Preventing Malaria Infections Through Topography and Satellite Image Analysis
Challenge finished! Results will be shared soon.
In this two-month project, a global team of up to 50 changemakers will help reduce the cost of malaria elimination campaigns by ensuring that field workers locate and treat contaminated water bodies. Based on available online satellite images, topography, and ongoing data from the field workers, the team will develop an algorithm to find the areas in which stagnant water bodies (malaria mosquito breeding sites) are likely to exist.
The project goal
The project scope will be around the following key areas:
Risk map of water bodies formation based on topography and satellite imagery
Risk map of water bodies given the location of other water bodies
Risk of scanners missing water bodies based on their route
Integration of the algorithm into the field workers’ mobile app
For this project, field data of water bodies location will be provided
The project falls under the UN´s Sustainable Development Goal 3, which is to “end the epidemics of AIDS, tuberculosis, malaria and neglected tropical diseases” by the year 2030.
Zzapp focuses on technological tools to improve the efficiency of malaria elimination campaigns, so malaria can eventually be eradicated from a region in one shot.
Labelbox solves the problem of taking artificial intelligence and machine learning initiatives from research and development into production. Labelbox's main product is a platform that makes it easy to create and manage labeled data, enabling rapid deployment of artificial intelligence applications.
After only two weeks of setting up the project team, working with such a diverse and motivated group of professionals was a truly unique experience, and it provided insights beyond our expectations. We look forward to collaborating on additional projects in the future!