AI for Disaster Risk Management: Integrating Traditional Knowledge of Natural Disaster Prediction

Abstract: Natural disasters, ranging from earthquakes to floods, pose significant challenges to vulnerable regions worldwide. Traditional knowledge systems, often deeply rooted in local cultures, have historically provided valuable insights into predicting such events. In the modern era, Artificial Intelligence (AI) is emerging as a powerful tool in disaster risk management, offering potential solutions for early warning systems, resource allocation, and post-disaster recovery. This paper investigates the integration of traditional knowledge with AI for disaster risk management, focusing on the development of predictive models, leveraging data sources such as meteorological records, satellite imagery, and indigenous wisdom. By combining machine learning algorithms with time-tested traditional techniques, we explore how AI can enhance disaster preparedness, resilience, and mitigation efforts in disaster-prone areas. This study highlights the importance of a hybrid approach, which combines scientific advancements with cultural practices, to create a more effective disaster response system.