Título: Computer Vision And Artificial Intelligence For The Verification Of Standard Operating Procedures In Beef Carcasses In The Meat Industry
Autores: Angelo Polizel Neto, Elton Fernandes dos Santos, João Pedro Lanzarini Lopes, Guilherme Roberto Matos Silva, Cecylyana Leite Cavalcante, Evelyn Prestes Brito, Marçal Henrique Moreira, Julio Cesar Machado Alvares, Emerson Amaral Santos, Priscila Dias da Silva & Rafael Sarto Zaratin
Resumo: The adoption of technologies based on Artificial Intelligence (AI) and Computer Vision has significantly expanded the possibilities for automation and quality control in the meatpacking industry. This study presents the development and application of an intelligent system for the automated verification of Standard Operating Procedures (SOPs) in beef carcasses, specifically targeting the visual assessment of compliance regarding the presence of the Matambrinho muscle cut post-slaughter. The methodology involves the use of computer vision models trained to recognize specific visual patterns required by quality standards, enabling rapid and accurate detection of non-conformities that directly impact profitability and economic losses. The system was validated in a controlled environment using real images of beef carcasses, demonstrating satisfactory accuracy in identifying deviations from the SOP. Automated verification contributes to process standardization, reduction of human errors, increased traceability, and greater efficiency across the beef production chain. The results indicate that integrating AI into SOP monitoring is a promising strategy to raise quality standards, detect potential non-compliant practices, and reduce operational losses in the meat industry.
Palavras-chave: Computational Intelligence; Convolutional Neural Networks; Quality.
Páginas: 7
Código DOI: 10.21528/CBIC2025-1191627
Artigo em PDF: CBIC_2025_paper1191627.pdf
Arquivo BibTeX:
CBIC_2025_1191627.bib