Precision livestock farming uses sensors, cameras, and AI to continuously monitor animal welfare indicators, offering the potential to detect health problems earlier and improve intervention.
Precision livestock farming technologies represent a significant opportunity to improve real-time welfare monitoring at scale. Traditional welfare assessment relies on periodic human inspections that miss many problems. Continuous sensor data from activity monitors, milk meters, and feeding systems can identify deviations from individual animal baselines indicating health or welfare problems. Computer vision systems analyzing video footage can detect lame cows, respiratory distress in pigs, and abnormal behaviors in poultry. These technologies allow earlier intervention, reducing both suffering duration and production losses. However, there are concerns about data privacy, system reliability, and whether precision monitoring improves the underlying conditions that cause welfare problems rather than just detecting them after they occur. Integration with farm management systems is key to translating data into welfare improvements.