Welcome to Smart Agriculture 中文

Smart Agriculture ›› 2022, Vol. 4 ›› Issue (2): 1-18.doi: 10.12133/j.smartag.SA202204005

• Topic--Smart Animal Husbandry Key Technologies and Equipment •     Next Articles

Advances and Challenges in Physiological Parameters Monitoring and Diseases Diagnosing of Dairy Cows Based on Computer Vision

KANG Xi1,2,3(), LIU Gang1,2(), CHU Mengyuan1,2, LI Qian1,2, WANG Yanchao1,2   

  1. 1.Key Lab of Smart Agriculture Systems, Ministry of Education, China Agricultural University, Beijing 100083, China
    2.Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China
    3.School of Computing and Data Engineering, NingboTech University, Ningbo 315200, China
  • Received:2022-04-28 Online:2022-06-30 Published:2022-08-05
  • corresponding author: LIU Gang E-mail:B20183080643@cau.edu.cn;pac@cau.edu.cn


Realizing the construction of intelligent farming by using advanced information technology, thus improving the living welfare of dairy cows and the economic benefits of dairy farms has become an important goal and task in dairy farming research field. Computer vision technology has the advantages of non-contact, stress-free, low cost and high throughput, and has a broad application prospect in animal production. On the basis of describing the importance of computer vision technology in the development of intelligent farming industry, this paper introduced the cutting-edge technology of cow physiological parameters and disease diagnosis based on computer vision, including cow temperature monitoring, body size monitoring, weight measurement, mastitis detection and lameness detection. The introduction coverd the development process of these studies, the current mainstream techniques, and discussed the problems and challenges in the research and application of related technology, aiming at the problem that the current computer vision-based detection methods are susceptible to individual difference and environmental changes. Combined with the development status of farming industry, suggestions on how to improve the universality of computer vision technology in intelligent farming industry, how to improve the accuracy of monitoring cows' physiological parameters and disease diagnosis, and how to reduce the influence of environment on the system were put forward. Future research work should focus on research and developmentof algorithm, make full use of computer vision technology continuous detection and the advantage of large amount of data, to ensure the accuracy of the detection, and improve the function of the system integration and data utilization, expand the computer vision system function. Under the premise that does not affect the ability of the system, to improve the study on the number of function integration and system function and reduce equipment costs.

Key words: dairy farming, computer vision technology, physiological parameters monitoring, diseases diagnosing, precision livestock farming, intelligent farming

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