This book begins by interpreting the nature of disasters, clearly distinguishing between natural and man-made hazards. It delves into the intricacies of disaster risk reduction (DRR), emphasizing the human contribution to most disasters. Recognizing the necessity for a multifaceted approach, the book advocates the four ‘R’s - Risk Mitigation, Response Readiness, Response Execution, and Recovery - as integral components of comprehensive disaster management.

This book explores various AI and ML applications designed to predict, manage, and mitigate the impact of natural disasters, focusing on natural language processing, and early warning systems. The contrast between weak AI, simulating human intelligence for specific tasks, and strong AI, capable of autonomous problem-solving, is thoroughly examined in the context of disaster management. Its chapters systematically address critical issues, including real-world data handling, challenges related to data accessibility, completeness, security, privacy, and ethical considerations

Coverage:
The many academic areas covered in this publication include, but are not limited to:
•Artificial Intelligence
•Data Challenges
•Deep Learning
•Disaster Management
•Disaster Recovery
•Disaster Response Execution
•Disaster Response Readiness
•Disaster Risk Mitigation
•Early Warning Systems
•Earthquake Forecasting
•Emergency Decision Making
•Ethical Issues in AI
•IoT-Based Systems
•Machine Learning
•Natural Hazards
•Predictive Modeling
•Seismic Attacks