Future smart cities can benefit from the flexible and affordable service delivery made possible by unmanned aerial vehicles (UAVs) or drones. However, because of limited onboard battery capacity, UAV applications typically experience severe flight time constraints, necessitating regular battery recharge or replacement while carrying out persistent missions. A potential remedy for this problem is the use of wireless mobile chargers, such as automobiles equipped with wireless charging technology for on-demand self-recharging. In order to promote on-demand, secure, and effective UAV recharging services, we give a thorough analysis of vehicle-assisted wireless rechargeable UAV networks (VWUNs) in this article. The market share of wireless charging worldwide in 2020 was USD 4.47 billion. By 2030, it is expected to grow by a CAGR of 22.73 per cent, reaching USD 34.65 billion.
In particular, we first go over the advantages and disadvantages of implementing VWUNs and examine cutting-edge solutions in this area. Then, based on differential privacy, we suggest a safe and privacy-preserving VWUN framework for UAVs and ground vehicles (DP). Within this framework, a two-phase DP algorithm is created to protect the participants’ private bid and energy trading information, as well as an online double auction process for the best charging schedule. The suggested architecture can successfully improve charging efficiency and security, according to experimental results.
There are basically two main challenges that are required to be solved in UAVs & their possible solutions:
1) On-demand and fast UAV recharging
The application of Intelligent Flying Resources in the field of Situ MIMO-WPT Recharging
Due to their dependency on the onboard battery, unmanned aerial vehicles (UAVs), which are utilized in civilian applications like emergency medical deliveries, precision agriculture, wireless communication supply, etc., face the difficulty of having a restricted flight period. Therefore, increasing the effectiveness of in-situ power transfer methods to recharge UAV batteries has the potential to increase the duration of their missions. To send wireless power to receiver UAVs (rUAVs) in a mission, the researchers are undertaking a thorough study on the far-field wireless power transfer (WPT) technology using specialized transmitter UAVs (tUAVs) integrated with MIMO or Multiple Input Multiple Output antennas. To maximize energy transfer gain, the tUAVs or Nano drones can fly and change the distance between them and the rUAVs.Mechanical alignment enables the use of high gain antennas to increase MIMO gain. A 90 per cent efficiency cap was used on the RF gain to simulate mutual coupling, a non-ideal implementation of MIMO. Additionally, the receiver’s RF to DC conversion efficiency shows how much of the wireless energy received can be transformed into energy that the rUAVs can use. In this work, we generally take an 80 per cent constant RF to DC efficiency.
By focusing the energy beam on the rUAVs, MIMO antenna utilization improves energy reception even more. With an increasing number of tUAVs and rUAVs with varying degrees of energy consumption and residual power, their dynamic operating environment becomes more complex. To maximize the energy transfer benefit, we suggest an intelligent trajectory selection approach for tUAVs is entirely based on a deep reinforcement learning model that is called as Proximal Policy Optimization (PPO). The simulation findings show that for a set of realistic transmit power, distance, sub-band number, and antenna numbers. The PPO-based system achieves an approximately tenfold increase in flight time.
2) Highly efficient scheduling of UGVs & UAVs
Energy Efficient Scheduling of UAVs for the purpose of Premises Sterilization
Many public and commercial institutions are required to restart their operations subject to assuring a proper sterilization of their premises, despite the severity of the second wave of the novel coronavirus disease (COVID-19) and the current promise for vaccine roll-outs.
The flying time and payload carrying capacity of the current off-the-shelf drones for this type of environment sanitization are both constrained. In order to reduce the energy used by drones with ultraviolet-C band (UV-C) panels, a 360-degree investigation was conducted. The scientists then proposed a randomized path selection algorithm, the efficiency of which is further enhanced by a UV-C drone-based sterilization (UV-CDS) scheduling technique based on a genetic algorithm. The effectiveness of UV-CDS in terms of sub-optimal performance and significantly quicker execution time in comparison to the other approaches is clearly demonstrated by the performance evaluation carried out through comprehensive computer-based simulations.
From the above-mentioned factors, it can clearly be elucidated that the mobile wireless rechargeable UAV networks consist of some of the most daunting challenges that can be tackled effectively by the adoption of some suitable technologies mentioned above.
