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Building Resilience and Preventing Catastrophes
Louise Reader
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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:
Audience
Researchers, civil, structural, and environmental engineers, policymakers, and graduate students involved in disaster management, sustainable development, AI, and data science.
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