Research on elastic governance strategy of urban public safety based on entropy weighted discrete clustering method

Abstract

Currently, there are problems in the governance of urban public safety, such as a single entity, outdated governance concepts, and immature governance technologies. This article combines big data analysis technology and utilizes intelligent emergency mechanisms to conduct in-depth research on governance strategies to enhance the resilience of urban public safety to disasters. This article first integrates big data analysis technologies, such as the Internet of Things and cloud computing, into UPS (urban public safety) and then builds a UPS system based on this. Combining the entropy-weighted dispersion clustering method, evaluate the values of urban public safety indicators. In order to verify the effectiveness of the intelligent emergency mechanism based on big data analysis, this article conducted experimental analysis on it. Under the intelligent emergency mechanism algorithm, the average seismic compliance rate of buildings in various cities has reached 88.57%. The conclusion indicates that an intelligent emergency mechanism based on big data analysis can enhance the adaptability of urban public safety governance strategies, improve the seismic and fire warning monitoring capabilities of urban buildings, reduce the occurrence of traffic accidents, and provide more guarantees for urban fire safety.