Integrating AI for Sustainable Disaster Management
eBook - ePub

Integrating AI for Sustainable Disaster Management

Building Resilience and Preventing Catastrophes

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Integrating AI for Sustainable Disaster Management

Building Resilience and Preventing Catastrophes

About this book

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.

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Yes, you can access Integrating AI for Sustainable Disaster Management by Palanichamy Naveen,R. Maheswar,K. Mohanasundaram,T. Rajasekaran,S. Arivazhagan,Rajasekaran Thangaraj in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Table of Contents
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Preface
  7. 1 Introduction to Sustainable Development and Disaster Management
  8. 2 Earthquake Risk Assessment Using Artificial Intelligence ā€“ A Review on Traditional Methods and Artificial Intelligenceā€“Based Methods
  9. 3 AI Applications in Earthquake Resistance Using Change in Structural Design
  10. 4 Automatic Detection of Tropical Cyclones from Satellite Images Using YOLO Models
  11. 5 Intelligent Transportation Systems in Cyclone-Prone Areas: A Study and Future Perspectives
  12. 6 AI-Enhanced Risk Assessment and Mitigation for Mass Movements
  13. 7 Distributed AI Systems for Disaster Response and Recovery
  14. 8 Intelligent Reasoning and Decisionā€‘Making in Disaster Scenarios
  15. 9 AI Applications in Real-Time Intelligent Automation
  16. 10 Knowledge Management and Processing in Disaster Management
  17. 11 Perception Technologies for Disaster Situations
  18. 12 Integration of AI and Software Engineering for Disaster Management: A Multimodal Disaster Identification Perspective
  19. 13 An Intelligent AI-Based Fault Detection Mechanism for Autonomous Vehicles with Blockchain Security
  20. 14 Industrial Experiences in Crop Cultivation Using AI for Disaster Management
  21. 15 A Comprehensive Review on Robotics in Disaster Response and Recovery
  22. Index
  23. End User License Agreement