Abstract
This paper addresses detection of oestrus in dairy cows using methods from
statistical change detection. The activity of the cows was measured by a necklace
attached sensor. Statistical properties of the activity measure were investigated. Using
data sets from 17 cows, diurnal activity variations were identified for the ensemble and
for the individual cows. A diurnal filter was adapted to remove the daily variation of the
individual. Change detection algorithms were designed for the actual probability
densities, which were Rayleigh distributed with individual parameters for each cow. A
generalized likelihood ratio algorithm was derived for the compensated activity signal
and detection algorithm was tested on 2323 days of activity, which contained 42
oestruses on 12 cows in total. The application of statistical change detection methods is a
new approach for detecting oestrus in dairy cows and the results are shown to outperform
earlier approaches in respect to combined statistics of false alarms and missed detections
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 17t. World Congress : The International Federation of Automatic Control |
| Publication date | 2008 |
| Pages | 658-663 |
| DOIs | |
| Publication status | Published - 2008 |
| Event | The International Federation of Automatic Control Congress - Seoul, Korea, Democratic People's Republic of Duration: 6 Jul 2008 → 11 Jul 2008 |
Conference
| Conference | The International Federation of Automatic Control Congress |
|---|---|
| Country/Territory | Korea, Democratic People's Republic of |
| City | Seoul |
| Period | 06/07/2008 → 11/07/2008 |
Keywords
- Signal processing
- Developments in measurement
- Fault diagnosis and monitoring.
- Animal husbandry