## 5 Discussion
It is very likely, that--according to the literature findings [13]--this aspect would be better assessed after the operators' have a longer period of experience with AR goggles. The second worst result (slightly positive or almost neutral impact) has been obtained while examining the relationship between the process reliability and the function of the automatic verification of graphical labels. After discussion with operators, they have explained their concerns about the function of the automatic recognition of graphical pictograms. The reliability of automatic recognition has been considered by the operators to be too low, making them not want to rely completely on the AR application during the controlling of DG shipments. The level of the recognition accuracy has been examined quantitatively in laboratory conditions. The observed probability of the correct recognition and the indication of labels were in the range of 0.43 (only one group of labels) to 1. The worst results were observed for DG pictograms from group 2.1 (the probability = 0.43), then for the group 7 (the probability = 0.5 for subgroup no. III and the probability = 0.72 for subgroup no. II). The rest of graphical pictograms were correctly indicated, with the probability being very close to 1. In the survey, DG operators were also allowed to leave their additional comments (open question) on positive and negative aspects which they noticed while using applications in tested areas. The results of the analysis of their responses, as well as our experience from the research, has let us form a list of conclusions which make it possible to answer the cognitive questions that form the main premise of this research:  
* Every operation of the DGA process, in the experts' opinion, reveals the potential for the use of IT tools using AR technology and is considered as the source of possible improvements of the process results;
* The main aspects of the DGA process, which can be improved by the AR solutions (the highest score values given by operators) are as follows: \(\circ\) The process reliability, especially thanks to:
* The easiness and comfort of the acquisition of controlled DG shipment data for an operator in every place of a warehouse. The connection of the AR tool with a shipments' database lets the operator have access to various data from the shipment, which they look at through AR goggles (e.g., Figure 6). * The reduction in possible mistakes resulting from the complexity and the size of law regulations for a DG shipment. Only a chosen regulation or a set of chosen regulations (and/or only a chosen acceptance list) can appear in the form of a virtual picture next to an automatically identified shipment; it makes the mistake less likely than in cases when an operator searches for related regulations, which they identify by themselves, for the shipment. * The possibility to attract the attention of an operator in the case of the identified incapability between permissible and real shipment parameters. Coloured warnings decrease the mistake probability for the operator. * The support of an operator throughout the verification of the text markings on a DG shipment. In the case of discovered non-compliance of the text on the shipment packaging with the required text (especially in regard to typos in the address or technical names for DGs), a virtual message attracts the operator's attention, limiting the mistake probability. The process duration thanks to the following: * The fast automatic choice and virtual presentation of required law regulations and/or an acceptance lists for a shipment. * The fast and automatic verification of text markings on a DG shipment--visual control of the complex text lasts much longer than the automatic one. * Both supporting tools using AR technology (smartphone and goggles) allowed us to compare the virtual possibilities offered by the tested levels of virtual reality combined with the real world.