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Cyber surveillance for flood disasters.

Shi-Wei Lo1, Jyh-Horng Wu2, Fang-Pang Lin3

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Summary

This study introduces an automated flood monitoring system using cyber surveillance and image processing. It provides instant alerts for specific river areas, improving disaster prevention accuracy for localized flooding events.

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Area of Science:

  • Environmental Science
  • Remote Sensing
  • Disaster Management

Background:

  • Extreme weather events frequently cause heavy rainfall, leading to devastating floods.
  • Current precipitation forecast systems lack precise, real-time monitoring for individual river sections.
  • Existing methods result in significant casualties and property damage due to inadequate localized flood alerts.

Purpose of the Study:

  • To develop an automated method for real-time flood monitoring in specific areas.
  • To utilize existing cyber surveillance systems for flood detection.
  • To provide instant feedback on flooding and waterlogging events for improved disaster prevention.

Main Methods:

  • Employing remote cyber surveillance systems and image processing techniques.
  • Adapting intrusion detection algorithms to identify flood events as 'invasion objects'.
  • Implementing object detection and verification for floodwaters in river segments and urban areas.

Main Results:

  • Successful automatic flood risk-level monitoring for specific river segments.
  • Enabled automatic urban inundation detection.
  • Demonstrated the system's effectiveness in providing prompt, localized disaster warnings.

Conclusions:

  • The proposed method offers a more practical and effective approach to disaster prevention than large-area forecasting.
  • Advantages include flexible location selection, no need for water-level rulers, and a wide field of view.
  • The system provides accurate and timely references for localized disaster warning actions.