AI-Powered Big Data Platforms for Enhancing Disaster Management and Emergency Response in Public Administration

Abstract

The increasing frequency and intensity of natural disasters and emergencies, compounded by the unpredictability of climate change and rapid urbanization, have placed unprecedented demands on public administration systems worldwide. Traditional methods of disaster management and emergency response often fall short due to inefficiencies in coordination, delayed decision-making, and inadequate resource allocation. However, advancements in artificial intelligence (AI) and big data platforms are transforming these paradigms. AI-powered big data platforms hold immense potential to improve disaster preparedness, response, and recovery through predictive analytics, real-time data processing, and enhanced decision support systems. These platforms integrate diverse datasets from satellite imagery, social media, Internet of Things (IoT) sensors, and historical records, enabling public administrators to anticipate disasters, optimize resource distribution, and facilitate timely interventions. This paper examines the synergy between AI and big data platforms in enhancing disaster management, focusing on key aspects such as predictive modeling, real-time situational awareness, resource optimization, and communication networks. Furthermore, it explores the challenges of implementation, including data privacy concerns, system integration complexities, and ethical considerations. The discussion underscores the need for robust frameworks and collaborations among governments, private sectors, and research institutions to harness the full potential of AI in public administration for disaster management. By leveraging AI-powered big data platforms, public administration can shift from reactive to proactive approaches, ultimately mitigating disaster impacts, reducing casualties, and enhancing resilience in vulnerable communities.