AI in Disaster Management: Early Warning System Predictive Modeling

Abstract

Artificial intelligence (AI) is revolutionizing early warning systems in disaster management by making disaster prediction models more accurate and timely. Artificial intelligence (AI) has several applications in disaster prediction, including machine learning, deep learning, and data fusion. Social media, weather predictions, sensor networks, and satellite images are just a few of the sources that these techniques pull from. By analyzing trends and patterns, artificial intelligence models can improve the prediction of natural disasters such as hurricanes, earthquakes, wildfires, and floods. This enables proactive reaction activities, which in turn minimizes the risk of casualties and property damage. For the purpose of disaster prediction and real-time warning systems, we evaluate various prediction models, such as sequential data RNNs and image-based CNNs. This study provides valuable insights on the most effective approaches to incorporate AI into disaster management by exploring topics such as data quality, computer resources, and model interpretability. the ground-breaking potential of artificial intelligence to enhance the preparedness and resilience of disaster-prone regions thru the implementation of reliable and efficient early warning systems.