## 7 Conclusions  
A localization algorithm with an estimation error of this magnitude is suitable for many applications. Advanced systems that improve and automate processes within cities will play a leading role in smart cities. From intelligently designed buildings that collect rainwater for later use to intelligent control systems that can autonomously monitor infrastructure, the potential improvements enabled by sensor technology are immense. Ubiquitous sensing inherently poses many technical and social challenges [38]. Improved localization ensures security and up-to-dateness where needed. A study in France assumes that the average parking space search time in large cities is up to 40 min, which equates to \begin{table}
\begin{tabular}{c c} \hline \hline
**Lambda** & **Accuracy Result** \\ \hline
0.006 & 98\% \\
0.01 & 95\% \\
0.03 & 95\% \\
0.16 & 84\% \\
0.3 & 59\% \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparative table of different lambda values and relative accuracy results. Figure 18: This figure shows the accuracy obtained in the case of an average position estimation error of 5 m.  
70 million hours or EUR 700 million in costs per year [39]. Another possible application is related to the customized signaling of escape routes in shopping centers or stadiums in case of adverse events. Once the threat has been identified, the system can guide users in a dynamic and personalized way, providing the necessary actions to keep them safe (e.g., finding the safest way out, not necessarily the closest one). Unmanned Aerial Vehicles are another interesting application set. Measurements are important both for drone motion and the performance of the drone's intended mission. The sensors used to collect the data required to operate unmanned vehicles vary widely in terms of technology, performance and the measurement accuracies to consider. The range of applications for these systems is constantly increasing in number and complexity, requiring new measurement options and methods [40]. Location-based services are a growing market. Location-based services not only bring commercial benefits, they can also improve the quality of life for people with disabilities and save lives in emergency situations. Future work will be focused on sensor localization with UAVs and, in particular, on UAV tracking techniques and cooperative control of multiple UAVs. Conceptualization, A.P. and M.T. ; methodology, A.P. ; software, A.P. ; validation, M.T. ; formal analysis, A.P. ; investigation, M.T. ; writing--original draft preparation, A.P. ; writing--review and editing, M.T. All authors have read and agreed to the published version of the manuscript. This research received no external funding. * LoRaWANTM (2022) LoRaWANTM 1.1 Specification. Available online: [[https://lora-alliance.org/wp-content/uploads/2020/11/lorawantm_specification_v1.1.pdf](https://lora-alliance.org/wp-content/uploads/2020/11/lorawantm_specification_v1.1.pdf)]([https://lora-alliance.org/wp-content/uploads/2020/11/lorawantm_specification_v1.1.pdf](https://lora-alliance.org/wp-content/uploads/2020/11/lorawantm_specification_v1.1.pdf)) (accessed on 26 September 2022). * [PERSON] et al. (2018) [PERSON]; [PERSON]; [PERSON]; [PERSON]; Sigfox and LoRaWAN Datasets for Fingerprint Localization in Large Urban and Rural Areas. _Data_**2018**, \(3\), 13. [CrossRef]
* LoRaWAN Dataset Antwerp (2022) LoRaWAN Dataset Antwerp. Available online: [[https://zenodo.org/record/3342253/files/lorawan_antwerp_2019_dataset.csv?download=1](https://zenodo.org/record/3342253/files/lorawan_antwerp_2019_dataset.csv?download=1)]([https://zenodo.org/record/3342253/files/lorawan_antwerp_2019_dataset.csv?download=1](https://zenodo.org/record/3342253/files/lorawan_antwerp_2019_dataset.csv?download=1)) (accessed on 22 November 2022). * [PERSON] and [PERSON] (2006) [PERSON]; [PERSON] RSSI Is Under-Appreciated. In Proceedings of the Third Workshop on Embedded Networked Sensors (EmNets), Cambridge, MA, USA, 30-31 May 2006.