The platform works with Machine Learning analyzing demographic data and data collected from the disease, aiming to classify the areas of cities by intensity of contagion.
The possibility of using data analysis to predict contamination outbreaks, contributing to rapid applications of public health policies to save lives. The approach was to implement Machine Learning to process data and make correlations. Nasa data as a grid in Brazil was used to work with urban and rural areas. The project used for the back-end: python + google colab and for the front-end: react, yarn, node, github and languages as java script JSX, json, sass, git. No hardware and software was used: visual code.The biggest problem was the time and achievements as teamwork with different people made it possible to acquire new knowledge.