ArticleSensors (Basel, Switzerland)2021
Biometric Physiological Responses from Dairy Cows Measured by Visible Remote Sensing Are Good Predictors of Milk Productivity and Quality through Artificial Intelligence.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 28 citations in OpenAlex.
- Machine Learning-Driven Computer Vision System for Automated Fat and Energy Quantification in Human Milk Microcapillaries.Sensors (Basel, Switzerland) · 2026Article
- An artificial intelligence-based diagnosis system for the identification of helminth parasitic infections in mithun and allied bovines.Scientific reports · 2025Article
- Socializing AI: Integrating Social Network Analysis and Deep Learning for Precision Dairy Cow Monitoring-A Critical Review.Animals : an open access journal from MDPI · 2025Review
- AI and Data Analytics in the Dairy Farms: A Scoping Review.Animals : an open access journal from MDPI · 2025Review
- Remote Vital Sensing in Clinical Veterinary Medicine: A Comprehensive Review of Recent Advances, Accomplishments, Challenges, and Future Perspectives.Animals : an open access journal from MDPI · 2025Review
- Applications of Artificial Intelligence for Heat Stress Management in Ruminant Livestock.Sensors (Basel, Switzerland) · 2024Review
- Health Status Classification for Cows Using Machine Learning and Data Management on AWS Cloud.Animals : an open access journal from MDPI · 2023Article
- Birth of dairy 4.0: Opportunities and challenges in adoption of fourth industrial revolution technologies in the production of milk and its derivatives.Current research in food science · 2023Review
- Livestock Identification Using Deep Learning for Traceability.Sensors (Basel, Switzerland) · 2022Article
- Identification of Factors Affecting Environmental Contamination Represented by Post-Hatching Eggshells of a Common Colonial Waterbird with Usage of Artificial Neural Networks.Sensors (Basel, Switzerland) · 2022Article
- Effect of Packaging and Portioning on the Dynamics of Water-Fat Serum Release from Fresh Pasta Filata Soft Cheese.Foods (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
New and emerging technologies, especially those based on non-invasive video and thermal infrared cameras, can be readily tested on robotic milking facilities. In this research, implemented non-invasive computer vision methods to estimate cow's heart rate, respiration rate, and abrupt movements captured using RGB cameras and machine learning modelling to predict eye temperature, milk production and quality are presented. RGB and infrared thermal videos (IRTV) were acquired from cows using a robotic milking facility. Results from 102 different cows with replicates (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.