Measurement science is becoming increasingly relevant to veterinary and animal sciences as sensing, imaging, wearable devices, Internet of Things (IoT), omics and genomic technologies, and artificial intelligence (AI) enable the quantitative assessment of animal health, physiology, behaviour, welfare, performance, genetic and molecular characteristics, and interactions with the environment. Despite these advances, important measurement challenges remain. These include the definition of measurands, establishment of reliable reference values and ground truth, sensor calibration and validation, measurement uncertainty, repeatability and reproducibility, data quality, and comparability of results across animals, systems, environments, and experimental conditions.

These challenges become particularly relevant when AI, computer vision, and data-driven models are part of the measurement process. High predictive accuracy alone does not necessarily ensure that an estimated quantity constitutes a reliable and metrologically characterized measurement result.

This Special Session aims to bring together researchers from measurement science, veterinary medicine, animal science, engineering, Precision Livestock Farming (PLF), sensing, imaging, bioinformatics, multi-omics analysis, and Animal Data Science. The goal is to establish a common measurement-science framework for emerging methods and technologies in veterinary and animal applications and to foster discussion on reliable, validated, and comparable animal measurements.

List of Topics

• Measurement science in veterinary and animal sciences
• Measurement of animal health and physiological parameters
• Quantitative assessment of animal behaviour and welfare
• Animal biometrics and phenotyping
• Veterinary diagnostic and monitoring systems
• Sensors, wearable devices, and non-invasive measurements
• Imaging and computer vision for animal measurements
• Precision Livestock Farming measurement systems
• IoT and distributed sensing for animal monitoring
• AI and machine learning in measurement systems
• Measurand definition in data-driven animal measurements
• Reference methods and ground-truth definition
• Calibration and metrological validation
• Measurement uncertainty
• Repeatability and reproducibility
• Sensor and measurement data quality
• Sensor fusion and multimodal measurement
• Environmental measurements and animal-environment interactions
• Comparability and interoperability of animal measurement systems

Veterinary measurements, Animal measurement science, Animal health, Animal welfare, Animal behaviour, Animal phenomics (high-throughput phenotyping), Precision Livestock Farming, Artificial intelligence, Computer vision, Sensor systems, Measurement uncertainty, Metrological validation, Animal Data Science