Your browser doesn't support javascript.
loading
Utilizing 3D Point Cloud Technology with Deep Learning for Automated Measurement and Analysis of Dairy Cows.
Lee, Jae Gu; Lee, Seung Soo; Alam, Mahboob; Lee, Sang Min; Seong, Ha-Seung; Park, Mi Na; Han, Seungkyu; Nguyen, Hoang-Phong; Baek, Min Ki; Phan, Anh Tuan; Dang, Chang Gwon; Nguyen, Duc Toan.
Afiliación
  • Lee JG; National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Chungcheongnam-do, Republic of Korea.
  • Lee SS; National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Chungcheongnam-do, Republic of Korea.
  • Alam M; National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Chungcheongnam-do, Republic of Korea.
  • Lee SM; National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Chungcheongnam-do, Republic of Korea.
  • Seong HS; National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Chungcheongnam-do, Republic of Korea.
  • Park MN; National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Chungcheongnam-do, Republic of Korea.
  • Han S; ZOOTOS Co., Ltd., R&D Center, Anyang 14118, Gyeonggi-do, Republic of Korea.
  • Nguyen HP; ZOOTOS Co., Ltd., R&D Center, Anyang 14118, Gyeonggi-do, Republic of Korea.
  • Baek MK; ZOOTOS Co., Ltd., R&D Center, Anyang 14118, Gyeonggi-do, Republic of Korea.
  • Phan AT; ZOOTOS Co., Ltd., R&D Center, Anyang 14118, Gyeonggi-do, Republic of Korea.
  • Dang CG; National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Chungcheongnam-do, Republic of Korea.
  • Nguyen DT; ZOOTOS Co., Ltd., R&D Center, Anyang 14118, Gyeonggi-do, Republic of Korea.
Sensors (Basel) ; 24(3)2024 Feb 02.
Article en En | MEDLINE | ID: mdl-38339704
ABSTRACT
This paper introduces an approach to the automated measurement and analysis of dairy cows using 3D point cloud technology. The integration of advanced sensing techniques enables the collection of non-intrusive, precise data, facilitating comprehensive monitoring of key parameters related to the health, well-being, and productivity of dairy cows. The proposed system employs 3D imaging sensors to capture detailed information about various parts of dairy cows, generating accurate, high-resolution point clouds. A robust automated algorithm has been developed to process these point clouds and extract relevant metrics such as dairy cow stature height, rump width, rump angle, and front teat length. Based on the measured data combined with expert assessments of dairy cows, the quality indices of dairy cows are automatically evaluated and extracted. By leveraging this technology, dairy farmers can gain real-time insights into the health status of individual cows and the overall herd. Additionally, the automated analysis facilitates efficient management practices and optimizes feeding strategies and resource allocation. The results of field trials and validation studies demonstrate the effectiveness and reliability of the automated 3D point cloud approach in dairy farm environments. The errors between manually measured values of dairy cow height, rump angle, and front teat length, and those calculated by the auto-measurement algorithm were within 0.7 cm, with no observed exceedance of errors in comparison to manual measurements. This research contributes to the burgeoning field of precision livestock farming, offering a technological solution that not only enhances productivity but also aligns with contemporary standards for sustainable and ethical animal husbandry practices.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Nube Computacional / Aprendizaje Profundo Tipo de estudio: Guideline Aspecto: Ethics / Patient_preference Límite: Animals Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Nube Computacional / Aprendizaje Profundo Tipo de estudio: Guideline Aspecto: Ethics / Patient_preference Límite: Animals Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article Pais de publicación: Suiza