Progress of Machine Vision Technologies in Intelligent Dairy Farming

Author:

Zhang Yongan1ORCID,Zhang Qian2,Zhang Lina3,Li Jia1,Li Meian1,Liu Yanqiu1,Shi Yanyu1

Affiliation:

1. College of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China

2. Department of Biosystems Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada

3. College of Physics and Electronic Information, Inner Mongolia Normal University, Hohhot 010022, China

Abstract

The large-scale and precise intelligent breeding mode for dairy cows is the main direction for the development of the dairy industry. Machine vision has become an important technological means for the intelligent breeding of dairy cows due to its non-invasive, low-cost, and multi-behavior recognition capabilities. This review summarizes the recent application of machine vision technology, machine learning, and deep learning in the main behavior recognition of dairy cows. The authors summarized identity recognition technology based on facial features, muzzle prints, and body features of dairy cows; motion behavior recognition technology such as lying, standing, walking, drinking, eating, rumination, estrus; and the recognition of common diseases such as lameness and mastitis. Based on current research results, machine vision technology will become one of the important technological means for the intelligent breeding of dairy cows. Finally, the author also summarized the advantages of this technology in intelligent dairy farming, as well as the problems and challenges faced in the next development.

Funder

Special Fund for Basic Scientific Research of Inner Mongolia Agricultural University

National Natural Science Foundation of China project

Natural Science Foundation of Inner Mongolia of China

China Scholarship Council

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference62 articles.

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