Abstract
The clinical mastitis is a harmful disease in cows and many researchers working on milk parameters to detect clinical mastitis. Internet of things (IoT) is a developing era of technology where every object is connected to the Internet using sensors. Sensors are an essential unit of an IoT to collect the data for analysis. The proposed method concentrates on deploying sensors on cows to monitor the health issues and will state IoT as an Internet of Animal Health Things (IoAHT). Dairy cows are an essential unit of the Indian economy because India is a top country in milk production. Clinical mastitis affects dairy cows in the production of milk. Recent studies in the dairy industry proved the use of technologies and sensors for good growth of cows. This paper reviews a method used for detecting clinical mastitis in cows and proposes a system for the same using IoAHT. The KNN and SVM algorithms are used on the primary data set to obtain a result of the detection. In comparison to these algorithms, SVM provided better results in detecting mastitis in cows.
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Ankitha, K., Manjaiah, D.H. (2021). Comparison of KNN and SVM Algorithms to Detect Clinical Mastitis in Cows Using Internet of Animal Health Things. In: Satapathy, S., Zhang, YD., Bhateja, V., Majhi, R. (eds) Intelligent Data Engineering and Analytics. Advances in Intelligent Systems and Computing, vol 1177. Springer, Singapore. https://doi.org/10.1007/978-981-15-5679-1_6
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