Body weight estimation of yak based on cloud edge computing
Abstract In stock farming, the body size parameters and weight of yaks can reasonably reflect the growth and development characteristics, production performance and genetic characteristics of yaks. However, it is difficult for herders to measure the body size and weight of yaks by traditional manual...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2021-01-01
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| Series: | EURASIP Journal on Wireless Communications and Networking |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13638-020-01879-y |
| _version_ | 1818648951838998528 |
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| author | Yu-an Zhang Zijie Sun Chen Zhang Shujun Yin Wenzhi Wang Rende Song |
| author_facet | Yu-an Zhang Zijie Sun Chen Zhang Shujun Yin Wenzhi Wang Rende Song |
| author_sort | Yu-an Zhang |
| collection | DOAJ |
| description | Abstract In stock farming, the body size parameters and weight of yaks can reasonably reflect the growth and development characteristics, production performance and genetic characteristics of yaks. However, it is difficult for herders to measure the body size and weight of yaks by traditional manual methods. Fortunately, with the development of edge computing, herders can use mobile devices to estimate the yak’s body size and weight. The purpose of this paper is to provide a machine vision-based yak weight estimation method for the edge equipment and establish a yak estimation comprehensive display system based on the user’s use of the edge equipment in order to maximize the convenience of herdsmen’s work. In our method, a set of yak image foreground extraction and measurement point recognition algorithm suitable for edge equipment were developed to obtain yak’s measurement point recognition image, and the ratio between body sizes was transmitted to the cloud server. Then, the body size and weight of yaks were estimated using the data mining method, and the body size estimation data were constantly displayed in the yak estimation comprehensive display system. Twenty-five yaks in different age groups were randomly selected from the herd to perform experiments. The experimental results show that the foreground extraction method can obtain segmentation image with good boundary, and the yak measurement point recognition algorithm has good accuracy and stability. The average error between the estimated values and the actual measured values of body height, oblique length, chest depth, cross height and body weight is 1.95%, 3.11%, 4.91%, 3.35% and 7.79%, respectively. Compared with the traditional manual measurement method, the use of mobile end to estimate the body size and weight of yaks can improve the measurement efficiency, facilitate the herdsmen to breed yaks, reduce the stimulation of manual measurement on yaks and lay a solid foundation for the fine breeding of yaks in Sanjiangyuan region. |
| first_indexed | 2024-12-17T01:26:35Z |
| format | Article |
| id | doaj.art-e3cf2128280346e0835c9dd4b2fdd761 |
| institution | Directory Open Access Journal |
| issn | 1687-1499 |
| language | English |
| last_indexed | 2024-12-17T01:26:35Z |
| publishDate | 2021-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Wireless Communications and Networking |
| spelling | doaj.art-e3cf2128280346e0835c9dd4b2fdd7612022-12-21T22:08:41ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14992021-01-012021112010.1186/s13638-020-01879-yBody weight estimation of yak based on cloud edge computingYu-an Zhang0Zijie Sun1Chen Zhang2Shujun Yin3Wenzhi Wang4Rende Song5Department of Computer Technology and Applications, Qinghai UniversityDepartment of Computer Technology and Applications, Qinghai UniversityDepartment of Computer Technology and Applications, Qinghai UniversityDepartment of Computer Technology and Applications, Qinghai UniversityDepartment of Computer Technology and Applications, Qinghai UniversityCenter for Animal Disease Control and Prevention in Yushu StateAbstract In stock farming, the body size parameters and weight of yaks can reasonably reflect the growth and development characteristics, production performance and genetic characteristics of yaks. However, it is difficult for herders to measure the body size and weight of yaks by traditional manual methods. Fortunately, with the development of edge computing, herders can use mobile devices to estimate the yak’s body size and weight. The purpose of this paper is to provide a machine vision-based yak weight estimation method for the edge equipment and establish a yak estimation comprehensive display system based on the user’s use of the edge equipment in order to maximize the convenience of herdsmen’s work. In our method, a set of yak image foreground extraction and measurement point recognition algorithm suitable for edge equipment were developed to obtain yak’s measurement point recognition image, and the ratio between body sizes was transmitted to the cloud server. Then, the body size and weight of yaks were estimated using the data mining method, and the body size estimation data were constantly displayed in the yak estimation comprehensive display system. Twenty-five yaks in different age groups were randomly selected from the herd to perform experiments. The experimental results show that the foreground extraction method can obtain segmentation image with good boundary, and the yak measurement point recognition algorithm has good accuracy and stability. The average error between the estimated values and the actual measured values of body height, oblique length, chest depth, cross height and body weight is 1.95%, 3.11%, 4.91%, 3.35% and 7.79%, respectively. Compared with the traditional manual measurement method, the use of mobile end to estimate the body size and weight of yaks can improve the measurement efficiency, facilitate the herdsmen to breed yaks, reduce the stimulation of manual measurement on yaks and lay a solid foundation for the fine breeding of yaks in Sanjiangyuan region.https://doi.org/10.1186/s13638-020-01879-yYakThree-river-sourceEdge computing |
| spellingShingle | Yu-an Zhang Zijie Sun Chen Zhang Shujun Yin Wenzhi Wang Rende Song Body weight estimation of yak based on cloud edge computing EURASIP Journal on Wireless Communications and Networking Yak Three-river-source Edge computing |
| title | Body weight estimation of yak based on cloud edge computing |
| title_full | Body weight estimation of yak based on cloud edge computing |
| title_fullStr | Body weight estimation of yak based on cloud edge computing |
| title_full_unstemmed | Body weight estimation of yak based on cloud edge computing |
| title_short | Body weight estimation of yak based on cloud edge computing |
| title_sort | body weight estimation of yak based on cloud edge computing |
| topic | Yak Three-river-source Edge computing |
| url | https://doi.org/10.1186/s13638-020-01879-y |
| work_keys_str_mv | AT yuanzhang bodyweightestimationofyakbasedoncloudedgecomputing AT zijiesun bodyweightestimationofyakbasedoncloudedgecomputing AT chenzhang bodyweightestimationofyakbasedoncloudedgecomputing AT shujunyin bodyweightestimationofyakbasedoncloudedgecomputing AT wenzhiwang bodyweightestimationofyakbasedoncloudedgecomputing AT rendesong bodyweightestimationofyakbasedoncloudedgecomputing |