Artifact-Driven Business Process Monitoring - A Novel Approach to Transparently Monitor Business Processes, Supported by Methods, Tools, and Real-World Applications (Paperback, 1st ed. 2019)


This book proposes a novel technique, named artifact-driven process monitoring, by which multi-party processes, involving non-automated activities, can be continuously and autonomously monitored. This technique exploits the Internet of Things (IoT) paradigm to make the physical objects, participating in a process, smart. Being equipped with sensors, a computing device, and a communication interface, such smart objects can then become self-aware of their own conditions and of the process they participate in, and exchange this information with the other smart objects and the involved organizations. To allow organizations to reuse preexisting process models, a method to instruct smart objects given Business Process Model and Notation (BPMN) collaboration diagrams is also presented. The work constitutes a revised version of the PhD dissertation written by the author at the PhD School of Information Engineering of Politecnico di Milano, Italy. In 2019, the PhD dissertation won the "CAiSE PhD award", granted to outstanding PhD theses in the field of Information Systems Engineering.

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Product Description

This book proposes a novel technique, named artifact-driven process monitoring, by which multi-party processes, involving non-automated activities, can be continuously and autonomously monitored. This technique exploits the Internet of Things (IoT) paradigm to make the physical objects, participating in a process, smart. Being equipped with sensors, a computing device, and a communication interface, such smart objects can then become self-aware of their own conditions and of the process they participate in, and exchange this information with the other smart objects and the involved organizations. To allow organizations to reuse preexisting process models, a method to instruct smart objects given Business Process Model and Notation (BPMN) collaboration diagrams is also presented. The work constitutes a revised version of the PhD dissertation written by the author at the PhD School of Information Engineering of Politecnico di Milano, Italy. In 2019, the PhD dissertation won the "CAiSE PhD award", granted to outstanding PhD theses in the field of Information Systems Engineering.

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Product Details

General

Imprint

Springer Nature Switzerland AG

Country of origin

Switzerland

Series

Lecture Notes in Business Information Processing, 368

Release date

October 2019

Availability

Expected to ship within 10 - 15 working days

First published

2019

Authors

Dimensions

235 x 155mm (L x W)

Format

Paperback

Pages

161

Edition

1st ed. 2019

ISBN-13

978-3-03-032411-7

Barcode

9783030324117

Categories

LSN

3-03-032411-7



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