Data-Driven Disaster Management: Leveraging Big Data Analytics for Preparedness, Response, and Recovery

Abstract

Disasters, both natural and human-induced, continue to pose significant threats to societies worldwide, necessitating innovative approaches to disaster management. This research focuses on the utilization of big data analytics to enhance disaster preparedness, response, and recovery. By synthesizing a wide array of data sources and employing advanced analytical techniques, data-driven strategies have emerged as a promising solution to the challenges posed by disasters. This article provides a comprehensive overview of the research, key findings, and its implications for disaster management stakeholders. Through an extensive literature review, this study establishes the theoretical foundation for data-driven disaster management, outlining the historical context of disaster management and the evolution of big data analytics. The research examines successful applications of data-driven strategies in disaster preparedness, response, and recovery phases, highlighting their transformative impact. Real-world case studies and examples illustrate the effectiveness of data-driven approaches. The key findings of this research indicate that data-driven disaster management significantly improves preparedness through predictive models, enhances response mechanisms through real-time data-driven decision-making, and expedites recovery efforts by optimizing resource allocation. These findings underscore the critical importance of data-driven disaster management in mitigating the impact of disasters on human life, property, and infrastructure. To advance the field, this research calls for continued exploration of emerging technologies and trends, as well as interdisciplinary collaboration among experts in disaster management and data science. It emphasizes the need to address challenges related to data privacy, security, and bias, and advocates for international cooperation in data-sharing to improve disaster response and management on a global scale.