dAIry 4.0

About dAIry 4.0

Objectives

Objective 1

Develop the dAIry 4.0 animal status clasifier

The goal is the development of an advanced AI-based module that uses multi-source information for classifying the cows (at the individual animal level).

Objective 2

Develop the actuation modules for individualised animal milking, feeding and milk partitioning

Focus will be the development of individualising milking, feeding and partitioning of the milk and further optimizing these actions in the Voluntary Automated Milking System (AVMS).

Objective 3

Integrating the milking robot and the Decision Support System (DSS)

Aiming to deliver six integrated milking robots for the use cases. The dAIry 4.0 DSS will be used to ensure that involved stakeholders are able to track, monitor and control the optimization process towards the high level farm goals, while also optimising AVMS use.

Objective 4

System validation & demonstration through real-world use cases

The complete system will be validated through tests in six farms. Validation will be performed through comparison of the system with standard performance, but also with non-AMS based milking. Added value will be demonstrated by qualitative and quantitative dairy and food industry relevant KPIs.

Objective 5

Facilitate the uptake of the technology beyond the specific use cases

Wide-scale but also audience-specific communication actions are planned. Aiming to demonstrate the value of project outcomes even beyond the targeted application domain.

Work Packages

WP1 – Project Management

WP1 coordinates the project tasks, milestones and deliverables, and ensures compliance with EC financial and administrative procedures.

WP2 – Preparation; Use cases detailed definition & system requirements

WP2 will focus on preparatory work based on identification of key stakeholders and collection of their requirements to support the definition of use cases and prepare the requirements of all system components.

WP3 – The dAIry 4.0 animal status classifier

WP3 aims for the development of specific modules for animal health inspection and milk quality analysis. In continuation, the overall animal status classifier will be developed.

WP4 – Actuation modules development and overall robotic integration

WP4 will look further into the development of actuation modules like individualized milking and feeding modules, milk partitioning modules and integration of the robotic system overall.

WP5 – DSS and data infrastructure development

WP5 focuses on the development of the data platform, simulation tools and the Decision Support System (DSS) based on farm experts’ experiences and needs.

WP6 – Validation & demonstration through real-world use cases

WP6 works as the quality control of the newly developed system by firstly validating the system in a controlled environment and then under real-world scenarios. Performance will be assessed and evaluation results will be used to confirm the system’s impact.

dAIry 4.0 Consortium

Start date: 01/10/2023

Duration: 42 months

Funding: € 2 957 356,25

Partners: 7

Countries: 6

News & Results

Zenodo Repository

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Cordis – Published Results

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Latest News

18M Consortium Meeting!

A successful M18 dAIry 4.0 project meeting was held on 12th-13th March in Athens, Greece and was hosted by our partner ICCS – NTUA . This two-day meeting provided an important[…]

admin March 19, 2025 0

12M Professional Video is out!

Imagine a dairy farm where AI detects health issues before they arise, where every drop of milk is monitored with precision, and where automation ensures that cows are milked at[…]

admin February 20, 2025 0

M6 – M12 Newsletter!

The second version of the newsletter is now released, summarizing all project updates, and events from the initial 12 months of the dAIry 4.0 project. Interested individuals can subscribe here[…]

admin December 2, 2024 0

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Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or of the granting authority. Neither the European Union nor the granting authority can be held responsible for them.

This work has received funding from the Swiss State Secretariat for Education, Research and Innovation (SERI).

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