AI FOR DISASTER PREDICTION AND EARLY WARNING
Keywords:
Artificial Intelligence (AI), Disaster Prediction, Early Warning Systems, Machine Learning, Deep Learning, Disaster Management, Remote Sensing, Internet of Things (IoT), Natural Disasters, Predictive Analytics.Abstract
Global challenges from wildfires and hurricanes to landslides and earthquakes continue to intensify. Current methods for predicting natural disasters have significant shortcomings. AI offers tremendous potential to provide disruptive improvements in predicting and modeling the impacts of natural hazards. The aim of this study is to understand the potential of AI and related technologies in improving disaster risk reduction and management. It will also assess the extent of AI integration in disaster risk prediction and response. The study also identifies and analyzes existing AI-based models for forecasting disasters and assesses the levels of warnings offered by these models. The study assesses challenges including, the ethical quandaries, trade-offs, and the resources required for AI integration. The research further evaluates the role of AI in transforming the trajectory of risk governance. It also assesses the impact of fusing real-time data, cognitive systems and edge computing in disaster risk management.
