UT Institute of Computer Science Graduation Theses Registry

Name

Pätris Halapuu

Abstract

Process Management Systems (PMSs) are more and more used to support highly dynamic situations and cooperative processes. Some domains have great diversity of environment variables that can change during the process and therefore affect the workflow in a way that process can not be successfully carried out. Such can be emergency management, health care and other domains involving in most cases in-field actors. In those domains, the frequency and variety of unexpected changes is really high compared to classical business domains that current Business Process Management (BPM) solutions can handle. In 2011, a model and an initial proofof-concept prototype of SmartPM (Smart Process Management) was introduced in Sapienza - Universit´a di Roma that is able to automatically cope with unplanned changes. The continuous screening of the real-world factors is suggested for such domains. A cyber-physical system can be created to automate the screening via physical-to-digital bridge. This bridge can be a set of tools consisting of sensors, mobile devices and translation layer to extract and feed the real-world information to the digital system. Challenge arises when transferring the information from sensors to the system as the system works with discrete values, but the information gathered by the sensors is continuous in most cases. To target this problem, a concrete solution is proposed and implemented by the author. This thesis explains the architecture and implementation of the sensor-aware task list handler and the web tool approach that was created to solve the discretization challenge of the real-world values. It is also explained how the adaptive PMS, SmartPM, was further developed and updated as the contribution of this thesis.

Graduation Thesis language

English

Graduation Thesis type

Master - Software Engineering

Supervisor(s)

Fabrizio Maria Maggi, Massimo Mecella, Andrea Marrella

Defence year

2015