AI-Based Strategies for Urban Disaster Emergency Response Management

Dong-Bo Chen （ Shenzhen Technology Institute of Urban Public Safety, Shenzhen, Guangdong, 518023, China;School of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, China ）

Guo-Feng Zhu （ Shenzhen Technology Institute of Urban Public Safety, Shenzhen, Guangdong, 518023, China ）

Ling-Hang Fang （ Shenzhen Technology Institute of Urban Public Safety, Shenzhen, Guangdong, 518023, China ）

Abstract

With the accelerated process of urbanization, urban disasters have become frequent and complex, posing higher demands on existing emergency response management. Traditional strategies for early warning, evacuation, and rescue have exposed numerous shortcomings in practice, necessitating innovation and improvement. The application of advanced technologies such as large language models in urban disaster simulation shows great potential and helps enhance the accuracy and effciency of disaster response. Research on digital twins and decision support technologies for emergency scenarios is emerging as a new research hotspot, promising breakthroughs and solutions for urban disaster emergency response management.

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