Process Model Reflection

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3.4 Analytical approach for process model extraction This work applied the following analytical approach to identify process activities and extract process model. The analytical approach is shown in Figure 2 and Figure 3. a). During the training/calibration phase, two operations are performed: mobile side executes training and generates 3 training data, which includes tuple timestamps and RSSIs of the full list of Bluetooth devices. The other opera- tion is manually record the training process, contains 1 information such as activity ID, activity begin and end time. Then, together with 2 the activity information/sensor settings defined in 3.1 b)., server side’s analytical process will compute 4 activity patterns and 5 other activity related…show more content…
In ad- dition, we evaluated the system and the analytical approach for process model extraction in a laboratory case study. We placed 17 Bluetooth transceivers in 8 locations in the computer science building in Aalto University to represent 9 activities. Figure 4 shows the setting of sensors in the process measurement. As mentioned, the performances of sensors vary and are neither stable nor con- sistent. In order to find an optimal setting of sensors, we conducted several experiments and found out that, the using of two sensors to represent one activ- ity helps improve the process measurement results. For comparison reasons, we wrote down the actual process on paper manually in addition to the automated process measurement with mobile devices. The process measurement results are presented in Figure 5a and Figure…show more content…
However, how to collect data from services has been a problem. This work focused on automated modelling of generic service processes that are location aware. In other words, activities in the process usually happen in a particular location and location information can be used to infer activities. Accordingly, we presented an approach to collect service process data based on wireless indoor positioning using inexpensive wireless sen- sors and smartphones. The objective of this work was to simplify the procedure of automated process modelling. For this reason, we designed a process data acquisition system to acquire minimised, but precise data set, instead of taking overwhelming redundant data. In our approach, Internet of things is integrated to implement real-time automated process modelling. We illustrated the ana- lytical approach for process model extraction in this system and we proved the performance of the process data acquisition system and the analytical approach in a case study. The results of the case study demonstrate that the system fulfils the demand of collecting precise process data for accurate process modelling. In addition, the presented approach has been tested and used in Tampere City dental care clinics. Their measurement results confirm the feasibility of this ap- proach in process modelling and the feasibility of using

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