## 4 Case Study: Embraer E2 Model Aircraft Flag Track
### Detail of the Implemented Services
The purpose of these predictive models was to generate advanced safety measures, identifying potential anomalies in the mechanical behavior of the specimen early on and halting execution if necessary. The values predicted by the models were continuously contrasted with the values collected at each moment during the test. If the difference between these values exceeded a pre-established threshold, an alert was triggered from the processing center client, executed in the RPi node (leverage the results of the real-time analysis in Figure 2). Alert messages, triggered by the processing center application, were displayed in the GUI executed in the fog nodes. Also, the responsible operator of the test was notified about the alerts so that they could react immediately to the cause of the alert by taking the necessary measures. In order to receive and visualize these alert topics, a smartphone application was created, which connected the test operator with the IoT system used in the test (Figure 8). In addition to automatically receiving alerts on deviations from the measured values, this smartphone application, programmed using the MIT App Inventor software, also allowed remote and on-demand visualization of the values being measured in the tests, as well as the levels of battery charge in the IoT devices. The application automatically warns when the battery charge levels reach a certain threshold, e.g., 20% charge, and needs to be replaced soon. The IoT application also included an intrusion alert system for the restricted test area. Aeronautical component structural tests are conducted using large hydraulic, pneumatic and/or electromechanical actuators. These actuators are responsible for generating  
Figure 8: Smartphone application for visualize information about the progress of the structural test: (**a**) Battery status alerts, (**b**) Monitoring the status of selected test variables. the loads applied to the test specimens and can pose a risk to the physical integrity of humans. Access to the test area is restricted during the test in order to avoid accidents. However, other tasks are usually still being performed in the workshop adjacent to the testing area, and pedestrian traffic is common. To prevent accidental access to the restricted area during a test, an active surveillance system has been developed. This system was implemented on an RPi device, to which a webcam and an HC-SR04 position sensor were connected (Figure 4c). The alternative of using presence detectors was discarded due to the poor directionality of these sensors. A Python application, running on the RPi device, was responsible for acquiring the measurements taken by the sensors. This application activated the capture of an image with the webcam when the position measured by the sensor was less than the total distance of the restricted zone perimeter. This application automatically stored the image recorded by the webcam every time the sensor detected an obstacle in the restricted area, and sent the image for further analysis. In this way, the alert system automatically warned the test manager of possible invasions of the restricted area, sending the captured image and thus avoiding possible accidents.