Short summary of your UC This use case combines sensor systems, real-time farm data, numerical modelling, and AI methods to improve the estimation of emissions and barn climate in dairy farming systems. The goal is to reduce greenhouse gas and ammonia emissions while improving barn climate and animal welfare. Introduction Dairy farms are important sources of NH₃ and greenhouse gas emissions. Reliable monitoring and assessment methods are still limited. This use case addresses these challenges through advanced measurements, modelling, and AI-based analysis. Methodologies • Low-cost sensor networks for monitoring barn climate and emissions • High-resolution measurements of NH₃, CH₄, and N₂O emissions • Wind tunnel experiments for validation datasets • Mechanistic modelling of ammonia emissions • Machine learning using multimodal datasets (images, videos, pH, temperature, etc.) • Harmonization of measurement protocols with international stakeholders Outputs • Public validation and emission datasets • AI training datasets • Mechanistic NH₃ emission model • Validated sensor network system • Workshop on harmonized measurement protocols Impact • Improved emission assessment and mitigation • Better barn climate and animal welfare • Open datasets and tools for the research community • Harmonized international measurement standards What I can offer • Expertise in emission measurements, sensor systems, and modelling • Mechanistic and AI-based modelling approaches • Collaboration on harmonized methodologies What I need • Access to commercial dairy farms • International collaboration and data exchange • Expertise in AI, modelling, and digital agriculture • Stakeholder involvement for dissemination and standardization

Source: Annual AgData Use Case Summit 2026 booklet.