dAIry 4.0 | Advanced, trustworthy AI and data solutions for individualised automated milking & feeding of dairy cows

Summary
The agricultural sector has a big challenge: producing more with fewer raw materials and less adverse effects on society, production animals, climate and biodiversity. Optimal use of resource is even more important now, due to the imminent food crisis. Climate-friendly sustainable agriculture, with care for natural resources, is essential for our food production and quality of life, today and for future generations.
Automated Milking Systems (AMS) were developed in the late 20th century under the perspective of reducing manual labour & costs and improving quality of life for the farmers. Not only have these machines improved in harvesting milk efficiently, but they also have the added ability to collect a greater amount of data about production, milk composition, cows health and behaviour. This could allow producers to make more informed management decisions, while in parallel reducing emissions and increasing animal welfare.
Nevertheless, currently available AMS have important limitations in terms of optimising their operation.
dAIry 4.0 addresses these challenges, integrating and optimising AI, data and robotics solutions to demonstrate how this combination will optimise AMS production aspects and minimise adverse effects on society, climate and biodiversity. The approach will be demonstrated through real-world use cases of interest both for the farming sector and the food industry. In terms of AI tools to be used, the project will focus on the following novelties:
- Developing multimodal learning techniques to efficiently utilize multiple types of information for animal health & overall animal status monitoring
- Developing self-supervised and novel data augmentation techniques to reduce the amount of labelled training data needed
- Exploring novel explainable AI techniques to increase transparency of the system and eventually facilitate acceptance by the users
- Including the farmer in the loop to build the cognitive abilities for the system
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/101119714
Start date: 01-10-2023
End date: 31-03-2027
Total budget - Public funding: 3 533 843,75 Euro - 2 957 356,00 Euro
Cordis data

Original description

The agricultural sector has a big challenge: producing more with fewer raw materials and less adverse effects on society, production animals, climate and biodiversity. Optimal use of resource is even more important now, due to the imminent food crisis. Climate-friendly sustainable agriculture, with care for natural resources, is essential for our food production and quality of life, today and for future generations.
Automated Milking Systems (AMS) were developed in the late 20th century under the perspective of reducing manual labour & costs and improving quality of life for the farmers. Not only have these machines improved in harvesting milk efficiently, but they also have the added ability to collect a greater amount of data about production, milk composition, cows health and behaviour. This could allow producers to make more informed management decisions, while in parallel reducing emissions and increasing animal welfare.
Nevertheless, currently available AMS have important limitations in terms of optimising their operation.
dAIry 4.0 addresses these challenges, integrating and optimising AI, data and robotics solutions to demonstrate how this combination will optimise AMS production aspects and minimise adverse effects on society, climate and biodiversity. The approach will be demonstrated through real-world use cases of interest both for the farming sector and the food industry. In terms of AI tools to be used, the project will focus on the following novelties:
- Developing multimodal learning techniques to efficiently utilize multiple types of information for animal health & overall animal status monitoring
- Developing self-supervised and novel data augmentation techniques to reduce the amount of labelled training data needed
- Exploring novel explainable AI techniques to increase transparency of the system and eventually facilitate acceptance by the users
- Including the farmer in the loop to build the cognitive abilities for the system

Status

SIGNED

Call topic

HORIZON-CL4-2022-DIGITAL-EMERGING-02-05

Update Date

31-07-2023
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Artificial Intelligence, Data and Robotics Partnership (ADR)
ADR Partnership Call 2022
HORIZON-CL4-2022-DIGITAL-EMERGING-02-05 AI, Data and Robotics for Industry optimisation (including production and services) (AI, Data and Robotics Partnership) (IA)
Horizon Europe
HORIZON.2 Global Challenges and European Industrial Competitiveness
HORIZON.2.4 Digital, Industry and Space
HORIZON.2.4.0 Cross-cutting call topics
HORIZON-CL4-2022-DIGITAL-EMERGING-02
HORIZON-CL4-2022-DIGITAL-EMERGING-02-05 AI, Data and Robotics for Industry optimisation (including production and services) (AI, Data and Robotics Partnership) (IA)
HORIZON.2.4.5 Artificial Intelligence and Robotics
HORIZON-CL4-2022-DIGITAL-EMERGING-02
HORIZON-CL4-2022-DIGITAL-EMERGING-02-05 AI, Data and Robotics for Industry optimisation (including production and services) (AI, Data and Robotics Partnership) (IA)