Design and Implementation of a Public Emergency Management System

In recent years, with the continuous development of economic globalization and social diversification, and the increasing frequency of extreme climates, public events have shown a significant upward trend. Establishing a scientific and rational disaster monitoring, warning, and emergency management system that can identify disaster risks in real time and accurately predict disaster impacts has become a core issue for social stability and development. This paper designs a multifunctional public emergency management system that integrates resource management, training and drills, and science popularization and education. Based on a process framework of three stages—risk identification, decision-response, and risk disposal, and combined with big data and artificial intelligence technologies, it realizes the full-process management of public events. Taking the 2024 Super Typhoon "Mojie" as an example, we utilized web crawling technology to obtain relevant data from Sina Weibo. Through word cloud visualization, we analyzed the public's focus and dynamic changes in their attention regarding the disaster event, providing robust data support for emergency management decision-making. In addition, the paper explores the development direction of integrated natural disaster monitoring and warning from aspects such as classified monitoring of natural disasters, graded warning, warning information release and response, and the informatization of monitoring and warning projects, offering intelligent solutions for the scientific response to public events.