Enhancing Cattle Farming Management: A Case Study from Uruguay

As livestock farming in Uruguay grows, technologies become necessary for increased efficiency of cattle farms. This paper explores the use of the DeepSORT tracking technique combined with the YOLO NAS model for cattle monitoring on a case study. The unique challenges presented by livestock applications requires robust tracking solutions. The lack of public datasets further complicates these efforts, highlighting the need for curated data tailored to the specific conditions of livestock farming. Through this work, we aim to develop and validate an MOT-based solution that can reliably monitor cattle, thereby enhancing farm management and productivity. This study also underscores the importance of ongoing data curation and the integration of advanced models within embedded platforms to support this crucial sector effectively.