Risk reduction in transportation systems: A Bibliometric-Based Literature Review on Artificial Intelligence in Disaster Response

This paper presents a comprehensive bibliometric-based literature review on the application of Artificial Intelligence (AI) in disaster response. Disasters, such as earthquakes and extreme weather events, necessitate innovative approaches for effective management and mitigation. Climate change could increase the frequency and severity of extreme weather events. For this reason, AI, with its growing potential for data analysis, prediction, and automation, emerges as a crucial tool in enhancing disaster response strategies. Our review methodically analyzes scholarly articles and publications sourced from the Scopus databases, employing bibliometric techniques to map out the evolution, trends, and focal p oints in this research area. This paper highlights the diversity and depth of AI applications in disaster scenarios. We also identify the key authors, the influential studies, and the emerging themes within this field. A discussion on the main papers in the field presents the more important directions of research and the potential applications of AI in disaster response. Finally, we suggest directions for future research, emphasizing the need for interdisciplinary collaboration and innovation in developing AI-driven solutions for disaster resilience. This review aims to provide a foundational understanding of the current landscape and future prospects of AI in disaster response, serving as a resource for researchers, policymakers, and practitioners in the field.