Urban flood disaster prevention, control, and rescue using edge computing and the resilience concept

Area of Science:

• Environmental Science
• Computer Science
• Disaster Management

Background:

• Increasing frequency of urban rain and flood disasters necessitates improved disaster relief strategies.
• Existing urban flood control systems require enhancement to address complex disaster scenarios.
• Integrating resilience concepts with advanced computing is crucial for effective disaster governance.

Purpose of the Study:

• To develop an urban flood disaster system integrating evolutionary resilience, systems theory, and synergetic theory.
• To explore the application of edge computing and unmanned aerial vehicles (UAVs) in flood disaster monitoring and response.
• To establish an effective prevention, control, and governance mechanism for urban flood disasters.

Main Methods:

• Constructed an urban flood disaster system model based on evolutionary resilience, systems theory, and synergetic theory.
• Simulated three-dimensional deployment and resource scheduling of edge computing-enabled UAV clusters.
• Analyzed network performance tuning and deployment impacts using UAVs and intelligent edge devices.

Main Results:

• The resilience-based disaster prevention system significantly improved urban flood warning, dispatching, and emergency platforms.
• Edge computing-enabled UAVs provided enhanced flood information and computing resources for ground rescue.
• The system demonstrated effective statistics of people via mobile terminals and provided operational guidance.

Conclusions:

• The proposed system effectively enhances urban flood warning and response capabilities through intelligent technical means.
• Intelligent edge devices like UAVs are vital for flexible information gathering and parallel computing in disaster relief.
• The integration of resilience concepts and edge computing offers a robust framework for future urban flood disaster management.