## 4 The Results
### Design of Applications Supporting a DG Operator
The application developed for AR goggles (Magic Leap 1);
2. The application developed for a smartphone (for Android operating system). Figure 4a depicts an operator who was testing the AR goggles in near-operational conditions. It can set a context--how the operator's work looked when they were using AR goggles. Figure 4b presents the view, which is visible for an operator in Magic Leap glasses, if an AR picture is turned off. This figure gives an insight to the level of resolution which can be achieved by the tested goggles' cameras (the goggles have four cameras which can capture pictures with a resolution of 2 megapixels and videos with 1460 \(\times\) 1080 pixels) for the needs of automatic identification in developed applications. Both versions of applications, due to used tools, can present different elements of DGA using AR. AR goggles can provide a constant virtual picture for an operator when they are on the operator's head, while, when using a smartphone, the operator must look purposefully at the smartphone screen to see the picture. From this perspective, the level of immersion provided by the AR goggles can be considered as higher than that of a smartphone. Table 2 presents the results of the analysis based on previously defined supporting areas and can be used to design the potential applications' functions. It presents how a function is currently executed in the examined airport and what potential effect the designed support can have for the function. Examples of a few practical solutions resulting from the assumptions presented in Table 2 are presented in Figures 5-7. The screen captures come from the original application developed in the project in its original language. To increase their readability in the paper, all meaningful headlines are additionally translated into English. The translation is given just next to an explained caption. Figure 5 depicts the screen with the shipment data that is available in the smartphone application. Figure 6 also presents the shipments' data but in  
Figure 4: Practical testing of AR solutions: (**a**) an operator while using AR goggles, (**b**) the view visible for her/him in Magic Leap glasses if an AR picture is turned off. the form of virtual frames with the text visible in AR goggles. A DG operator can see them as soon as the goggles automatically identify a shipment (with their photo camera) when they wear it. Figure 7 presents pictures from experiments conducted with the automatic recognition of graphical labels, which are necessary to use on DG shipments during their air transport. The automatic function is able to draw a virtual frame around a label and display the text characterizing the group of DG material (number of the group and its name in the Polish language). The last number visible on the red area (DG group 2.1) means the value of probability that the recognized label belongs to group 2.1 of DG materials. Examples in Figures 5-7 make clear the difference between the two tested forms of the communication of both applications with a DG operator. It should be noted that Figure 7 presents the results of the automatic recognition of graphical labels. Purposefully, it also shows one of the main limits that should be considered when one would like to apply automatic verification of the labelling and the marking of shipments of DGs. The white label (the grey frame) from the group 2.3 (poisoned gas with the symbol of a skull), depending on the quality of its picture, can be incorrectly recognized, like in this case--as the group 6.2 (the green frame). This limit for DGA automation is discussed in the future part of the paper.