Precision Livestock Farming and Biomedical Engineering: Assessing Feed Quality, Animal Health, and Behavior Using Machine Learning for Sensor Data.

Saved in:
Bibliographic Details
Title: Precision Livestock Farming and Biomedical Engineering: Assessing Feed Quality, Animal Health, and Behavior Using Machine Learning for Sensor Data.
Authors: Kiktev N; Department of Automation and Robotic Systems, National University of Life and Environmental Sciences of Ukraine, 15 Heroiv Oborony Str., 03041 Kyiv, Ukraine., Hradoboiev D; Department of Automation and Robotic Systems, National University of Life and Environmental Sciences of Ukraine, 15 Heroiv Oborony Str., 03041 Kyiv, Ukraine., Pravilov M; Department of Automation and Robotic Systems, National University of Life and Environmental Sciences of Ukraine, 15 Heroiv Oborony Str., 03041 Kyiv, Ukraine., Antypov I; Department of Power Systems Engineering, National University of Life and Environmental Sciences of Ukraine, 15 Heroiv Oborony Str., 03041 Kyiv, Ukraine., Meish Y; Department of Higher and Applied Mathematics, National University of Life and Environmental Sciences of Ukraine, 15 Heroiv Oborony Str., 03041 Kyiv, Ukraine., Stroianovska L; Department of Animal Hygiene and Veterinary Support of the Cynological Service of the National Police of Ukraine, Higher Educational Institution 'Podillia State University', 32-300 Kamianets-Podilskyi, Ukraine., Kielbasa P; Department of Machine Operation, Ergonomics and Production Processes, Faculty of Production and Power Engineering, University of Agriculture in Krakow, Balicka 116B, 30-149 Krakow, Poland., Hutsol T; Department of Machine Operation, Ergonomics and Production Processes, Faculty of Production and Power Engineering, University of Agriculture in Krakow, Balicka 116B, 30-149 Krakow, Poland.; Ukrainian University in Europe-Foundation, Balicka 116, 30-149 Krakow, Poland.
Source: Sensors (Basel, Switzerland) [Sensors (Basel)] 2026 Jun 24; Vol. 26 (13). Date of Electronic Publication: 2026 Jun 24.
Publication Type: Journal Article; Review
Journal Info: Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1424-8220
DOI:10.3390/s26134015