# Performance of Sensor Data Process Offloading on 5G-Enabled UAVs
## 4 Conclusions  
This article examined the capabilities and the limitations of a 5G-UAV serving as a sensing platform. Additionally, the behavior of a 5G-UAV was evaluated in three scenarios: (1) the transmitted data for the corresponding process offloading remains well within the limits of the 5G uplink capacity, (2) the 5G-UAV offloaded sensor data exceeded the cell's uplink capabilities, and (3) the 5G-UAV was operating an autonomous mission while experiencing significant competing traffic in the same cell. In the first case, the measured latency exhibits robust bounded values and the corresponding application can be reliably served. For the second case, it is evident that a combination of raw sensor data that includes lidars and cameras with too high throughput requirements is not possible to transmit. Applications that rely on the full use of such data for offloading purposes are difficult to serve in a similar  
Figure 11: A 5G-UAV’s trajectory when offloading sensors from competing agents or competing 5G-UAVs.  
architecture. Nonetheless, even if it was possible to transmit that amount of data from a single 5G-UAV sensing platform, this would yield significant scaling concerns. For example, an unofficial report from Intel predicts that in the near future, autonomous vehicles, which serve as sensing platforms and share common characteristics with 5G-UAV sensing platforms, would produce approximately 4000 gigabytes per day [24]. However, it is observed that the combination of the essential sensors often required to manifest an autonomous mission is possible. Modern data compression techniques and intelligent offloading requests enable the possibility of offloading most of the 5G-UAV's senses to be externally processed. This observation is essential for future innovation, where cellular networks can make applications such as power line inspection, wide-area surveillance, wide-area search and rescue, and others possible while utilizing the existing infrastructure.  
Finally, it is essential to note that the operation of a 5G-UAV should be studied and designed as a whole. Many important factors distinguish 5G-UAVs from other traditional UEs. For example, high mobility is an important fact that describes a 5G-UAV, but it could also affect its communication capabilities when served by the cellular network as channel quality varies when the UAV moves between base stations. Additionally, cellular networks such as 5G can provide feedback, helping 5G-UAVs maintain a particular application performance. One characteristic example would be using 5G QoS (data flow prioritization) to prioritize CNPC data over payload data, thus ensuring the reliable transmission of CNPC data.  
Conceptualization, G.D., T.L. and G.N.; methodology, G.D.; software, G.D.; validation, G.D., T.L. and S.S.; formal analysis, G.D. and S.S.; investigation, G.D.; resources, G.N.; data curation, G.D.; writing--original draft preparation, G.D.; writing--review and editing, G.D., S.S., T.L., and G.N.; visualization, G.D.; supervision, T.L., S.S., and G.N.; project administration, G.N.; funding acquisition, G.N. All authors have read and agreed to the published version of the manuscript.  
This work has been partially funded by the European Union's Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie grant Agreement No. 953454.  
Not applicable.  
The authors declare no conflict of interest.