## 2 Target Detection Prototypes and Their Related Metrics and Crucial Issues
### Metrics  
In the recent years, various researchers concentrated on the miscellaneous features of UAVs for target detection, which include cost, safety, privacy, etc. A few dominant metrics are shown in Figure 5 and reviewed below. Figure 4: Average comparison of target detection based on UAVs and traditional vision. 1. _Power Consumption:_ For UAVs, it is difficult to detect small targets under different weather conditions due to the restricted battery ability. Although it is not possible to extend the size of the battery because doing this will extend the mass of the UAVs which is one more critical consideration. Many research reviews have described the battery demand for the UAVs through the wireless power transfer (WPT) approach [37, 38]. Through an expressive connection of WPT, the charging of UAVs can be performed to increase the flight time and dimension for the target inspection, observation, and other surveillance assignments. Moreover, it can also overcome the many restrictions of the current inspection approaches, for instance, costly tasks and dangerous functions. In [39], the researchers charged the battery of the drone and carried out the testing of presented schemes for various distances and unbalanced cartography with the help of magnetic resonance coupling WPT. Besides this, machine learning and DL algorithms for drones also provide a better solution in terms of energy consumption for data collection and processing in compute-hungry realms [40]. 2. _Security and Privacy:_ Security and privacy are important key factors while detecting targets through UAVs. This is because sometimes the attackers liberate all the accumulated information of UAVs through scareware, viruses, and keystrokes with the help of computer streaming-assigned software. Hacking all the data will lead to false detection of traffic congestion, convey corrupt statistics which misguide the ground command stations, and may be used in illegal activities, for instance, using the stolen data against military action. To save the system from such kind of hacking and lay out the correct information about the required recipient, a model was presented named \"Privacy by Design\" in [41] which provides a solution for security and privacy violations. Recently, blockchain, machine learning, DL, and watermarking have performed an important role to secure UAV applications. These approaches aim to supply reliable, safe, and accurate information and secure programmatically updated facts. Further details of these approaches are presented in the research article [42]. 3. _Cost:_ To identify the targets, it is compulsory to develop low-cost UAV detectors. Light mass and low cost are the features of UAVs to ratify the quality inspection with extreme temporal and multidimensional resolutions without endangering the lives of humans. In the recent years, traditional approaches have been used to detect the targets through UAVs, but traditional approaches such as scale-invariant feature transform features [43] have some drawbacks such as high computational cost, bulky deployment, and unpredictable risks and cannot identify the targets in real-time scenarios. In contrast to traditional approaches, DL approaches, such as R-FCN [44], have considerable computational cost and meet real-time demands. However, there is a requirement to better stabilize the dummy complexity and perception reliability and to validate the dummy with unified data from multiple sources [45]. 4. _Resource Employment:_ For humans, it is exhausting for the crew to find the targets only from aerial graphics which consumes extensive human resources and time. The technology of intelligent automatic target recognition and monitoring can empower UAVs to become more competent in rescue, tragedy response, stuff transportation, target crushing, enemy research, and other tasks, which can tremendously decrease the consumption of mankind's resources and additionally stimulate the evolution  
Figure 5: Metrics of target detection through UAVs. of the UAVs' domain.