Artificial Intelligence for Emergency Response: Developing a Real-time Decision Support System for Disaster Management

Author(s)	Mr. Ronak Goyal, Mrs. Ashwini Somani
Country	India
Abstract	This study investigates the impact of AI-based Decision Support Systems (AI_DSS) and Real-Time Predictive Analytics (RT_PA) on Emergency Response Quality (ERQ) during disaster scenarios. A structured survey was administered to 291 households in New York, aiming to assess how emerging technologies influence the effectiveness and efficiency of emergency responses. The data, analyzed using both SPSS and R Studio, revealed a strong, statistically significant relationship between the use of AI and predictive analytics and improved ERQ outcomes. The regression model (Adjusted R² = 0.629) confirms that AI_DSS and RT_PA significantly contribute to better decision-making, faster response times, and optimized resource allocation during crises. These findings highlight the managerial and strategic value of integrating intelligent systems into disaster response operations, particularly in urban settings like the United States. The study provides actionable insights for policymakers, emergency services, and urban planners in adopting technology-driven emergency management frameworks.
Keywords	Emergency Response, AI Decision Support Systems, Predictive Analytics, Disaster Management
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 1, January-February 2026
Published On	2026-02-24
DOI	https://doi.org/10.36948/ijfmr.2026.v08i01.69102

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