Enhancing Real-Time Emergency Response With Artificial Intelligence: Algorithms For Faster Decision- Making And Resource Allocation

Abstract

Rapid and effective response systems are necessary for emergencies including pandemics, natural catastrophes, and cyber-attacks. In these kinds of scenarios, artificial intelligence (AI) has become a game-changing tool that helps with real-time decision-making and maximizes resource allocation. With an emphasis on machine learning algorithms, neural networks, and optimization techniques, this study investigates how AI might be incorporated into emergency response systems to enhance cyber security defenses, disaster management, and healthcare responses. The study analyzes current AI-driven models, evaluates their efficacy, and suggests a framework for future developments in AI emergency systems using a qualitative research methodology. The results show that AI greatly improves resource management and decision-making, which improves readiness, flexibility, and recovery results in emergency situations. Together with discussing potential future avenues for this field of study, the report also highlights ethical and practical issues related to the application of AI in crisis management.