Robust Classification of Animal Tracking Data

TitleRobust Classification of Animal Tracking Data
Publication TypeJournal Article
Year of Publication2007
AuthorsSchwager M., Anderson D.M., Butler Z., Rus D.
JournalComputers and Electronics in Agriculture
Date PublishedApril 2007
ARIS Log Number197372
Keywordsadaptive sampling, animal tracking, cluster analysis, GPS, sensor networks
AbstractThis paper describes an application of the K-means classification algorithm to categorize cow tracking data into various classes of behavior. It is found that even without explicit consideration of biological factors, the clustering algorithm can repeatably resolve cow behavior into two groups corresponding to active and inactive periods. Furthermore, it is shown that this classification is robust to a large range of data sampling intervals. An adaptive data sampling algorithm is suggested for improving the energy efficiency and memory usage of animal tracking equipment.