Otimização de rota tecnológica de resíduos sólidos usando redes neurais artificiais: um estudo de caso em Crateús – CE

Abstract

The accelerated growth of urban areas in Brazil has intensified the generation of solid waste, highlighting challenges in the management and adequate supply of these materials. Data from the National Sanitation Information System (SNIS, 2022) highlight the insufficiency of selective collection and the persistence of landfills in several municipalities, aggravating environmental impacts. In this context, the city of Crateús, in Ceará, has already shown advances in waste management, such as collected collection and initiatives by the Consórcio de Manejo Público de Resíduos Sólidos dos Sertões de Crateús (CORSEC). However, technological limitations are still evident. This work proposes the development of an artificial intelligence model based on artificial neural networks (ANN) to trace optimized technological routes for solid waste management in the municipality. Neural networks were used to integrate technical, environmental, and economic dimensions in the planning of collection and destination routes. The methodology applied consists of collecting and analyzing data provided by sources such as the Brazilian Association of Waste and Environment (ABREMA) and the SNIS. The data were processed and compared with a table of previously established parameters, enabling the availability of the ANN model to define the most efficient route to Crateús. The development of the code included steps of normalization, training, and validation of the model, ensuring its applicability to the local context. The results indicated a significant optimization in the planning of results, providing greater operational efficiency, within the indicators analyzed. The application of the model allowed not only the definition of a more strategic trajectory, but also the identification of operational challenges that can be mitigated with logistical adjustments. In addition, an approach based on artificial intelligence proved promising for replication in other municipalities with similar characteristics, contributing to the development of public policies aimed at urban sustainability. Thus, this study reinforces the importance of technology in improving environmental management, highlighting the potential of artificial intelligence as a tool for the modernization and optimization of solid waste collection services. Furthermore, research sought to contribute to urban sustainability and promote innovative public policies in the context of small and medium-sized cities.