Optimization of urban public safety and disaster prevention strategies based on deep learning algorithms

In order to enhance urban public safety and disaster response capabilities, a deep learning based urban safety monitoring system was constructed, and technical analysis and implementation of image acquisition, object detection, and data fusion were carried out. The results indicate that the system can effectively improve the identification accuracy and response speed of security threats, which is of great significance for optimizing the urban emergency management system.