## 9 Conclusions  
The article proposed a 6G-envisioned UAV scheme where basic avoidance operations to tackle COVID-19 and future pandemics are discussed. A 3 FFs mechanism (social distancing, sanitizing, and inspection and monitoring) of COVID-19-infected patients is presented. The proposed scheme frames a layered architecture, where the governance layer presents the guidelines for 3 FFs monitoring through UAVs (to minimize human intervention) against the backdrop of the 6G communication layer. 6G allows real-time monitoring and information transfer between entities. Finally, to track 3 FFs violations, social distance monitoring and thermal inspection through the YOLOv3 and the MEDICAS thermal imaging system are considered. For mass sanitization, hexacopter and octocopter drones with high load-carrying capacities are considered. The computations take into account the data-centric computations at UAVs, and thus the FL-based computational offloading process is presented at the edge network. We considered the use case where a person might be located in a non-stationary FoR, and discussed how geo-fencing is possible to impose the 3 FFs norms. In the simulation, performance metrics in terms of network parameters, computational offloading, and FL setup is considered. In network characteristics, the scheme is compared against traditional 5G-assisted UAV channels, and the presented results indicate the effectiveness of 6G-assisted UAVs in meeting 3 FFs operations. To realize the benefits of edge computation, a comparative analysis of cloud, edge, and local UAV computation is proposed. A significant improvement of 778 ms is recorded in executing tasks on edge rather than the cloud, for a task size of 100 MB. Next, the energy dissipation is measured, and the edge records an improvement of 19.59% over cloud execution. Finally, the open issues and research challenges in deploying the proposed scheme are presented, with potential solutions..  
In the future, to address security and privacy issues of exchanged data of infected patients in different tagged zones, a decentralized UAV model over the blockchain network will be explored to facilitate trust, immutability, and traceability of transactions.  
Conceptualization: R.G., A.T., P.B. and S.T.; writing--original draft preparation: R.G., M.S.R., F.-E.T. and P.B.; methodology: P.B., F.A., A.T. and S.T.; writing--review and editing: S.T., M.S.R., A.T. and R.S.; Software: P.B., R.S., R.G. and S.T.; Visualization: F.-E.T., F.A., M.S.R. and R.S.; Investigation: P.B., R.S., F.A. and S.T. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the Researchers Supporting Project No. (RSP2022R509) King Saud University, Riyadh, Saudi Arabia.  
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This work was funded by the Researchers Supporting Project No. (RSP2022R509) King Saud University, Riyadh, Saudi Arabia. Also, this work is also supported by a grant from the Gheorghe Asachi Technical University of Iasi: postdoctoral research--2022 and POCU--IrouHbDoc. The results were obtained with the support of the Ministry of Investments and European Projects through the Human Capital Sectoral Operational Program 2014-2020, Contract no. 62461/03.06.2022, SMIS code 153735. This work is supported by Ministry of Research, Innovation, Digitization from Romania by the National Plan of R & D, Project PN 19 11, Subprogram 1.1. Institutional performance-Projects to finance excellence in RDI, Contract No. 19 PFE/30.12.2021 and a grant of the NationalCenter for Hydrogen and Fuel Cells (CNHPC)--Installations and Special Objectives of National In-terest (IOSIN). This paper was partially supported by UEFISCDI Romania and MCI through BEIA projects ArtiPred, ALPHA, NGI-UAV-AGRO, Inno4 Health, AICOM4 Health, SmarTravel, Mad@Work and by European Union's Horizon 2020 research and innovation program under grant agreements No. 101073982 (MOBILISE) and No. 883441 (STAMINA).  
The authors declare no conflict of interest.