Future-proof your disaster management strategy with this essential, multidisciplinary guide that shows how cutting-edge AI technologies can be practically integrated to enhance early warning systems, save lives, and build long-term community resilience. By bridging the fields of AI, engineering, and sustainable development, this book offers a comprehensive, multidisciplinary approach to disaster management. It provides valuable insights for researchers, practitioners, and policymakers on how to integrate AI to improve decision-making, enhance infrastructure design, and promote long-term sustainability. This book explores the transformative role of artificial intelligence in enhancing disaster resilience and promoting sustainable disaster management practices. The book delves into cutting-edge AI technologies, such as machine learning, deep learning, robotics, and big data analytics, showcasing their potential to improve risk assessment, early warning systems, and real-time disaster response. It focuses on practical applications for mitigating natural hazards like earthquakes, cyclones, and mass movements, providing real-world case studies and successes that demonstrate how AI can save lives, reduce economic loss, and strengthen community resilience. The practical examples and forward-looking perspectives explored in this book make it a crucial resource for anyone working to mitigate the impacts of natural disasters and build a more resilient, sustainable future. Readers will find the volume: Explores how artificial intelligence enhances risk assessment, early warning systems, and realtime disaster response; Provides practical insights through detailed examples of AI applications in earthquakes, cyclones, and mass movement management; Demonstrates how AI can support sustainable practices and align with global development goals to build resilient communities; Provides comprehensive coverage, combining expertise from AI, engineering, sustainability development, and disaster management practitioners; Introduces the latest AI techniques, including IoT, big data, deep learning, and robotics, for effective disaster prevention and recovery. Audience Researchers, civil, structural, and environmental engineers, policymakers, and graduate students involved in disaster management, sustainable development, AI, and data science.
