Leveraging AI for Real-time Earthquake Damage Assessment and Efficient Resource Allocation

Local Chapter Singapore Chapter

Coordinated by Singapore ,

Project background.

While the current challenge focuses on addressing earthquakes in Turkey and Syria, I believe there is a pressing need to extend these efforts to Singapore. Although Singapore has a robust infrastructure and disaster preparedness measures, it is susceptible to various natural and man-made disasters. These include tropical storms, flooding, urban fires, and industrial accidents. Leveraging AI and data science can significantly enhance Singapore’s disaster response and recovery capabilities, ultimately safeguarding the lives and well-being of its citizens.

However, I have also seen that our neighboring country, Myanmar, has suffered from these earthquake disasters. The earthquakes that struck Myanmar in recent years have caused significant devastation and loss of life. The impact on infrastructure and communities has been severe. By adapting to the existing challenge faced by this region and developing AI solutions that are tailored to its specific needs, I am thinking of adding Omdena Myanmar Chapter Lead as a Co-Lead. Together, we will surely find a solution that can prevent earthquakes from happening in Southeast Asian countries.

Project plan.

  • Week 1

    – Understand the problem and gathering ways to collect data.

  • Week 2

    – Data Collection: Gather seismic data, weather patterns, satellite imagery, and other relevant information from various sources.
    – Data Preprocessing: Clean and preprocess the collected data to remove noise and handle missing values.

  • Week 3

    – Feature Engineering: Extract meaningful features from the preprocessed data, such as building density, road network connectivity, and population distribution.
    – Model Development: Start developing AI models for real-time situation assessment based on historical earthquake data.

  • Week 4

    – Model Training: Split the preprocessed data into training and validation sets and train the AI models on historical earthquake data.

  • Week 5

    – Show Demo for real time deployment.

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