## 4 Conclusions  
This work provides a framework and system specification to use the currently deployed 4G telecommunication network to transmit real-time telemetry and video data from a UAS to a control ground station. Results are presented that show how data is being collected and exploited to improve traffic and road infrastructure monitoring. The on-board payload contains, apart from the drone, its flight controller (FC) and its positioning systems (GNSS), an extra microcomputer capable of reading telemetry data from the FC and video from a peripherical camera. A USB-moden and a SIM card connect the drone to the 4G network. The dedicated software allows the tunneling of such data though a Virtual Private Network to the public internet and towards the desired ground station. We have shown the logical schematic of such system and the main parameters needed for it to work, as well as experimental data carried out in a test site to prove the feasibility of the system. The on-board system combined with the 4G terrestrial antennas network have a limited capacity of performance, which was found to limit the upload stream to 9 Mbps and the download stream to 15 Mbps. Also, the 4G coverage is better when the drone is in the air than close to/on the ground, i.e., less than 400 ft (120 m) over the terrain, due to the 4G network antennas lobule shape and the absence of topographic shadows.  
The complete 4G framework for drone telemetry and video is a solution for BVLOS operations that overpasses the classical radio-link range. Moreover, we foresee that this  
Figure 9: The drone tracks a flight plan following the linear infrastructure and takes images. The imagery is saved in EXO Data dockers and postprocessed using photogrammetric, remote sensing and GIS software. The infrastructure manager can retrieve information for conservation, maintenance or exploitation purposes.  
study that can be a base for an upcoming upgrade to 5G networks, since the challenges that cannot be reached with 4G technology in terms of data consumption and latency will be reached with the next communication paradigm. Data collection continues and further enhancements of the traffic monitoring tools are anticipated during the final year of the StratoTrans project [18].  
Conceptualization, J.-C.P.; Methodology, J.-C.P. and R.G.; formal analysis, EACOM, J.O.; investigation, R.G., J.-C.P. and A.Z.; UAS data acquisition and flight planning, J.-C.P. and A.Z.; data curation, A.Z.; writing--original draft preparation, R.G.; writing--review and editing, J.-C.P.; visualization, R.G.; supervision, J.-C.P.; project administration, J.-C.P.; Computer Vision formal analysis and supervision, A.B. and P.C.; funding acquisition J.-C.P. All authors have read and agreed to the published version of the manuscript.  
This work was funded by Exodronics SL and was partially supported by the Spanish Government through the Centro para el Desarrollo Tecnologico Industrial (CDTI) under the StratoTrans Project [IDI-20191270] (Proyecto cofinanciado por el Centro para el Desarrollo Tecnologico e Industrial (CDTI) en el marco de la convocatoria de Proyectos de I + D de Transferencia Tecnologica CERFERA).  
Not applicable.  
This work was boosted by the R&D department of Exodronics SL, and partially supported by the Spanish Government through the Centro para el Desarrollo Tecnologico Industrial (CDTI) under the StratoTrans Project [IDI-20191270]. We would like to acknowledge the collaborators in the StratoTrans Project, the EURECAT, the Technology center of Catalunya and its Multimedia Technologies Unit with the large experience in Computer Vision research and development, the EACOM Company for formal analysis, the NEXIONA Company for the development of the EXO Data server, and Barcelona Drone Center for the care in the facilities use. Finally, we acknowledge the UAV Matrix Company for the UAV Cast tool and the Wirelesslogic Company for the multioperator SIM card testing.  
The authors declare no conflict of interest.