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The WFP works to reduce world hunger: https://www.wfp.org/resilience-building The Great Green Wall has already brought food security to over 500k people. |
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The World Food Programme has a data visualizer here: https://dataviz.vam.wfp.org/ |
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This paper "establishes the groundwork for a global, data-driven early warning system designed to anticipate and detect food insecurity". It might be possible to learn which actions to take to avoid food insecurity. Forecasting trends in food security with real time data |
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World Food Programme Food Security OptimizationSimilar to the Covid-19 NPI Optimization use-case, one can forecast food security and make prescriptions for aid based on this forecast. Forecasting has already been done by the WFP as mentioned above using reservoir computing. The paper can be found at: https://doi.org/10.1038/s43247-024-01698-9 and the Github repo can be found at: https://github.com/ducciopiovani/FamPredAI Data
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There could be some interesting information for a project here: |
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AquaCrop Irrigation Strategy OptimizationThe FAO has a simulator called AquaCrop which takes in lots of variables such as weather, crop type, soil type, irrigation strategy, and field management, and then outputs the yield and amount of irrigation used. A python library version can be used as an evaluator for evolution. DataContext
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This FAO project could be interesting: 3 type of players:
Plus a game master. 3 scores:
15 policies to choose from for each player. It may be possible to optimize what players should do / should have done at each turn. |
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Additional resources from the Food and Agriculture Organization of the United Nations (FAO):
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Chat about anything related to Goal 2: End hunger, achieve food security and improved nutrition and promote sustainable agriculture
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