This review paper provides a comprehensive analysis of optimization strategies for Unmanned Aerial Vehicles (UAVs) in various surveillance tasks and scenarios. It evaluates the multifaceted role of UAVs in critical areas such as infrastructure inspection, security surveillance, environmental monitoring, archaeological research, and mining applications. The paper details 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 addresses the challenges of operating in complex environments. The paper also predicts trends in cooperative UAV surveillance networks and explores the potential of UAVs in more challenging scenarios. It highlights current research gaps and future research directions, aiming to inspire further exploration of UAVs in surveillance missions. UAV path planning; UAV coverage planning; UAV applications; UAV optimization; UAV surveillance; UAV monitoring; aerial video surveillance; review; survey Surveillance tasks are classified based on the type and number of objects to be monitored, as well as the significance of the task. Traditional surveillance methods often struggle with complex environments, leading to the development of UAVs that can operate autonomously and efficiently. Common UAV surveillance tasks include environmental monitoring, search and rescue, agricultural surveillance, target tracking, traffic flow monitoring, infrastructure inspection, etc. UAVs can achieve autonomous single-unit operation or operate in clusters for data sharing and collaborative operations. The surveillance range of a UAV is often correlated with its flight altitude, and multiple UAVs can form a network to enhance mission efficiency. Publicly available data demonstrates the superiority of drones in identifying critical issues compared to traditional methods, highlighting their potential to increase efficiency, reduce costs, and optimize resource use. The paper discusses four main types of surveillance tasks: area security and target tracking, infrastructure retrieval, search and rescue, and environmental and resource surveillance. For each type, the paper analyzes the path planning and deployment strategies adopted to optimize the Path Planning Problem (PPP) and the Coverage Problem (CPP). The optimization objectives include maximizing the number of observed targets, maximizing the quality of surveillance (QoS), and minimizing the cost of surveillance. The paper explores various methods for achieving these objectives, such as path planning algorithms, coverage planning algorithms, and optimization models. It also discusses the limitations of current methods and proposes potential solutions for future research. The paper provides a detailed analysis of UAV surveillance for target tracking, infrastructure inspection, and search and rescue. For target tracking, the focus is on maximizing the number of observed targets, maximizing the quality of surveillance, and minimizing the cost. For infrastructure inspection, the paper discusses the use of UAVs in inspecting transmission lines and bridges, highlighting the advantages of using UAVs over traditional methods. For search and rescue, the paper explores the use of UAVs in emergency response and personnel location, emphasizing their rapid deployment, efficient surveillance, and precise positioning in hard-to-reach areas. The paper also addresses the challenges and future directions in theseThis review paper provides a comprehensive analysis of optimization strategies for Unmanned Aerial Vehicles (UAVs) in various surveillance tasks and scenarios. It evaluates the multifaceted role of UAVs in critical areas such as infrastructure inspection, security surveillance, environmental monitoring, archaeological research, and mining applications. The paper details 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 addresses the challenges of operating in complex environments. The paper also predicts trends in cooperative UAV surveillance networks and explores the potential of UAVs in more challenging scenarios. It highlights current research gaps and future research directions, aiming to inspire further exploration of UAVs in surveillance missions. UAV path planning; UAV coverage planning; UAV applications; UAV optimization; UAV surveillance; UAV monitoring; aerial video surveillance; review; survey Surveillance tasks are classified based on the type and number of objects to be monitored, as well as the significance of the task. Traditional surveillance methods often struggle with complex environments, leading to the development of UAVs that can operate autonomously and efficiently. Common UAV surveillance tasks include environmental monitoring, search and rescue, agricultural surveillance, target tracking, traffic flow monitoring, infrastructure inspection, etc. UAVs can achieve autonomous single-unit operation or operate in clusters for data sharing and collaborative operations. The surveillance range of a UAV is often correlated with its flight altitude, and multiple UAVs can form a network to enhance mission efficiency. Publicly available data demonstrates the superiority of drones in identifying critical issues compared to traditional methods, highlighting their potential to increase efficiency, reduce costs, and optimize resource use. The paper discusses four main types of surveillance tasks: area security and target tracking, infrastructure retrieval, search and rescue, and environmental and resource surveillance. For each type, the paper analyzes the path planning and deployment strategies adopted to optimize the Path Planning Problem (PPP) and the Coverage Problem (CPP). The optimization objectives include maximizing the number of observed targets, maximizing the quality of surveillance (QoS), and minimizing the cost of surveillance. The paper explores various methods for achieving these objectives, such as path planning algorithms, coverage planning algorithms, and optimization models. It also discusses the limitations of current methods and proposes potential solutions for future research. The paper provides a detailed analysis of UAV surveillance for target tracking, infrastructure inspection, and search and rescue. For target tracking, the focus is on maximizing the number of observed targets, maximizing the quality of surveillance, and minimizing the cost. For infrastructure inspection, the paper discusses the use of UAVs in inspecting transmission lines and bridges, highlighting the advantages of using UAVs over traditional methods. For search and rescue, the paper explores the use of UAVs in emergency response and personnel location, emphasizing their rapid deployment, efficient surveillance, and precise positioning in hard-to-reach areas. The paper also addresses the challenges and future directions in these