# Radio Wave Propagation and WSN Deployment in Complex Utility Tunnel Environments +
## 5 Conclusions  
In this work, the radio wave propagation assessment and wireless system deployment for real urban utility tunnels was described. The impact of large obstacle density, given by the inclusion of elements such as service trays or handrails, as well as the presence of occupational staff within the underground utility tunnels, was analyzed by means of an in-house 3D-RL code. The calibration and validation of the 3D-RL algorithm for this singular scenario were presented by comparison with experimental measurements in the real scenario, showing good agreement between them. Once the optimal simulation parameters were obtained from the experimental measurements, the large and small-scale simulation results were presented to characterize the radio wave propagation within the tunnel. A complete volumetric analysis was performed in order to consider the location of wireless transceivers and enable them to be embedded within the elements of the tunnels. The system-level analysis considering the conventional transceiver parameters (ZigBee and LoRaWAN) was performed for an 868-MHz operational frequency, obtaining the initial deployment planning results. The use of higher frequencies could lead to a higher signal attenuation, and then, the coverage could be affected within the underground tunnel. Additionally, an infrastructure security and work safety monitoring application were developed in which the information was stored in a private Cloud. The proposed methodology enables to consider specific propagation losses in complex urban utility tunnels in order to provide a better understanding of the physical characteristics of the system.  
Figure 20: Web-based monitoring tool.  
to deploy wireless communication systems with optimal coverage, minimum interference and an enhanced quality of service.  
Conceptualization, L.A. and P.L.-I.; methodology, L.A.; software, M.C.-E. and I.P.; validation, M.C.-E.; formal analysis, M.C.-E., L.A. and P.L.-I.; investigation, M.C.-E. and L.A.; data curation, M.C.-E. and I.P.; writing--original draft preparation, L.A. and M.C.-E.; writing--review and editing, P.L.-I., J.J.A. and F.F.; visualization, E.A. and M.C.-E.; supervision, F.F.; wireless network planning, P.L.-I. and I.P.; cloud design and development, J.J.A., monitoring system design and development J.J.A. and J.V. and funding acquisition, F.F. All authors have read and agreed to the published version of the manuscript.  
This research was funded in part by the School of Engineering and Sciences at Tecnologico de Monterrey, in part by Project KIT2018-095499-B-C31, funded by Ministerio de Ciencia, Innovacion y Universidades, Gobierno de Espana (MCIU/AEI/FEDER, UE) and, in part, by the European Union's Horizon 2020 research and Innovation program under grant agreement N\({}^{\circ}\)774094 (Stardust-Holistic and Integrated Urban Model for Smart Cities).  
The authors would like to acknowledge the support and collaboration of the School of Engineering and Sciences and the Focus Research Group of Telecommunications and Networks at Tecnologico de Monterrey.  
The authors declare no conflict of interest. The statements made herein are solely the responsibility of the authors.