Title | Robust Classification of Animal Tracking Data |
Publication Type | Journal Article |
Year of Publication | 2007 |
Authors | Schwager M., Anderson D.M., Butler Z., Rus D. |
Journal | Computers and Electronics in Agriculture |
Volume | 56 |
Pagination | 46-59 |
Date Published | April 2007 |
ARIS Log Number | 197372 |
Keywords | adaptive sampling, animal tracking, cluster analysis, GPS, sensor networks |
Abstract | This 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. |
URL | /files/bibliography/07-010.pdf |