Subject: Precision farming / AI

Comparing the performance of deep learning video-based models and trained veterinarians in cattle pain assessment

Feighelstein M, Tomacheuski RM, Elias G, Shashoua N, van der Linden D, Luna SPL, Zamansky A

Published in 2026

Study showing that artificial intelligence models can recognize pain in cattle with an accuracy comparable to that of experienced veterinarians analysing video footage.

Document Types: Scientific paper

Animal categories: Bovines

Go to document

Invited Review: Precision Livestock Farming Technologies in Swine Intensive Production

Giovanni Buonaiuto, Eleonora Nannoni, Luca Sardi, Simona Belperio, Chris Sanzò, Giovanna Martelli

Published in 2026

Scientific synthesis of the use of precision farming technologies, including the use of sensors, automation, and artificial intelligence, to improve monitoring and management in pig farming. It focuses on technologies to monitor health, optimize feeding, control microclimates, and assess pig welfare. It sets out the benefits and limitations of these technologies for intensive pig farming.

Document Types: Scientific review

Animal categories: Porcines

Go to document

Review: Understanding cattle social behavior in modern penned production systems with AI technology: Are we tracking welfare indicators?

A. Fuentes, S. Han, J. Liu, J. Park, S. Yoon, D.S. Park

Published in 2026

Review stressing the limitations of AI in automatically monitoring cattle behaviors, currently limited to describing actions independent of context. The authors propose an AI framework based on the principles of multimodal data integration, context-aware behavioral modeling, shared behavioral ontologies, human-in-the-loop system design, and explainable AI to improve assessment of animal welfare.

Document Types: Scientific review

Animal categories: Bovines

Go to document

Rethinking Poultry Welfare—Integrating Behavioral Science and Digital Innovations to Improve Animal Well-Being

Suresh Neethirajan

Published in 2026

Review article describing the welfare challenges associated with the intensification of poultry farming and the innovative solutions (behavioral, sensor-based, AI) that have been developed to address them, while emphasizing the need to validate and standardize such novel tools and to develop a sustainable interdisciplinary production pathway. 

Document Types: Scientific review

Animal categories: Poultry

Go to document

Integration of computer vision-based behavioral monitoring and machine learning to enhance precision in health and welfare monitoring systems in pig farming

Eddiemar B. Lagua, Hong-Seok Mun, Md Sharifuzzaman, Md Kamrul Hasan, Ahsan Mehtab, Jin-Gu Kang, Young-Hwa Kim, Chul-Ju Yang

Published in 2026

Study showing that computer vision and machine learning are effective in detecting stress-related behaviors in pigs. The models perform very well (especially in binary), but the precise detection of certain states still needs improvement.

Document Types: Scientific paper

Animal categories: Porcines

Go to document

Precision Livestock Farming for Dairy Sheep: A Literature Review of IoT and Decision-Support Systems for Enhanced Management and Welfare

Mura M.C., Trimasse O., Carcangiu V., Luridiana S.

Published in 2026

Review showing that precision farming technologies have significant potential to improve the monitoring and welfare of dairy ewes, but their adoption continues to be constrained by economic, technical, and ethical factors.

Document Types: Scientific review

Animal categories: Ovines

Go to document

Measuring shade use of dairy cattle at pasture with an on-cow light sensor: a case study

Lydiane Aubé, Bruno Meunier, Romain Lardy

Published in 2026

Study confirming the effectiveness of using a light sensor attached to grazing cows to automatically detect whether they are in the shade or in the sun. The technique works well and allows continuous monitoring of the cows' use of shade.

Document Types: Scientific paper

Animal categories: Bovines

Go to document

Review: Understanding cattle social behavior in modern penned production systems with AI technology: Are we tracking welfare indicators?

A. Fuentes, S. Han, J. Liu, J. Park, S. Yoon, D.S. Park

Published in 2026

Review showing that, while AI systems make it possible to monitor certain cattle behaviors automatically, there are major limitations on their contextual and social interpretation of welfare signals. The authors propose a welfare-centered AI framework, integrating multimodal data and contextual modelling to facilitate early detection of welfare risks and informed decision-making.

Document types: Scientific documents

Animal categories: Bovines

Go to document

Real-Time Behavior Recognition Using a Legged Robot for Animal–Robot Interaction

Edoardo Fazzari, Donato Romano, Fabrizio Falchi, Cesare Stefanini

Published in 2025

Study presenting an AI-integrated framework that enables a robotic dog to autonomously analyze the behavior of cows and chickens in real time using detection (YOLO) and action recognition (DARTEMIS) models.

Document types: Scientific documents

Animal categories:Cattle, Poultry

Go to document

Behavior recognition of tail and ear biting in pigs using AI-based computer vision

Qinghua Guo, Clémence A.E.M. Orsini, Patrick P.J.H. Langenhuizen, Yue Sun, Shoujun Huo, Lisette E. van der Zande, Inonge Reimert, J. Elizabeth Bolhuis, Piter Bijma, Peter H.N. de With

Published in 2026

Study demonstrating the feasibility of video-based automated monitoring of tail and ear biting on commercial farms. A computer vision-based model (MViTv2-S) achieves approximately 72% accuracy without having to rely on detection of specific postures, paving the way for early-warning systems and breeding selection strategies to reduce these harmful behaviors.

Document Types: Scientific paper

Animal categories: Porcines

Go to document