COVID-19 Intelligent Monitoring Platform
DOI:
https://doi.org/10.33448/rsd-v11i14.36659Keywords:
Big data; Machine Learning; COVID-19; Data analysis.Abstract
During the COVID-19 pandemic, monitoring platforms for the disease emerged through the analysis and visualization of data. The focus of most platforms was monitoring at the State level, with information concentrated in macro-regions. As a result, cities and municipalities were left without due attention to their internal data, which resulted in difficult decision-making and coping strategies tailored to their local needs. With previous experience in monitoring COVID-19 in the State of Paraná, using public access data, it was possible to identify new types of data and analyzes that could be carried out with specific information for each city or municipality, in order to generate useful information in the context local characteristics, as a way of helping managers in decision making. The platform's ability to analyze and visualize data is directly related to the challenges of establishing a standard for obtaining the most varied types of data found in the internal organizations of Brazilian cities and municipalities. Thus, this work presents a methodology for intelligent monitoring of COVID-19 data, which comprises the steps of obtaining, extracting, cleaning, analyzing and visualizing the data. With data analysis, it was possible to investigate actions and define strategies focusing on local characteristics, generating a platform that was transferred to some municipalities in Paraná in 2021.
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Copyright (c) 2022 Arlete Teresinha Beuren; Hugo José Teixeira de Freitas; Thiago França Naves; Hugo Andrés Ruiz Flórez; Gloria Patrícia López Sepúlveda; Anderson da Silva Soares; Telma Woerle de Lima Soares
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