Sistema de inferência fuzzy para avaliação dos impactos ambientais sobre o aspecto da caminhabilidade

Abstract

This dissertation investigates the applicability of a fuzzy inference system to evaluate environmental impacts on urban walkability in Manaus, Amazonas. The central problem lies in the need for precise methodologies to measure pedestrian infrastructure quality and guide sustainable public policies. The main objective of the study is to develop a fuzzy inference model capable of classifying the level of pedestrian mobility in different city zones, using the walkability indicators (iCam) from the Institute for Transportation and Development Policy (ITDP). The methodology involved the collection of primary and secondary data, the application of walkability indicators in four city zones, and the modeling of the fuzzy system using MATLAB software. The results demonstrated that the developed model is effective in identifying areas with different levels of walkability, contributing to the formulation of public policies aimed at sustainable urban development. It is concluded that the fuzzy inference system is a useful tool for assessing urban walkability and improving the quality of life in cities.