# UAV-Enabled Mobile Edge-Computing for IoT Based on AI: A Comprehensive Review
## 2 UAV System Model
### UAVs Classification  
Deploying a UAV network (known as swarms in IoT contexts) is becoming a practical and necessary requirement for many applications. Various UAVs are currently available on the market, with distinctive features such as supportable altitude, speed, and battery autonomy, for multiple applications. Generally, the selection of any UAV model should fulfill many of the criteria of the targeted application, such as QoS, energy capacity, environmental restrictions, and federal rules [18]. There are three types of UAVs: low-altitude platforms (LAPs), high-altitude platforms (HAPs), and satellites. Since this work focuses on UAV-enabled MEC, UAVs are described based on many aspects. Figure 1 categorizes UAVs into the LAPs category based on their type, size, range, and type of rotors. Figure 2 shows the shape and form of three kinds of commercialized UAVs: a rotary-wing drone (Figure 1(a)), a fixed-wing drone (Figure 1(b)), and a fixed wing hybrid VTOL UAV (Figure 1(c)). Typically, UAVs present unique characteristics, being dynamic, agile, easy to repair, easy to deploy, and offering the potential to provide various measurements wherever and whenever required. They provide a low-cost alternative for collecting and providing information to intelligent systems that can undertake the necessary data analysis (e.g.,  
Figure 1: Classification of LAP UAVs. Figure 2: Examples of several types of UAV: (**a**) rotary-wing drone, (**b**) fixed-wing drone, (**c**) fixed-wind hybrid vertical take-off and landing (VTOL) drone (modified from [19]). real-time image or video analysis). UAVs will substantially promote the progress of farming, defense, insurance inspection, law enforcement, emergency assistance, pollution monitoring, disaster recovery, and package delivery. The data are collected remotely through controllable devices installed on UAVs, each triggered via the platform. The collected data are processed locally onboard the UAVs or are offloaded to cloud servers, based on the required power. Deploying a practical UAV-based IoT framework requires an orchestrator platform that recognizes various contextual information about UAVs, such as flight trajectories, IoT equipment, and battery status. Two main UAV communication networks exist: ad hoc UAV networks and UAV-assisted aided communication networks. The former is characterized by a flexible topology and self-organized architecture, while the latter's main feature comprises flexible scheduling at the edge side of the network. UAVs can collect data massively by being equipped with sensors of different sizes, forms, features, and capabilities. Many remote sensing devices for airborne and satellite platforms are now adopting miniature and low-cost versions for UAV platforms, such as multispectral, hyperspectral, short/medium-wave range cameras (e.g., thermal imaging camera), and light LiDAR. Table 1 gives a list of the sensors and cameras integrated with UAVs and their usefulness for monitoring various applications. The characteristics and specifications of each type differ according to specifications. For example, the RGB camera can be helpful for visual analysis, mapping and classifying objects and tracking animals and people. Moreover, UAVs with lightweight thermal infra-red sensors can deal with complex natural tracking such as monitoring volcanoes and forest fires, tracking animals, and in hydrothermal scientific studies.