SVM classifiers with an average accuracy of 99% to monitor…
Home / Challenges / Completed Projects / Predicting Climate Change and Forced Displacement in Somalia
Together with the UN Refugee Agency (UNHCR) 34 collaborators built several AI and machine learning based solutions to predict forced displacement, violent conflicts, and climate change in Somalia. In addition, an exploratory data analysis resulted in powerful insights regarding conflict types, areas, and reasons. The findings will help UNHCR to execute necessary support mechanism for people at need in a faster and more effective way.
Millions of people in Somalia are forced to leave their current area of residence or community due to resource shortage and natural disasters like droughts and floods as well as violent conflicts. Our challenge partner, UNHCR, provides assistance and protection for those who are forcibly displaced inside of Somalia. Using the latest AI technology, our community of AI experts and data scientists developed several solutions to predict climate change and forced displacement.
A team of 34 Omdena collaborators developed the following solutions:
Supervised learning SVM classifiers and random forest classifiers with an average accuracy of 99 percent to monitor critical areas of conflict including the type of incidents and impact. The information is used to build a hot zone representation, which predicts the most dangerous locations and the highest fatalities. The machine learning model can help to optimize the allocation of utility personnel to handle incidents.
A report visualizing what type of climate change/ anomalies result in forced displacement and what are the needs of people affected by it.
Graphic: Excerpt from the report showing types of forced displacement resulting from climate change
All articles for this challenge can be found on our blog below.
UNHCR – The UN Refugee Agency
UNHCR is a global organization dedicated to saving lives, protecting rights, and building a better future for refugees, forcibly displaced communities, and stateless people. Our AI and machine learning based technologies will help to make data-driven decisions and act more efficiently and effectively to support people and communities in need.
We are thanking all community collaborators for the amazing work done! AI for Earth! AI for All!
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