Conférences et ateliers

Vasseur, Elsa; Diallo, Abdoulaye Baniré

Responsible Development and Deployment of AI and IoT in the Dairy Industry, bridging gaps between research and implementation: The WELL-E Initiative [External] Présentation

Innbruck, Austria, 01.08.2025.

Résumé | Liens | BibTeX | Étiquettes: conférencier invité, Presentation

@misc{vasseur_responsible_2025,

title = {Responsible Development and Deployment of AI and IoT in the Dairy Industry, bridging gaps between research and implementation: The WELL-E Initiative},

author = {Elsa Vasseur and Abdoulaye Baniré Diallo},

url = {https://eaap2025.org/},

year  = {2025},

date = {2025-08-01},

urldate = {2025-08-01},

address = {Innbruck, Austria},

abstract = {Responsible AI that properly addresses real-world stakeholder needs is at the heart of the R+I Chair in Animal Welfare and Artificial Intelligence. WELL-E approach relies on the use of IoT, computer vision, and machine learning to improve our ability to detect and monitor changes in animal welfare earlier than possible with visual methods, and to generate predictions to aid on-farm decision-making, ensuring that resources and efforts are focused on the animals most likely to succeed in the long term. Grounded in industry partnerships, members of the dairy community sit on both the scientific and management committees, where they contribute to research orientations, leading to the co-creation of research projects and initiatives. This collaborative approach not only ensures the applicability and relevance of all research carried out, but allows for continuous feedback between the research and industry environments, creating a true digital living lab that can grow with the Chair. Launched in 2023, our team has been conducting pilot research on two research farms and working to build functional and resilient data collection infrastructure for implementation on commercial dairy farms throughout 2025. Through a federated learning approach, this deployment ensures robust continuous monitoring across a network of farms, while respecting data confidentiality and cybersecurity. We have developed a framework for the study of animal behaviours and emotions, presenting a paradigm shift for both annotation and data analysis based on continuouscand heterogeneous data sources. As we grow our network of partner farms, we will continue focussed studies on research farms, allowing for continuous exchange between the two contexts. This collaborative approach promotes the responsible integration of new technologies to the industry and empowers endusers to be at the forefront of these new developments, ensuring their sustainability and reinforcing the importance of stakeholder participation in innovative scientific research.},

keywords = {conférencier invité, Presentation},

pubstate = {published},

tppubtype = {presentation}

}

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Responsible AI that properly addresses real-world stakeholder needs is at the heart of the R+I Chair in Animal Welfare and Artificial Intelligence. WELL-E approach relies on the use of IoT, computer vision, and machine learning to improve our ability to detect and monitor changes in animal welfare earlier than possible with visual methods, and to generate predictions to aid on-farm decision-making, ensuring that resources and efforts are focused on the animals most likely to succeed in the long term. Grounded in industry partnerships, members of the dairy community sit on both the scientific and management committees, where they contribute to research orientations, leading to the co-creation of research projects and initiatives. This collaborative approach not only ensures the applicability and relevance of all research carried out, but allows for continuous feedback between the research and industry environments, creating a true digital living lab that can grow with the Chair. Launched in 2023, our team has been conducting pilot research on two research farms and working to build functional and resilient data collection infrastructure for implementation on commercial dairy farms throughout 2025. Through a federated learning approach, this deployment ensures robust continuous monitoring across a network of farms, while respecting data confidentiality and cybersecurity. We have developed a framework for the study of animal behaviours and emotions, presenting a paradigm shift for both annotation and data analysis based on continuouscand heterogeneous data sources. As we grow our network of partner farms, we will continue focussed studies on research farms, allowing for continuous exchange between the two contexts. This collaborative approach promotes the responsible integration of new technologies to the industry and empowers endusers to be at the forefront of these new developments, ensuring their sustainability and reinforcing the importance of stakeholder participation in innovative scientific research.

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Vasseur, Elsa

Plenary Session 2 [External] Présentation

Vila Real, Portugal, 01.07.2025.

Liens | BibTeX | Étiquettes: conférencier invité

Diallo, Abdoulaye Banire

Cas concrèt: WELL-E [External] Présentation

Montreal, Canada, 01.06.2024.

Liens | BibTeX | Étiquettes: conférencier invité

Cellier, M.; Aigueperse, N.; Shepley, E.; Villetaz-Robichaud, M.; Vasseur, E.

Cow-conception - Intégrer l'expérience de l'animal lors de la conception du logement ou de nouvelles pratiques pour maximiser la réponse animale et l'expérience utilisateur (producteur) [External] Présentation

Rennes, France, 01.02.2024.

Liens | BibTeX | Étiquettes: conférencier invité

Diallo, A. B.; Vasseur, E.

Le Projet WELL-E (IA au service du bien-être des bovins laitiers). [External] Présentation

Montreal, Canada, 01.11.2023.

Liens | BibTeX | Étiquettes: conférencier invité