Desenvolvimento de um sistema de monitoramento inteligente para determinação do ponto ótimo para o abate de animais de produção utilizando visão computacional e inteligência artificia

Abstract

Beef cattle production faces challenges in accurately identifying the ideal slaughter time for Nelore cattle, affecting yield and animal welfare. Traditional monitoring methods, such as manual weighing and visual inspection, may compromise meat quality and increase costs. This study developed an intelligent monitoring system using computer vision and artificial intelligence to determine the optimal slaughter moment for Nelore cattle. The system applies deep learning algorithms and video cameras to analyze animals in real time, considering productive and morphological parameters. A cost-benefit analysis was performed based on hardware, software, and operational returns. Results showed increased productivity, improved slaughter precision, and an estimated 268.42% ROI over five years, demonstrating the technical and economic feasibility of AI-based livestock monitoring.