This project introduced quick thoracic ultrasonography (qTUS) into practice, using it as a reference test for therapy and vaccine evaluation as well as sensor development for calf pneumonia. A combination of a digital course and practical sessions enabled veterinarians to achieve acceptable diagnostic accuracy. Cough was identified as the most informative early warning sign. Over 70% of pneumonia cases were found to be subclinical, rendering clinical scoring systems unsuitable for treatment. However, the developed lung ultrasound scoring system (qTUS score) allowed for maximum recovery with minimal antibiotic use. qTUS-guided antimicrobial therapy achieved a 60% reduction in antibiotic use on a closed beef farm but was less effective in the veal sector, where mixed infections occur. Antibodies against bovine coronavirus and bovine respiratory syncytial virus at the time of veal farm arrival protected against pneumonia onset. Current biomarkers (SAA and haptoglobin) were insufficient to differentiate viral from bacterial infections. A multivariable single-sensor system was validated for calves and deemed suitable for non-invasive stress monitoring in a setup evaluating respiratory sampling methods. Initial results of this system for automated pneumonia detection are promising but require further exploration with alternative machine learning techniques in larger populations.