## 3 Related Works: An Overview of Wireless Power Transfer
Scheduling the WPT and data collection has become very critical in order to extend the battery life of the sensor-nodes and to reduce the packet loss. Moreover, inadequate scheduling causes some of the nodes to drain their batteries and have their data buffer overflow, while the other nodes waste their harvested energy which could be used for data transmission operations. Therefore, optimizing the scheduling of WPT and data collection is very critical in order to reduce the hardware cost. The use of unmanned aerial vehicles (UAVs) with microwave power transfer (MPT) capability to remotely recharge the batteries of the sensor-devices and harvest their data was studied in [34; 35; 36] as a practical means of deploying a large number of wireless powered sensor-nodes into harsh terrains and inaccessible areas. A large-sized UAV can be equipped with lightweight high-capacity rechargeable batteries and solar panels on top of its wings and can be employed in area of interest to collect data from the sensing devices and recharge their batteries. The paper studied the UAV-assisted MPT and data collection, where the instantaneous patrolling velocity of the UAV is optimized along with online decisions of power transfer and data collection. Authors developed an on-board deep Q-network for online scheduling of MPT and data collection to minimize the overall data packet loss, prevent battery drainage and data queue overflow of the sensing devices. Authors relied on two key limitations of the UAV-assisted MPT technique for their proposed scheme, which included that in practical scenarios, energy harvesting and data transmission could be impaired by the movements of the UAV and time-varying channels [34]. Secondly, information about an up-to-date battery level and data queue length of the ground sensors is not always available to the UAV. The proposed architecture combines the concepts of cyber physical systems (CPS), the embedded systems and data communication systems. The layout is designed to enable autonomous, simultaneous and synergetic operations among the various concepts and features. A fundamental challenge of the proposed data-Mule-WPT scheme is the security of data being transmitted over the cyber network. CPSs are described as smart systems using cyber technologies embedded in and interacting with physical components [37; 38; 39]. The key CPS challenges are discussed in [39] while [37] outlines security measures including forensics, prognostics and recovery plans for the analysis of cyber-attacks. In order to prevent the exploitation of CPS vulnerabilities, authors in [37; 38] propose an anti-malicious and anti-tamper system engineering and the development of unique security solutions that can fill the gap where \(\Pi\) solutions do not apply. The potential security and privacy vulnerabilities and threats of a cordless power transfer technique particularly the Qi wireless charging for mobile devices were studied in [40]. It was posited that an adversary could stealthily position an adversarial coil between the charger and the device being charged, and inject some malicious data to the communication channel. As a result, the adversary can largely reduce the charging efficiency, or directly terminate the power transfer, or increase the amount of power leading to overheating, battery-life reduction or even an explosion. Following the discussions on cyber risks, our proposed model intends to adapt the six-layered security architecture proposed in [38] for cyber-physical systems, motivated by the OSI.