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@article{194934,
        author = {P. Himasiri and K. Keerthana and B.L.V Tejaswini},
        title = {Smart Visual-Based Disease Detection System for Livestock},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {6229-6237},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194934},
        abstract = {Livestock and horses play a crucial role in rural economies by providing food, labor, and financial stability. However, diseases such as Foot and Mouth Disease (FMD) in cattle and skin or eye infections in horses spread rapidly and cause significant losses. Traditional diagnosis methods are time-consuming, costly, and often inaccessible in rural areas. This paper presents a Smart Visual-Based Disease Detection System using a camera interfaced with a DE10-Nano FPGA board and Azure Custom Vision API. The system captures images of animals, analyzes them using cloud-based AI, and provides real-time disease predictions along with precautionary measures via a web interface. The proposed system is affordable, scalable, and user-friendly, making it highly suitable for rural deployment.},
        keywords = {Livestock Disease Detection, FPGA, DE10-Nano, Computer Vision, Azure Custom Vision, Smart Agriculture},
        month = {March},
        }