AI for Disaster Response: Improving Emergency Management During Cyclones

AI for Disaster Response: Improving Emergency Management During Cyclones

  • The Results
Project finished!

In this Omdena Challenge, you’ll have the chance to collaborate with 40 AI experts and aspiring data scientists from around the world to build an innovative AI-driven logistic prevision model for emergency management in cyclones.


The problem: Quick disaster response

When a disaster strikes, the World Food Programme (WFP), as well as the other humanitarian actors, 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 their experience.

What if we could use past disaster data to help them know what is needed?


The goal

Applying Machine Learning to predict logistics needs after a disaster strikes.

The mission of the WFP Innovation Accelerator is to build the world’s #1 disaster logistic prediction tool for cyclones.

The data is pulled from Humanitarian agency reports and the Humanitarian Data Exchange.


Why you should join the challenge

For the next two months, you will not only build AI solutions to make a real-world impact but also go through an entire data science project lifecycle. This covers problem scoping, data collection and preparation, as well as modeling for potential deployment.

And the best part is that you will be part of a global collaboration.


This project is hosted with our friends at