COROB Cluster Conversations: dAIry 4.0
What is your project about?
dAIry 4.0 develops an AI-driven optimisation framework for next-generation dairy farming, focusing on intelligent control of robotic milking systems, named Automated Milkings Systems (AMS). The project integrates advanced data analytics, machine learning and adaptive decision-support tools to personalise milking processes at the individual cow level.
By leveraging real-time behaviour and production data, dAIry 4.0 transforms conventional robotic milking from a rule-based automation system into a continuously learning, self-optimising environment.
The project aims to improve animal welfare, milk yield, operational efficiency and environmental sustainability. Through dynamic adjustment of milking parameters, early health risk detection, and simulations of cow performance, dAIry 4.0 enables precision livestock farming with measurable economic and societal benefits.
The AI, Data and Robotics Partnership call emphasises optimisation of production and services value-chains through integrated AI, data and robotics solutions. How does your project contribute to this ambition, and what concrete added value do you aim to demonstrate in your selected use cases?
dAIry 4.0 directly contributes to the optimisation of the dairy production value chain by embedding AI0driven intelligence into the core production stage: robotic milking. Rather than treating milking robots as isolated automated units, the project integrates AI, data analytics and robotics control into a unified optimisation tool. This enables continuous adaptation of operational parameters (e.g. milking time) based on individual cow responses and herd-level performance indicators.
The concrete added value demonstrated in the selected use cases includes: increased milk yield through personalised milking strategies, improves animal welfare through operational adjustments and early anomaly detection, lower operational costs by optimising energy, time and labour use, and enhanced decision-making for farmers through explainable AI.
By improving efficiency, product and herd health simultaneously, dAIry 4.0 strengthens the resilience and competitiveness of the dairy value chain while reducing waste and environmental footprint.
One of the expected outcomes of the call is the development of AI or learning systems that adapt workflows to dynamic environments and human capabilities. How does your project address adaptability, flexibility or human-centred innovation in your domain?
dAIry 4.0 develops adaptive AI systems capable of learning from continuously evolving farm environments. Dairy farms operate under dynamic conditions: seasonal variations, herd composition changes, lactation stages, health fluctuations, and human operator practices.
The project employs machine learning models that update based on new data streams, enabling real-time adjustment or robotic workflows to reflect changing biological and operational conditions. Human-centred innovations is embedded through decision-support interfaces that provide interpretable AI recommendations rather than opaque automation, configurable autonomy levels, allowing farmers to retain control over critical operation decisions, workflow adaptation aligned with farmer routines and labour availability, and continuous feedback loops between system performance and user input.
By balancing automation with farmer oversight, dAIry 4.0 ensures that AI enhances human expertise, creating a flexible, trustworthy and socially acceptable innovation pathway in precision livestock farming.
Learn more about dAIry 4.0 at: https://dairy40.eu/
