The project WAIT4 (Welfare, Artificial Intelligence and new Technologies for Tracking key indicator Traits in animals facing challenges of the agroecological Transition) aims to enhance animal welfare (AW), a key component of sustainable livestock production systems. As environmental conditions become increasingly variable due to the impacts of global warming, the effects on animals raised in agroecological transition systems --characterized by less optimized and more variable outdoor conditions -- are expected to intensify. This underscores the growing need for innovative tools to assess AW and support decision-making, enabling the adoption of agroecological practices that promote animal well-being.

Strategies to improve AW rely heavily on accurately measuring traits related to an animal’s physiology, behavior, and perception when facing various challenges. The WAIT4 project will leverage advancements in digital technologies to enable real-time monitoring of these diverse components of AW. Furthermore, it will employ pioneering artificial intelligence approaches to integrate and analyze large, heterogeneous datasets collected from and around the animals, facilitating more informed and effective interventions to enhance their welfare.

The project aims to:

• Test and develop equipment and sensors to assess animal behavior, physiological constants, and emotional states.
• Develop artificial intelligence algorithms to integrate heterogeneous data in terms of nature and temporality, extracting relevant animal welfare (AW) indicators (proxies).
• Enable real-time monitoring of changes in these proxies for various species (pigs, small and large ruminants) raised indoors or outdoors, under conventional (e.g., grazing) or alternative (e.g., organic) farming systems, and in contrasting environmental contexts (e.g., tropical or temperate climatic conditions).
• Identify early warning signals (early deviations) of changes in AW and health.
• Foster interdisciplinary collaboration by encouraging dialogue between scientists from diverse fields (e.g., ethology, data science) and stakeholders, promoting the adoption and dissemination of project outcomes.

Consortium

The consortium brings together expertise in electrochemistry, physiology, ethology, precision agriculture, data science, and data mining. Partners include French research and education institutes (INRAE, CEA, INRIA/Univ Rennes 1, INSA Lyon), a living lab (LIT Ouesterel), and a small enterprise (AIHERD).

Ultimate goals

WAIT4 aims to generate new knowledge and develop proxies for better measurement of AW for individual animals within their groups, covering periods ranging from a few days to several months, and even accounting for seasonal effects within an agroecological framework. The project will ultimately result in tools to enhance AW, including:

• Proposing livestock management practices (individual or group-based),
• Refining AW evaluation frameworks,
• Informing breeding programs to accelerate the agroecological transition.