Sow-activity classification from acceleration patterns: A machine learning approach

► A supervised-learning approach to sow-activity classification is introduced. ► Acceleration patterns are used, time dependencies between measurements are ignored. ► The method is able to classify measurements recorded at an instance of time. ► The method allows the online monitoring of animals in (near) real-time. ► Experimental results outperform previous work by a considerable margin.