S. ;
Pereira Filho, Jose G. ;
Andreao, Rodrigo V. .
SAC '19: PROCEEDINGS OF THE 34TH ACM/SIGAPP SYMPOSIUM ON APPLIED COMPUTING, 2019, :824-831
[9]   Fall-curve: A novel primitive for IoT Fault Detection and Isolation [J].
Chakraborty, Tusher ;
Nambi, Akshay Uttama ;
Chandra, Ranveer ;
Sharma, Rahul ;
Swaminathan, Manohar ;
Kapetanovic, Zerina ;
Appavoo, Jonathan .
SENSYS'18: PROCEEDINGS OF THE 16TH CONFERENCE ON EMBEDDED NETWORKED SENSOR SYSTEMS, 2018, :95-107
[10]   Mobile Cloud Business Process Management System for the Internet of Things: A Survey [J].
Chang, Chii ;
Srirama, Satish Narayana ;
Buyya, Rajkumar .
ACM COMPUTING SURVEYS, 2017, 49 (04)