Abstract
The global dairy industry has undergone profound changes over recent decades in the world. There is a trend in dairy farming toward the automation of processes to reduce the labor and its associated costs. This development is mainly driven by the increment of labor costs relative to capital costs. Automated systems enable dairy farmers to manage larger herds with lower labor requirements and costs. This trend toward automation is suitable for the tendency of increasing herd sizes.
The behavior of animals is a clear indicator of their physiological and physical state. Eating, ruminating and resting are the main daily activities of ruminant livestock. Monitoring these activities in the field is essential to crucial management decisions in grazing systems. This information allows herd managers to evaluate the feeding conditions of grazing cattle and make productive decisions about supplement and pasture management. Furthermore, accurate monitoring of foraging behavior of free-grazing cattle is necessary to ensure the welfare and health of these animals. Many efforts have been devoted to develop suitable techniques to address this problem, however the success of these developments has been limited by practical factors.
In this research line, we develop algorithms and embedded systems for analyzing the feeding and reproductive behaviour of caws. We develop novel algorithms and computing tools for signal processing, classification and data fusion, which are implemented in embedded systems that operates in field. Current research lines:
- Analysis of feeding behaviour using sound and movements of the head;
- Estrus detection using animal locomotive and feeding behaviour;
- Development of low-power embedded system.
Principal researchers:
Leandro Giovanini
Diego Milone
Leonardo Rufiner
Current funding:
Proyecto 2010 ASaCTeI
CATT 2016 UNL
Past funding:
PICT-O 2005 ANPCyT
PICT Start-up 2011 ANPCyT