Integrating AI for Sustainable Disaster Management

Integrating AI for Sustainable Disaster Management, 1st Edition, examines how computational methods strengthen disaster resilience and support catastrophe prevention. The text provides a structural framework for applying artificial intelligence across emergency planning and hazard mitigation. Designed for researchers, civil, structural, and environmental engineers, policymakers, and graduate students in data science and sustainable development, the book outlines technical approaches to environmental risk.

The volume details specific computational tools, including machine learning, deep learning, robotics, and big data analytics. It demonstrates how these technologies enhance risk assessment models, refine early warning systems, and coordinate real-time disaster response protocols during critical events.

Integrating Internet of Things deployment with big data processing, the material shows how automated systems maintain sustainable practices. This integration aligns engineering protocols with global development goals across academic and municipal environments.