The use of artificial intelligence in the instrumentalization of disaster classifiers

Abstract

Disasters are events that claim thousands of lives, increasing in both quantity and intensity. For this reason, work that assists in understanding disasters has the potential to save lives and assist in best practices in policy planning aimed at reducing disaster risks. Thus, the research aimed to group disasters by classes using artificial intelligence considering the variables selected in the platform  of the integrated disaster information system [S2ID] of the municipalities of Rio de Janeiro. To implement the algorithm, the work was structured in four sections, in which the first was contextualized, a brief problematization of the absence of disaster classifiers using artificial intelligence in the Brazilian system, followed by the second section, in which the materials and methods implemented in the research were presented. Then the results were presented and discussed in the third section and we concluded with the final considerations in the fourth section. At the end of the research we were able to create classes of disasters from quantitative variables that can help in understanding the intensity of disasters and allow the Civil Defense, the agency responsible for disaster risk reduction management, to develop better strategies in its activities.

DOI:https://doi.org/10.56238/Connexpemultidisdevolpfut-008