Disaster Prediction Using Artificial Intelligence

Wiley-Scrivener, 2026

At the intersection of artificial intelligence and disaster management, this essential guide delivers cutting-edge techniques and real-world case studies to help harness AI for faster, life-saving predictions, real-time monitoring, and optimized emergency response. The frequency and severity of natural hazards are continuously growing as a result of climate change, population growth, urbanization, and environmental degradation. Effective disaster risk management is a critical component for achieving sustainable development. Artificial intelligence and machine learning have the potential to greatly improve disaster management by utilizing predictive analytics, enabling real-time monitoring, and facilitating effective resource distribution. These technologies assist in anticipating disasters, delivering timely alerts, and streamlining response initiatives. AI can predict, prepare for, and respond to crises with speed and accuracy. This book provides a comprehensive overview of emerging techniques in this vital industry. It discusses different aspects, including hazard mapping, real-time event detection and monitoring, and the prediction of extreme events using AI and machine learning. Real-world case studies demonstrate the role of AI in disaster management, including resource allocation, emergency-service coordination, and logistics optimization. This volume is an essential guide for professionals, researchers, and students, providing a thorough understanding of how artificial intelligence is revolutionizing disaster management, from preparedness and prediction to response and recovery.

• Curatore: Sanjay Kumar, Chander Prakash, Himanshu Sharma, Disha Thakur
• Anno edizione: 2026
• Editore: Wiley-Scrivener
• Formato: EPUB3 con Adobe DRM
• Lingua: Inglese
• Compatibilità: Tutti i dispositivi (eccetto Kindle)
• Layout: Reflowable
• EAN: 9781394386512