Gesellschaft für Informatik e.V.

Lecture Notes in Informatics


IT-standards in der agrar- und ernährungswirtschaft -- fokus: risiko- und krisenmanagement P-226, 221-224 (2014).

Gesellschaft für Informatik, Bonn
2014


Copyright © Gesellschaft für Informatik, Bonn

Contents

Recognition of activity states in dairy cows with svms and graphical models

Jan Behmann , Kathrin Hendriksen , Ute Müller , Sebastian Walzog , Wolfgang Büscher and Lutz Plümer

Abstract


Activity patterns of dairy cattle have received increasing interest in recent years because they promise insights into health state and well-being. The fusion with data from additional sensor signals promises a comprehensive monitoring of activity patterns composed of sequences of single activity states. We used a combination of a Support Vector Machine (SVM), a state of the art classification method, and a Conditional Random Field (CRF). SVMs distinguish single states, whereas CRFs label state sequences under consideration of specified constraints. In a preliminary experiment, a Local Positioning System was combined with a heart rate sensor in order to estimate seven spatiotemporal activity states. The application of the CRF to the SVM result caused a slight increase in accuracy (5\%) but a major improvement at the correct determination of long sequences (increasing length of the longest common subsequence from 3481 to 6207 periods). This robust detection of long lying sequences allowed for the unaffected extraction of the resting pulse.


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Gesellschaft für Informatik, Bonn
ISBN 978-388579-620-6


Last changed 15.04.2014 17:36:53