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Veterinärmedizinische Universität Wien

Statistics of PLF research projects

PLFDoc

PLFDoc is a collaboration between

  • Vetmeduni
  • Technical university Vienna
  • Univesrity of Applied Science Upper Austria

Research focus of the PLFDoc is on application of computer vision for monitoring parturition in cows and pigs. 

The main aim of the PLFDoc is to enhance animal welfare, e.g. through early detection of dystocia and preventing the death of newborns and their dams in this sensitive period and other health- and welfare-related risks. 

aWISH

The main objective of aWISH is to develop and offer the capacity to evaluate and improve the welfare of meat producing livestock throughout Europe via automated monitoring of animal-based welfare indicators at the slaughterhouse in order to give feedback and advice on best practices to those responsible for the various stages of production (farmer, catching team, transporter, slaughterhouse). This approach will be developed and evaluated in close collaboration with all actors involved, from primary producers up to policy makers and citizens.

Feedura

The project is organized with our commercial partner Schauer. The focus is automated estimation of Body Condition Score and Precision Feeding in gestating sows based on individual nutrition needs.

Machine Perception for PLF

The Project aims to develop software, algorithms and methods for automated monitoring and optimal management of livestock farming that is transferable to diverse production systems with minimal retraining. Optimal management is defined as the best possible use of the available resources for the objectives set by the farmer, given the available information.
The Project seeks to achieve explainable optimal inference from the available data, (particularly the existing herd management data, feed analysis, environmental sensors and sensors on cows), and from additional robust low-cost sensors including but not limited to video.

DiLaAg

 

D4Dairy

The overall goal of D4Dairy is the generation of added value for herd management as well as the improvement of animal health, animal welfare and product quality by creating a welldeveloped (data) network and by exploiting the opportunities offered by new (digital) technologies and analytical methods.

SmartCalf_BRD

Visual scoring of calves of approx 2mo age for detecting BRD.
Describe movement and activity patterns for heatlhy and diseased calves. Algorithm developing and testing. The hypothesis is that accelerometer derived data can be used for early detection of BRD.

 

SmartCalf_DIA

Scoring and clinical examination of calves from d0 to d28 of life for detecting diarrhea. Describe movement and activity patterns for heatlhy and diseased calves. Algorithm developing and testing. The hypothesis is that accelerometer derived data can be used for early detection of calves suffering from diarrhea.

LocateIt!

Evaluate the validity of detecting animals in various functional areas by use of the accelerometer system SMARTBOW.

HeatSensor

Evaluation of the accelerometer system SMARTBOW for detecting bovine estrus events. Describe activity and movement patterns of natural estruses as well as induced estruses (OvSynch).

agriProKnow

The agriProKnow project develops a novel methodology for process related Information management, which aims at significantly improving the milk production efficiency in precision dairy farming. In a particularly complex cyber-physical production system that combines people, animals and technology, the focus is on animal health and welfare modelling, monitoring, and control, as they play the crucial roles in the production process.

The focus of the innovation is a procedure for process knowledge generation, which combines methods of stochastic analysis of sensor data, and semantic situation modeling and semantic data-warehousing.

PigWatch

The objective of the PigWatch project was to develop an automated monitoring technique for detection of nest-building behaviour in sows on the basis of accelerometer data. Postural behaviour of sows was also classified on the basis of accelerometer data. The third objective of the project was to develop a 2D image based piglet counter.

CalfMonitoring

Monitoring of vital parameter of calves during 2nd stage of labor by use of a wireless pulseoximeter.

Developing and testing of a hoof cover for fixing the sensor of the pulseoximeter.

BirthMonitoring

Developing and testing of an algorithm for predicting parturition in dairy cows by use of the accelerometer system SMARTBOW. Hypothesis: Animal acitivity and rumination data can be used for prediction parturition in cattle.

 

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