Assessing the Impact of Desert Locust through Machine Learning
Kenya Red Cross Society is the leading humanitarian agency and the strongest humanitarian brand in Kenya. 50 technology changemakers are leveraging satellite and drone imagery for assessing the impact of desert locust in various regions.
The problem
Already, 3.1 million people in arid and semi-arid areas of Kenya are food insecure, and increased breeding of desert locusts, coupled with a recent flooding as well as Covid-19 pandemic, poses a wider risk of food and pasture shortage.
Regionally, Ethiopia, Kenya, Somalia, South Sudan, Sudan, and Uganda host 25.3 million people facing high levels of acute food insecurity, which is 28% of the case-load of Africa. Of these, more than 11 million people in Ethiopia, Kenya, and Somalia are located in areas currently affected by the desert locust infestations.
The following is a short sequence, recorded in Kenya in May 2020, which shows the scale of the problem.
Requirements
Good English
A good/very good grasp in computer science and/or mathematics
Student, (aspiring) data scientist, (senior) ML engineer, data engineer, or domain expert (no need for AI expertise)
Programming experience with C/C++, C#, Java, Python, Javascript or similar
Understanding of ML and Deep learning algorithms
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