A crucial sector of India’s agricultural sector and economy is the livestock industry, especially cattle farming. The demand for milk, dairy products, and meat has increased the necessity for advanced methods of managing cattle. This paper explores the application of deep learning (DL) models, especially those incorporating attention mechanisms, for accurate and efficient cattle detection in “smart cattle farming.” The paper focuses on object detection method and attention mechanisms such as self, channel, spatial, and temporal attention, which significantly enhance detection accuracy by focusing on relevant features of the images. The novelty of this study lies in the dataset collected, which focuses on low-light or nighttime conditions. This study utilizes a YOLO model with an integrated attention mechanism, which outperforms other models in overall detection performance. The findings demonstrate how effectively deep learning and attention mechanisms work in improving cattle detection and promoting sustainable livestock management.