# BPMNE4 IoT: A Framework for Modeling, Executing and Monitoring IoT-Driven Processes +
## 6 Prototype Evaluation
### Smart Factory Scenario  
We use a smart factory model provided by _Fischertechnik_ (FT) ([[https://www.fischer](https://www.fischer)]([https://www.fischer](https://www.fischer)) technik.de/en/simulating/industry-4-0, accessed on 14 December 2022)) to emulate a real-world smart factory. Figure 14 shows this factory, which simulates a complete production line. In detail, the smart factory consists of five stations: the high-bay warehouse, vacuum gripper robot, oven, milling machine and sorting machine. The smart factory is equipped with six different types of IoT sensors (cf. Figure 14), whose short labels and colors are summarized in Table 2.  
In addition to the sensors of the smart factory, the scenario comprises four sensor types that measure the state of the environment (cf. Table 3). In total, the smart factory has 34 sensors (see Figure 14), including 7 light barrier sensors that detect the interruption of a light beam, 10 limit switch sensors that are activated by the movement of a machine part or the presence of an object, 3 pressure sensors that measure the intake pressure, one temperature sensor that measures oven temperature, 4 encoder sensors that return the current motor position and one color sensor that detects  
Figure 13: Excerpt of an output event log showing a segment of an IoT-driven Process in CSV Format. the color of the workpiece. In addition, two vibration sensors, two brightness sensors, two humidity sensors and two air quality sensors are used to evaluate the workpiece condition. Figure 15 illustrates a production process enabled by the smart factory. This example shows how we can model, setup, execute and monitor the IoT-driven BP based on the BPMNE4 IoT framework. First of all, a white workpiece (WP) is transported to the transfer point of the high-bay warehouse. While delivering the workpiece, the vacuum gripper moves to the transfer point and waits until the condition of the IoT catch artifact evaluates it to be true. The _Outside LB triggered_ catch artifact evaluates whether or not a light barrier is activated. The process may end, for example, if the condition is not satisfied within 120 s, e.g., due to network errors or defective sensors. The transport of the workpiece is activated by the _Vacuum Gripper_ object artifact (cf. Section 5.2.4) and the oven is waiting for the arrival of the workpiece. Upon arrival, it is burned and then transported to the turntable for milling. Subsequently, the workpiece is transported to the sorting machine via  
Figure 14: Overview of components and sensors in the smart factory. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**IoT Sensor Type** & **Quantity** & **Short Label** & **Color** \\ \hline Limit switch & 10 & LM & Red \\ Light barrier & 7 & LB & Yellow \\ Pressure sensor & 3 & CR & Blue \\ Temperature sensor & 1 & TS & Orange \\ Encoder sensor & 4 & EC & Cyan \\ Color sensor & 1 & CL & Purple \\ \hline \hline \end{tabular}
\end{table} 
Table 2: IoT sensors of smart factory with short label and color. \begin{table}
\begin{tabular}{c c c} \hline \hline
**IoT Sensor Type** & **Quantity** & **Short Label** & **Color** \\ \hline Vibration sensors & 2 & VR & Pink \\ Brightness sensors & 2 & BN & Green \\ Humidity sensor & 2 & HD & Neon Green \\ Air quality sensor & 2 & AQ & Brown \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Environment sensors of smart factory with short label and color. a conveyor belt. After activating the light barrier, the color of the workpiece is automatically determined to sort it by color. Finally, the process terminates. The BPMS (cf. Section 5.3) manages the smart factory. First, the IoT-driven process must be modeled, accompanied by the configuration of the involved IoT devices. The modeling part of the BPMS is shown in Figure 15. It offers both the traditionalBPMN 2.0 elements and the described IoT-specific artifacts and events (see Section 5.3). The process model depicted in Figure 15 comprises an object artifact, an IoT intermediate catch event, and an IoT intermediate catch artifact.