Affiliation:
1. Sreenidhi Institute of Science and Technology, India
Abstract
The transformational field of utilizing machine learning (ML) and artificial intelligence (AI) to forecast natural disasters is explored in this book chapter. The severity of natural disasters demands catastrophe mitigation, risk assessment, and early warning. The use of AI and ML technologies, which have the potential to safeguard communities, is essential in this endeavor. The chapter emphasizes the need of a multidisciplinary strategy that combines domain expertise with AI and ML to improve capacity to predict and respond to natural disasters with an ultimate goal to build a more secure and resilient global community. The chapter examines a number of AI and ML applications in disaster prediction, including forecasts for earthquakes, floods, wildfires, hurricanes, landslides, tsunamis etc. In order to increase prediction accuracy, it covers sensor networks, data sources, and the integration of various datasets. Additionally, it tackles the issues related to ethical considerations, robustness of the model, and data quality.