Exploring the Potential of Machine Learning for Early Cattle Disease Diagnosis

Dairy farming has long been a common occupation in regions where industrial agriculture is not prevalent, such as India. The dairy industry has seen a rise in productivity as a result of dairy farming modernization, but it is still afflicted by various ailments that can affect cow product output, an...

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Bibliographic Details
Published in2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA) pp. 853 - 857
Main Authors R, Gokul Krishna, S, Periyasamy. V, S, Roshan Khan. B, T, Mohan Raj
Format Conference Proceeding
LanguageEnglish
Published IEEE 03.08.2023
Subjects
Agriculture
Animals
Cattle Farming
Cows
Data mining
Deep Learning
IoT
Machine learning
Smart Contract
Temperature measurement
Temperature sensors
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Summary:Dairy farming has long been a common occupation in regions where industrial agriculture is not prevalent, such as India. The dairy industry has seen a rise in productivity as a result of dairy farming modernization, but it is still afflicted by various ailments that can affect cow product output, and poor-quality dairy products not only hamper long-term national economic success. Due to the large number of dairy cattle housed in various dairies, dairy owners and local governments struggle to maintain and monitor their health. A health management method must include continuous monitoring of each cow's health as well as rapid identification and treatment of sick animals. To do this, sensor technology is employed to measure essential animal properties such as heart rate and temperature. This data is then gathered and put into a data mining system, which forecasts any disease-related events. As a result, even routine veterinary exams and animal care may become more expensive. As a result, in this study, the costs of livestock monitoring are avoided.
DOI:10.1109/ICIRCA57980.2023.10220827