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Monitoring and Prediction System of the Nutritional and Food Security in the Central america Dry Corridor based on GIS and Artificial Intelligence

In this project we have worked to strengthen the information management system of food safety and nutrition (SGI-SAN) in the Central america Dry Corridor to anticipate potential humanitarian crisis, identify priority territories to be attended and transfer the capacities to public institutions, universities and NGOs in Central America for the analysis of information, prediction of humanitarian needs and disclosure evidences about the situation.

We have built a repository by way of Data Warehouse with monthly updates using secondary sources, remote sensing data from remote sensors and primary monitoring data. For obtaining the data, we have implemented methodologies such as Self-Organizing Maps (SOM), Predictive Models of Decision Trees using Machine Learning, Agroclimátic Analysis and Sample Designs, all displayed on a digital platform with a web interface operated by Power BI.