# Implementing an Industry 4.0 UWB-Based Real-Time Locating System for Optimized Tracking
## 5 Conclusions  
The primary objective of driving our study was to develop an efficient RTLS solution tailored for industrial applications within the Industry 4.0 framework. This article presents a comparison of the state-of-the-art RTLS implementations, showing that UWB technology is in a mature state, while providing a taxonomy for the existing tracking technologies and a comparison matrix for supporting decision making in the selection of the most suitable technology for real-time tracking in indoor areas. Based on this analysis, the proposed RTLS solution (hardware and software) was developed. Additionally, we introduce an algorithm capable of determining a tag's position using only two anchors under specific conditions. The results demonstrate that the proposed system effectively localizes assets with high accuracy, enabling industries to monitor their resources efficiently. As a result, the proposed method can achieve an RMSE of 0.18 m for 80% of the observations compared to 50% when using the normal trilateration method. The proposed method has a maximum error of 0.26 m, as compared to 0.37 m for the normal trilateration. The experiments show-cased that the proposed algorithm improves the overall positioning error by 24%, reporting an RMSE of 0.124 m in comparison to the 0.163 m of the normal trilateration method. This provides a notable competitive edge, especially in industrial settings with numerous dynamic and static obstacles -- such as corridors lined with tall racks -- which frequently demand NLOS operations with limited anchors. Ultimately, the proposed system is suitable for tracking assets moving at low speeds, showing high accuracy in indoor environments (a positioning error of 10-20 cm), when provided with at least two LOS anchor-tag range measurements at any given position. The system has low power consumption, entailing low maintenance needs for portable devices. It also covers around 200 square meters using just three anchors, while allowing for the easy installation of additional anchors in areas with numerous obstacles (i.e., harsh NLOS environments). The NLOS identification method that was used in this experiment, which relies on the maximum tag speed, has certain limitations. It requires the tag to move at low speeds to effectively determine when a new distance measurement is likely a false indication due to communication occurring under NLOS conditions. For future research, the algorithm could be further enhanced by incorporating more sophisticated and precise methods for NLOS identification that can be found in the literature [60,82]. This advancement would  
Figure 11: (**a**) Actual tag position at point B and estimated positions with the normal trilateration and the proposed algorithm. (**b**) Cumulative distribution function of the Euclidean error of the normal trilateration and the proposed algorithm. contribute to further improving the localization accuracy of the RTLS. Additionally, it is essential to conduct extensive testing of the proposed system in daily industrial operations to evaluate its performance under real-world conditions. Conceptualization, A.S.; methodology, A.S.; software, A.S.; validation, A.S.; investigation, A.S.; resources, A.S.; writing\(-\)original draft preparation, A.S.; writing\(-\)review and editing, D.B. and D.V. ; visualization, A.S. and D.V. ; supervision, D.B. and D.V. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Not applicable. The data presented in this study are available on request from the corresponding author due to privacy restrictions. The authors declare no conflicts of interest. The following abbreviations are used in this manuscript: