(2025-02-10) Silva, Vitor Arlinson Rodrigues da; Pereira, Micila Sumária Medeiros; http://lattes.cnpq.br/7877913821937987; Santos, Alyson de Jesus dos; http://lattes.cnpq.br/5998752909180697; Fialho, Edevaldo Albuquerque; http://lattes.cnpq.br/1681351413618686; Santos, Renan Cavalcante; http://lattes.cnpq.br/6930748017205035
This work proposes the study of methods that seek to unite concepts from society 5.0 and industry 4.0 to be used in favor of sustainability. With the increase in the production of plastic waste around the world and its low recycling rate, there was a need to reduce the impact on the ecosystem. The methodology used was applied, explanatory research with a technological design. As a result, three methods were developed for recognizing recyclable waste. Finally, the method selected used a convolutional neural network to create and train a classifier for a machine, powered by plastic and metal lids. The aim of this system is to promote sustainability and reduce the amount of recyclable materials disposed of inappropriately in the environment. Therefore, this work aims to develop low-cost sorters and select the best one to be used in an machine powered by recyclable waste.
