CLASSIFICATION OF AREAS FOR SOCIAL HOUSING USING FUZZY LOGIC: A CASE STUDY FOR THE SOROCABA REGION

• Grant number: 25/14232-8
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: September 01, 2025
• End date: August 31, 2026
• Field of knowledge: Physical Sciences and Mathematics - Mathematics - Applied Mathematics
• Principal Investigator: José Arnaldo Frutuoso Roveda
• Grantee: Emily Akiye Furlan
• Host Institution: Instituto de Ciência e Tecnologia. Universidade Estadual Paulista (UNESP). Campus de Sorocaba. Sorocaba , SP, Brazil
• Associated research grant: 24/01128-5 - Science Center for the Development of Social Housing in the State of São Paulo "CCD HIS SP", AP.CCD

Abstract

This project aims to classify the Special Zones of Social Interest (ZEIS) in the municipality of Sorocaba, established by Municipal Law No. 12,759/2023, based on technical criteria related to urban infrastructure, using fuzzy inference systems. ZEIS are areas demarcated to promote the implementation of Social Interest Housing (HIS), aiming to guarantee adequate housing for low-income populations. However, to provide a clearer picture of their effectiveness and to enable the government to optimize their use, mechanisms capable of evaluating and classifying these zones in a careful and standardized manner are essential. In this context, the application of fuzzy logic emerges as an innovative and effective tool to aid in the decision-making process, with the ability to address imprecise and subjective variables, such as the quality of the areas' layout, proximity to essential public services (such as schools, daycare centers, and primary care units), and the available land area. The fuzzy system to be developed will follow the Mamdani framework, consisting of fuzzification, rule base, inference, and defuzzification stages, using MATLAB software for implementation and testing. Ultimately, the aim is to obtain an objective classification of the ZEIS, or ranking, according to their suitability for receiving affordable housing projects, contributing to urban planning and combating socio-spatial segregation. In addition to expanding the student's technical training in computational tools applied to environmental engineering, the research will also support a master's project under development along the same thematic line, reinforcing the importance of interdisciplinarity in building more inclusive cities. (AU)