A Survey on Early Cattle Diagnostic Techniques

Abstract

Dairy cattle's well-being is the rancher's riches. One of the huge dangers to dairy ranchers is cow infections. Assume the illnesses are not distinguished at the right time some other time when the infection turns into a persistent stage. The treatment cost will be more, and further, the monetary expense caused to the rancher is irreversible as the dairy cattle may not give the yield it was offering before, even after getting mended. The thought is to recognize the steers’ illnesses in the beginning phase so the rancher can take the treatment measures immediately. The study is centred on applying machine learning to automatically detect haemoprotozoan illness in cattle. By combining cutting-edge technology in data analysis, the project seeks to produce a reliable system that uses sophisticated algorithms for accurate and effective diagnosis. Improvements in early detection capabilities lead to better management of cattle health and increased output in agriculture.