# UAV-Enabled Mobile Edge-Computing for IoT Based on AI: A Comprehensive Review
## 2 UAV System Model
### UAV Applications
Their versatility also allows obtaining a quick overview of the rescue situation instead of using human-crewed airplanes that may take extra time to deploy [58]. Relying on UAV-enabled MEC, AI, and CV schemes could lead to new applications that simulate visual reality, thus enabling faster and real-time decisions in emergency interventions. For instance, UAVs typically detect obstacles by flying over them, gathering data, extracting the most prominent features, and making decisions based on machine vision and pattern recognition technologies. In this manner, people with visual impairments can maneuver comfortably. This technology is expected to be a key solution in the healthcare revolution [58]. * Smart cities and smart homes:  
The urban environment is expected to acquire a massive number of dynamically connected devices due to diverse activities wherein UAVs as mobile vehicles will have many pivotal roles, including real-time traffic control [59], transportation [60], infrastructure control and management [61], and buildings observation [62]. Accordingly, UAVs are expected to provide communication services to heterogeneous smart devices in urban areas, to improve the smart city from application perspectives [63]. For example, the authors of [64] have proposed an architecture for 5G hierarchical IoT networks where the UAVs play a fundamental role as a data fusion center, formation controller, and network gateway. In another context, UAVs were used to perform lightweight parts delivery to workstation operators within a manufacturing plant, where GPS could not provide a practical solution for indoor positioning, in addition to intelligent shipping, intelligent monitoring, and intelligent control [65]. * Natural disaster tracking:  
During natural disasters, a rapid and effective response is required to assist the population, avoid increasing the number of victims, and minimize the economic impact. UAVs can respond quickly to earthquake help requests, find missing people, and facilitate the monitoring and rescue of victims in danger of drowning during floods [66; 67]. Collecting a large amount of data from different sensors deployed in the environment, using UAV-enabled MEC with AI algorithms, can help to rapidly predict and intervene in natural disasters such as tornadoes, volcanic eruptions, tsunamis, and storms. * Construction:  
UAV-enabled MEC and computer vision techniques are promising solutions for the condition assessment of civilian and public infrastructures. UAVs are being used increasingly in many construction tasks, such as building inspections [68], building condition monitoring, damage assessments of buildings after disasters [69], public site surveying and mapping [70], safety inspections of construction sites and workers, and monitoring the progress of construction [71]. \begin{table}
\begin{tabular}{l l l l l l} \hline \hline
**Application Domains** & **Objectives** & **Pos/Cons** & **Future Insights** & **Ref. ** \\ \hline  & & & & \(\checkmark\) Multi-UAV integration & \\  & & & & \(\checkmark\) Difficult to fly in harsh conditions & \\  & & & & \(\checkmark\) Energy efficiency & \\  & & & & \(\checkmark\) UAV-based autonomous decisions & \\  & & & & \(\checkmark\) Autonomous decision-making based on DL & \\  & & & & \(\checkmark\) Short-ramp coverage of BLE-enabled UAVs & \\  & & & & \(\checkmark\) Energy uncertainty & (100 m) & \\  & & & & \(\checkmark\) Discrete and prediction of various & \\  & & & & \(\checkmark\) Energy uncertainty & \\ Agriculture/Precision agriculture & & & & \(\checkmark\) Energy changes & \\  & & & & \(\checkmark\) Energy changes &  
* Wireless and cellular networks:  
Many efforts have been dedicated to harnessing the full potential of UAV communications for cellular and wireless communications in the networks industry. The research community explored the opportunity of UAV-mounted utilization via flying relays and BSs that can dynamically reposition themselves to boost network coverage, increase spectral efficiency, and improve user QoS.