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

Local Chapter Singapore Chapter

Coordinated bySingapore ,

Myat Kaung Kaung

Status: Ongoing

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.

The problem.

“Real-time situation assessment for efficient resource allocation” will be project title. It will use AI to assess the extent of damage during an earthquake, identify areas in urgent need of assistance, and optimize the allocation of the resource for effective relief efforts. We will have the steps normally data collection, data processing, model development, model training, real-time monitoring if possible.

Project goals.

So far I can think of it is that real-time situation assessment, efficient resource allocation, and improved disaster response. We can develop AI models and a real-time monitoring system that can rapidly access the extent of damage during earthquake events in Myanmar and the goal is to provide immediate and accurate information on the severity and distribution of damage. For efficient resource allocation, we can utilize the real time assessment from AI models to optimize the allocation of resources and aid during earthquake disasters. The aim is to prioritize the areas in urgent need and ensure that resources are directed to the most affected regions efficiently.

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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