Construction and Path of Urban Public Safety Governance and Crisis Management Optimization Model Integrating Artificial Intelligence Technology

Abstract

As urbanization and population growth continue to accelerate in China, maintaining public safety and crisis management has become increasingly complex. To address this issue, this research article proposes a new model for optimizing urban public safety governance and crisis management by integrating artificial intelligence (AI) technology with a focus on sustainability. This study aims to explore the construction and path of an urban public safety governance and crisis management optimization model integrating artificial intelligence (AI) technology in China. We developed a linear regression model to examine the relationship between public safety technologies and outcomes, with public safety outcomes (PSO) as the dependent variable and public safety governance structure (PSGS), AI-driven data collection and analysis (AIDC&A), crisis prediction and early warning system (CPEWS), AI-assisted decision-making (AIADM), and public safety response mechanisms (PSRM) as independent variables. The model summary revealed that the independent variables accounted for a moderate proportion of the variance in public safety outcomes, with an R² value of 0.5 and an adjusted R² value of 0.45. The results supported the hypothesis that the integration of different public safety technologies has a positive impact on public safety outcomes. The effective governance structure, AI-driven data collection and analysis, crisis prediction and early warning system, AI-assisted decision-making, and efficient public safety response mechanisms were all found to be crucial for enhancing public safety outcomes. The proposed model was validated through a case study in a Chinese city, with feedback from stakeholders confirming its effectiveness. Overall, the findings suggest that the urban public safety governance and crisis management optimization model integrating AI technology can significantly improve public safety management in urban areas.

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