Reliability of IoT-Aware BPMN Healthcare Processes

Author:

Domingos Dulce1,Respício Ana2,Martinho Ricardo3ORCID

Affiliation:

1. Universidade de Lisboa, Portugal

2. Operations Research Center/GUESS/Universidade de Lisboa, Portugal

3. School of Technology and Management, Polytechnic Institute of Leiria, Portugal

Abstract

BPMN (Business Process Model and Notation) has become the de-facto business process modelling language standard. Healthcare processes have been increasingly incorporating participants other than humans, including Internet of Things (IoT) physical devices such as biomedical sensors or patient electronic tags. Due to its critical requirements, IoT-aware healthcare processes justify the relevance of Quality of Services aspects, such as reliability, availability, and cost, among others. This chapter focuses on reliability and proposes to use the Stochastic Workflow Reduction (SWR) method to calculate the reliability of IoT-aware BPMN healthcare processes. In addition, the chapter proposes a BPMN language extension to provide processes with reliability information. This way, at design time, modellers can analyse alternatives and, at run time, reliability information can be used to select participants, execute services, or monitor process executions. The proposal is applied to an Ambient Assisted Living system use case, a rich example of an IoT-aware healthcare process.

Publisher

IGI Global

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Internet of things in Healthcare: a conventional literature review;Health and Technology;2023-07-20

2. A BPMN-VSM based process analysis to improve the efficiency of multidisciplinary outpatient clinics;Production Planning & Control;2022-07-13

3. Advancement of Machine Learning and Cloud Computing in the Field of Smart Health Care;Machine Learning Approach for Cloud Data Analytics in IoT;2021-07-13

4. Resilient Process Modeling and Execution Using Process Graphs;Communications in Computer and Information Science;2021

5. Graph-based Multi-Criteria Optimization for Business Processes;Lecture Notes in Business Information Processing;2020

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