Projects / AI Innovation Challenge

Disaster Prediction to Optimize Relief Package Allocation

Project completed!

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A collaborative Omdena team of 34 AI experts and data scientists collaborated with the World Food Programme Innovation Accelerator to build solutions to predict affected populations and create customized relief packages for disaster response.

The complete data analysis and details about the relief package tool, including a live demonstration, can be found in the demo day recording.

The problem

When a disaster strikes, the World Food Programme (WFP), as well as other humanitarian agencies, need to design comprehensive emergency operations. They need to know what to bring and in which quantity. How many shelters? How many tons of food? These needs assessments are conducted by humanitarian experts based on the first information collected, their knowledge, and experience.

The project goal: Building a disaster relief package tool for cyclones (applicable to other use cases and disaster categories)

Tropical Cyclone Amphan infographic

Figure 1: Tropical Cyclone Amphan infographic


The project outcomes

Tropical cyclones cost about 10,000 human lives a year. Many more are injured with homes and buildings destructed, which results in financial damage of several billion USD. Due to changes in climate and extreme weather events, the impact is growing steadily.

The team mapped different correlation factors to determine which populations are most in need. For example, below the income level is correlated with the number of people affected. Taking advantage of past data, the data model predicts affected populations.

Cyclone Pabuk route

Figure 2: Cyclone Pabuk route (Affected countries)

Once an affected population is identified, humanitarian actors need to design comprehensive emergency operations, including how much food and what type of food is required. The project team built a food basket tool, which facilitates calculating the needs of affected populations. The tool looks for various features such as days to be covered, the number of affected people, pregnancies, kids, etc.


AI for cyclone prediction

Figure 3: Relief package tool

The team

The WFP Innovation Accelerator hosted the project and worked with 34 collaborators and changemakers across four continents. All team members worked together for two months on Omdena´s innovation platform to build AI solutions with the mission to improve disaster response.

The complete data analysis and details about the relief package tool, including a live demonstration, can be found in the demo day recording below.

Your benefits

Working with world-class mentors and domain experts to acquire real-world experience

Making international friends in a fast-growing supportive community of collaborators

Boosting your technical skills, problem-solving capabilities, and collaboration skills

Building your personal brand and publishing your own articles on our website and blog

Receiving certificates of participation and references to build a meaningful career


Good English

A good/very good grasp in computer science and/or mathematics

Student, (aspiring) data scientist, AI engineer, data engineer

Programming experience with C/C++, C#, Java, Python, Javascript or similar

Understanding of ML and Deep learning algorithms

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