Precision Detection of Real-Time Conditions of Dairy Cows Using an Advanced Artificial Intelligence Hub

Applied Sciences

Seong Ho Choi¹  Hyoung Ki Hong¹  Dong-Hoon Lee²  Ju-Phil Cho³  Jihwan Park⁴  Sun-il Chon⁴  Kim Margarette Corpuz Nogoy⁴  Min-Jeong Park⁴  Saraswathi Sivamani⁴ 

[1] Department of Animal Science, Chungbuk National University, Cheongju City 28644, Korea;Department of Biosystems Engineering, Chungbuk National University, Cheongju City 28644, Korea;School of IT Information and Control Engineering, Kunsan National University, Gunsan City 54150, Korea;ThinkforBL Consultancy Services, Seoul 06236, Korea;

关键词: dairy farming;    precision and accuracy;    data mining;    heat stress;    subclinical mastitis;    artificial intelligence;   

DOI  :  10.3390/app112412043

来源: DOAJ

【 摘 要 】

One of the main challenges in the adoption of artificial intelligence-based tools, such as integrated decision support systems, is the complexities of their application. This study aimed to define the relevant parameters that can be used as indicators for real-time detection of heat stress and subclinical mastitis in dairy cows. Moreover, this study aimed to demonstrate the use of a developed data-mining hub as an artificial intelligence-based tool that integrates the defined relevant information (parameters or traits) in accurately identifying the condition of the cow. A comprehensive theoretical framework of the data-mining hub is demonstrated, the selection of the parameters that were used for the data-mining hub is listed, and the relevance of the traits is discussed. The practical application of the data-mining hub has shown that using 21 parameters instead of 13 and 8 parameters resulted in a high overall accuracy of detecting heat stress and subclinical mastitis in dairy cows with a high precision effect reflecting a low percentage of misclassifying the conditions of the dairy cows. This study has developed an innovative approach in which combined information from different independent data was used to accurately detect the health and wellness status of the dairy cows. It can also be implied that an artificial intelligence-based tool such as the proposed theoretical data-mining hub of dairy cows could maximize the use of continuously generated and underutilized data in farms, thus ultimately simplifying repetitive and difficult decision-making tasks in dairy farming.

【 授权许可】

Unknown