The utilization of unmanned aerial vehicle (UAV) intelligent vision technology for intelligent analysis and early warning during armed police patrol and duty tasks has become imperative. This paper offers a thorough review of the latest advancements in UAV inspection technology. It delineates the strengths and limitations of pertinent algorithms in accordance with the operational requirements of the armed police force. Emphasizing the intricacies of UAV image characteristics, including complex backgrounds, wide fields of view, diminutive objects, and rotating objects, this paper synthesizes recent research endeavors in UAV object detection. Additionally, it identifies pressing challenges in the deployment of UAV object detection within the operational contexts of the armed police force, thereby furnishing a theoretical underpinning for subsequent endeavors aimed at enhancing the intelligence of associated information systems within the armed police force.
In the current cloud-native usage scenario, the default algorithm is single. When the cluster resources are insufficient, the service guarantee is generally achieved by the expansion of the cluster, and preemptive scheduling cannot be achieved during the scheduling process. Therefore, the original strategy cannot guarantee the operation of important services. Cloud video system provides video conference, online education, video office and other services. Cloud video consists of different pods like Nginx, MySQL, Tomcat, etc. This article sets pod priorities by dividing the categories of Cloud video Pods. Aiming at resource-constrained scenarios, the Preemptive resource scheduling strategy based on Cloud video Pod priority is proposed, and cluster experiments are carried out. Experiments show that the algorithm can effectively guarantee the operation of pods with high priority.
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