This review paper explores optimization strategies for Unmanned Aerial Vehicles (UAVs) in various surveillance tasks and scenarios. It provides insights into the role of UAVs in critical areas such as infrastructure inspection, security surveillance, environmental monitoring, archaeological research, mining applications, and more. The paper analyzes the effectiveness of UAVs in specific tasks, including power line and bridge inspections, search and rescue operations, police activities, and environmental monitoring. It focuses on the integration of advanced navigation algorithms and artificial intelligence technologies with UAV surveillance and the challenges of operating in complex environments. The paper predicts trends in cooperative UAV surveillance networks and explores the potential of UAVs in more challenging scenarios. It highlights current research and future directions for UAV surveillance, aiming to inspire further exploration of UAVs in surveillance missions. UAV surveillance tasks include environmental monitoring, search and rescue (SAR), agricultural surveillance, target tracking, traffic flow monitoring, infrastructure inspection, etc. UAVs are equipped with cameras and can perform various surveillance tasks such as environmental monitoring, search and rescue, agricultural surveillance, and urban surveillance for police security. These tasks utilize the unique capabilities of UAVs, such as mobility and flexibility, and often reduce the cost of surveillance. Using sophisticated localization, navigation, data collection, and control algorithms, UAVs can achieve autonomous single-unit operation or operate in the form of a cluster for data sharing and collaborative operations. For surveillance missions, a single UAV can be used to achieve surveillance by designing path-planning algorithms. The surveillance range of a UAV is often correlated with its flight altitude, and even a single UAV can achieve greater coverage through altitude adjustment. For some large-scale missions, it is sometimes difficult for a single UAV to efficiently fulfill the needs of the mission, and this is when the existence of a UAV network is necessary. The use of multiple UAVs to form a UAV network, using information sharing between UAVs, designing optimized allocation or deployment strategies, and planning the corresponding paths, can greatly enhance the efficiency of the mission. The paper discusses different types of surveillance tasks, including area security and target tracking-based surveillance, infrastructure retrieval-based surveillance, search and rescue-based surveillance, and environment and resource surveillance tasks. It analyzes the path planning and deployment strategies adopted by different researchers to optimize and solve the Path Planning Problem (PPP) and the Coverage Problem (CPP) arising from the corresponding surveillance tasks. The paper also discusses the optimization of UAV surveillance for target tracking, focusing on maximizing the number of observed targets, maximizing the quality of surveillance (QoS), and minimizing the cost of surveillance. It explores various algorithms and strategies for these optimization problems, including path planning and coverage planning. The paper highlights the importance of UAVs in infrastructure inspection, such as bridge and transmission line inspections, and discusses the use of advanced technologies like computer vision, LiDAR, and path planning algorithms to improve the efficiency and accuracy of inspections. The paper also discusses the use of UAVs in search and rescue (SAR)This review paper explores optimization strategies for Unmanned Aerial Vehicles (UAVs) in various surveillance tasks and scenarios. It provides insights into the role of UAVs in critical areas such as infrastructure inspection, security surveillance, environmental monitoring, archaeological research, mining applications, and more. The paper analyzes the effectiveness of UAVs in specific tasks, including power line and bridge inspections, search and rescue operations, police activities, and environmental monitoring. It focuses on the integration of advanced navigation algorithms and artificial intelligence technologies with UAV surveillance and the challenges of operating in complex environments. The paper predicts trends in cooperative UAV surveillance networks and explores the potential of UAVs in more challenging scenarios. It highlights current research and future directions for UAV surveillance, aiming to inspire further exploration of UAVs in surveillance missions. UAV surveillance tasks include environmental monitoring, search and rescue (SAR), agricultural surveillance, target tracking, traffic flow monitoring, infrastructure inspection, etc. UAVs are equipped with cameras and can perform various surveillance tasks such as environmental monitoring, search and rescue, agricultural surveillance, and urban surveillance for police security. These tasks utilize the unique capabilities of UAVs, such as mobility and flexibility, and often reduce the cost of surveillance. Using sophisticated localization, navigation, data collection, and control algorithms, UAVs can achieve autonomous single-unit operation or operate in the form of a cluster for data sharing and collaborative operations. For surveillance missions, a single UAV can be used to achieve surveillance by designing path-planning algorithms. The surveillance range of a UAV is often correlated with its flight altitude, and even a single UAV can achieve greater coverage through altitude adjustment. For some large-scale missions, it is sometimes difficult for a single UAV to efficiently fulfill the needs of the mission, and this is when the existence of a UAV network is necessary. The use of multiple UAVs to form a UAV network, using information sharing between UAVs, designing optimized allocation or deployment strategies, and planning the corresponding paths, can greatly enhance the efficiency of the mission. The paper discusses different types of surveillance tasks, including area security and target tracking-based surveillance, infrastructure retrieval-based surveillance, search and rescue-based surveillance, and environment and resource surveillance tasks. It analyzes the path planning and deployment strategies adopted by different researchers to optimize and solve the Path Planning Problem (PPP) and the Coverage Problem (CPP) arising from the corresponding surveillance tasks. The paper also discusses the optimization of UAV surveillance for target tracking, focusing on maximizing the number of observed targets, maximizing the quality of surveillance (QoS), and minimizing the cost of surveillance. It explores various algorithms and strategies for these optimization problems, including path planning and coverage planning. The paper highlights the importance of UAVs in infrastructure inspection, such as bridge and transmission line inspections, and discusses the use of advanced technologies like computer vision, LiDAR, and path planning algorithms to improve the efficiency and accuracy of inspections. The paper also discusses the use of UAVs in search and rescue (SAR)