# The Use of Augmented Reality for the Management of Equipment Ageing with a Virtual Sensor
## 4 Results
### Augmented Reality Results  
Figure 8 shows some screenshots of the results provided by the virtual sensor during an inspection made for the case study. The first operation to be carried out to use the virtual sensor is to frame the QR code of the equipment (Figure 8a). The code is positioned at a certain distance and at a certain height, depending on the orography of the territory as well as the arrangement of the unit of the establishment, to allow an easy overview during the walk of the inspector inside the plant. The device instantly recognises the vessel and shows the 3D model of the tank on the display in AR (Figure 8b). The colour of the equipment depends on its ageing state, i.e., the value of the ageing index during the last inspection; a legend to identify this state is available above the tank. Subsequently, by clicking on the \"Visualizza fondo\" (which translates to \"View bottom\") button at the top of the interface (Figure 8c), all the slabs making up the mantle and roof of the 3D model become transparent, even if the structure of the tank remains visible; at the same time, an iso-contour map is overlapped on the bottom, which represents the corrosion surface associated with the last performed inspection. The next step is to choose the year (past or future) for which the corrosion trend must be estimated (Figure 8d); this can be chosen by means of a pop-up menu on the bottom left button. For the same year, the ageing-related metrics (the corrosion rate, the pit density, the RUL, the probability of the critical pit, the ageing index, and the updated failure rate) and other general equipment information (name of the tank and the stored substance) are also displayed in a table placed on the right side of the equipment (Figure 8e). Finally, the last step of the use of the App Mobile concerns the visualisation of the graphs showing the trend of the ageing index, the corrosion rate, and the failure frequency vs. the time (year); this can be achieved by using a small pop-up menu on the \"Graphics\" button at the bottom right of the GUI (Figure 8f). Figure 8: Screenshots of the mobile display visualising augmented reality during a simulated safety walk in the establishment. (**a**) holistic view of equipment; (**b**) overlay 3D model; (**c**) bottom thickness map; (**d**) thickness map enlargement and scrolling of a pop-up menu; (**e**) table box information; (**f**) example of graph given and scrolling of the graphs pop-up menu. Below the translation is given for all the words (or phrases) that appear in this Figure: Visualizza fondo = View bottom. Molto carente = Very lack. carente = lack. Migliorabile = Improvable. adequato = Adequate. Indice di invecchiamento = Ageing index. Grafci = Graphs. Tra = Between. Anni = Years. Nome serbatoi = Tank name. Sostanza contenuta = Substance contained. Gasolio = Diesel. Anno ispezione = Inspection year. Probabilita di pit critico = Critical pit probability. Velocita di cortisonee = Corrosion rate. Indice di pit = Pit index. Chüudi = Close. For each movement of the inspector (i.e., the movement of the camera), the AR view updates according to the movement; for example, it allows zooming when he/she is approaching the framed area or shrinking if he/she moves away. The dots that can be observed on the tank bottom maps in Figure 8f are not the sampled points, but a graphical representation of the pit density, which increases over time due to the worsening of the material due to the corrosion [42]. The number of points displayed is correlated with the scale parameter of the distribution probability function used to model the phenomenon (note that for each 0.1 increment in the scale parameter, there is an increase of 50 points randomly scattered and displayed on the map). Some considerations must be made about the image resolution. It is certainly conditioned by the number of sampled points (points where the measurement was made during the last inspections).