e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.

This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.

You can access and play with the graphs:

Discover all records
Home page

Title

The automatic detection of dairy cow feeding and standing behaviours in free-stall barns by a computer vision-based system

en
Abstract

Changes in cow behaviour may occur in relation to health disorders. In literature the suitability of using behavioural changes to provide an early indication of disease is studied. The possibility of achieving a real-time analysis of a number of specific changes in behaviours, such as lying, feeding, and standing, is crucial for disease prevention. Cow feeding and standing behaviour detectors were modelled and validated by defining a methodology based on the Viola-Jones algorithm and using a multi-camera video-recording system to obtain panoramic top-view images of an area of the barn. Assessment of the detection results was carried out by comparison with the results generated by visual recognition. The ability of the system to detect cow behaviours was shown by the high values of its sensitivity achieved for the behaviours of feeding and standing which were about 87% and 86%, respectively. Branching factor values for the two behaviours showed that one false positive was detected for every 13 and 6 well-detected cows, respectively. On the basis of these research outcomes, the proposed system is suitable for computing cow behavioural indices and the real-time detection of behavioural changes. (C) 2015 IAgrE. Published by Elsevier Ltd. All rights reserved.

en
Year
2015
en
Country
  • IT
Organization
  • Univ_Catania (IT)
Data keywords
  • real time analysis
en
Agriculture keywords
  • farming
  • livestock
en
Data topic
  • sensors
en
SO
BIOSYSTEMS ENGINEERING
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
    uid:/KX1M9ZCG
    Powered by Lodex 8.20.3
    logo commission europeenne
    e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
    Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.