# Implementing an Industry 4.0 UWB-Based Real-Time Locating System for Optimized Tracking
## 4 Results and Discussion  
In this section, a typical use case is described, using both the hardware devices and the developed software tool to dynamically monitor tags in an indoor environment. A computer that executes the proposed software tool is connected to the main anchor using the USB interface; it retrieves the relative anchor-tag distance measurements. The software calculates the exact location of the tags and plots them on the map (Figure 9). Thus, to determine the accuracy of the system (software and hardware), two experiments were conducted. In both experiments, the accuracy of the tag was measured in a 2D facility of approximately 26 square meters. Specifically, the experiments were executed by placing the tag at point A and then moving it consecutively to points B, C, D, E, and F (Figure 9a). In the first experiment, a normal trilateration algorithm was used without identifying NLOS conditions; in the second experiment, our proposed algorithm was used. In the normal trilateration algorithm, all three anchor-tag measurements are utilized, even when conducted under NLOS conditions, which can lead to increased ranging errors. The system's accuracy and the deviation of the calculated points were measured to determine the overall localization error. For the experiment, the maximum movement speed \(Vmax_{i}\) was 0.8 m/s. In Figure 9a, the actual points where the tag device was placed are shown with red dots. For each point, 100 samples (position estimations) were collected with a frequency of 1 samples/s, which leads to a constant \(dt_{ij}\) of 1 s. It is worth noting that the experiments were conducted in an indoor area where a concrete pillar was used to obstruct the direct path between the tag and an anchor (with a different anchor each time). It is evident that the proposed environment cannot be a harsh NLOS environment; this plays a crucial role when the primary goal is the NLOS range correction. However, in our case, the concrete pillar in the facility obstructs the direct path between the anchor devices and the tag to demonstrate how the proposed algorithm reacts in such cases in order to provide a solution in NLOS conditions. Significant localization errors are anticipated for points B, C and D, as the tag device communicates with the anchors under NLOS conditions (at point B, there is NLOS communication with anchor 3, at point C with anchor 2, and at point D with anchor 1). Even under NLOS conditions, the communication between the tag and the anchors was successful but this led to increased errors regarding the anchor-tag measured distances and  
Figure 9: (**a**) The developed RTLS application and the positions where the tag device was placed; (**b**) experimental environment. provided an increased localization error. After the execution of the experiments, the deviations were plotted on a box plot graph to compare the results. In Figure 10, the box plots for 100 measurements at points B, C, and D are depicted; the overall NLOS errors (all 300 measurements from points B, C, and D) of the normal trilateration algorithm and the proposed algorithm are also illustrated. The proposed algorithm in two of the three cases (on points B and D) was able to identify the NLOS conditions on the anchor-tag measurements and excluded the measurement that was identified as NLOS. For point C, the algorithm also recognized the NLOS communication between the tag and anchor 2. The problem in that case was that Equation (10) was not satisfied, producing the same results as the normal trilateration algorithm. In conclusion, the proposed algorithm helps with asset localization and has better accuracy when there are obstacles between the tag and the anchors as it can identify the existence of NLOS conditions. The algorithm can Identify and exclude error-prone measurements and track the tag more accurately. Finally, the RMSEs were calculated to highlight the accuracy of the system. Specifically, the RMSE was calculated for the two independent axis and for the Euclidean distance.