# Networked Unmanned Aerial Vehicles for Surveillance and Monitoring: A Survey
## 2 General Target Surveillance
### Optimization Objectives  
From the optimization point of view, the literature on the deployment of surveillance UAVs can be divided into four categories according to the optimization objectives considered. Figure 4: Summary and taxonomy of previous studies on UAV surveillance for general targets. Figure 3: Surveillance UAV applications categorized by the target of interest. **Minimizing UAV number:** The authors of [16; 17] studied the minimization of the number of UAVs for surveillance tasks. In detail, the authors of [17] investigated the deployment of a group of UAVs for surveillance and monitoring of a ground region, with the goal of minimizing the number of UAVs to observe every point of the region with ground-facing cameras. To solve this problem, the authors of [17] developed an easily implementable algorithm based on [PERSON]'s theorem from combinatorial geometry. The results are proven to be asymptotically optimal in the sense that the number of UAVs deployed is close to the minimum number of UAVs for large ground regions. Different from [17], the authors of [16] considered the scenario of monitoring a very uneven terrain. Specifically, UAVs are to be deployed over a very uneven terrain area with the goal of covering every point of the area. The authors in [16] viewed the problem as a UAV version of the 3D Art Gallery Problem. A computationally simple algorithm was proposed to calculate an upper estimate of the minimal number of UAVs necessary. The proposed algorithm also gives the locations of the UAVs. The limitation of [16] is that the considered terrain model are simple polyhedrons, while real uneven terrains can be much more complicated with many irregular structures. The authors of [18] formulated a set cover problem to find the 3D positions of UAVs, with the objective of minimizing the UAV number such that all of the sensor nodes monitored can operate without a time limitation. **Maximizing the number of covered targets:** The authors of [19; 20] provided some formulations for the deployment of a single UAV by assuming the availability of target locations. In particular, the authors of [19] presented an energy-efficient deployment approach for covering the largest number of targets. This approach first finds the vertical position of the UAV at an altitude, providing the maximal coverage, and then optimizes the UAV's horizontal position to maximize the number of covered targets while minimizing the transmission power. To maximize the number of targets served, Reference [20] formulated a mixed-integer nonlinear problem involving both the horizontal coordinates and the altitude as variables rather than decoupling the deployment. The case of multiple UAVs has also been investigated under the assumption of that the locations of the targets are known [21]. UAVs are used to serve the greatest number of targets possible, provided that each UAV has a service capacity. **Maximizing the quality of coverage:** Reference [22] focused on deploying a network of UAVs to surveil and monitor a set of static ground targets. To characterize the quality of coverage of targets using surveillance UAVs, the authors in [22] proposed a novel coverage model and further presented a reactive collision-free three-dimensional deployment algorithm to maximize the overall quality of coverage of targets by a group of surveillance UAVs. In particular, the proposed algorithm consisted of two control laws for horizontal submovement and vertical submovement of the UAVs in real-time. The authors analyzed the computational complexity and proved the convergence of the algorithm. The authors of [23] considered the deployment problem for a group of UAVs to maximize the quality of coverage of an area for surveillance. The authors proposed a distributed optimization model and coverage-maximizing algorithm to find the locations of the UAVs. The proposed optimization model considered the constraint that a connected communication graph needs to be maintained between the UAVs and some ground nodes.