Know more

Our use of cookies

Cookies are a set of data stored on a user’s device when the user browses a web site. The data is in a file containing an ID number, the name of the server which deposited it and, in some cases, an expiry date. We use cookies to record information about your visit, language of preference, and other parameters on the site in order to optimise your next visit and make the site even more useful to you.

To improve your experience, we use cookies to store certain browsing information and provide secure navigation, and to collect statistics with a view to improve the site’s features. For a complete list of the cookies we use, download “Ghostery”, a free plug-in for browsers which can detect, and, in some cases, block cookies.

Ghostery is available here for free:

You can also visit the CNIL web site for instructions on how to configure your browser to manage cookie storage on your device.

In the case of third-party advertising cookies, you can also visit the following site:, offered by digital advertising professionals within the European Digital Advertising Alliance (EDAA). From the site, you can deny or accept the cookies used by advertising professionals who are members.

It is also possible to block certain third-party cookies directly via publishers:

Cookie type

Means of blocking

Analytical and performance cookies

Google Analytics

Targeted advertising cookies


The following types of cookies may be used on our websites:

Mandatory cookies

Functional cookies

Social media and advertising cookies

These cookies are needed to ensure the proper functioning of the site and cannot be disabled. They help ensure a secure connection and the basic availability of our website.

These cookies allow us to analyse site use in order to measure and optimise performance. They allow us to store your sign-in information and display the different components of our website in a more coherent way.

These cookies are used by advertising agencies such as Google and by social media sites such as LinkedIn and Facebook. Among other things, they allow pages to be shared on social media, the posting of comments, and the publication (on our site or elsewhere) of ads that reflect your centres of interest.

Our EZPublish content management system (CMS) uses CAS and PHP session cookies and the New Relic cookie for monitoring purposes (IP, response times).

These cookies are deleted at the end of the browsing session (when you log off or close your browser window)

Our EZPublish content management system (CMS) uses the XiTi cookie to measure traffic. Our service provider is AT Internet. This company stores data (IPs, date and time of access, length of the visit and pages viewed) for six months.

Our EZPublish content management system (CMS) does not use this type of cookie.

For more information about the cookies we use, contact INRA’s Data Protection Officer by email at or by post at:

24, chemin de Borde Rouge –Auzeville – CS52627
31326 Castanet Tolosan CEDEX - France

Dernière mise à jour : Mai 2018

Menu Logo Principal Oniris

Home page

Rumba : Research network on digital technologies to improve livestock health and welfare

Network funded by INRAE / Sanba

Context and implications

Technological advances have greatly increased the possibilities of collecting animal husbandry data automatically and at high frequency, on different scales and at ever decreasing costs. For example, GPS, RFID or accelerometer technologies make it possible to monitor the state of the animal in real time on commercial farms. For other technologies, such as 'omics' measurements, acquisition costs have been significantly reduced, enabling more frequent measurements. As a result, these new technologies have opened up new horizons for both animal science research and commercial applications for non-invasive measurements related to animal health and welfare. The possibilities of measuring and generating alarms for prevention or early detection could help to meet certain societal expectations in relation to animal husbandry on the one hand and the rational use of medication in farm animals on the other hand.

These technologies also raise new questions. For example, the calibration of new measurement methods is often based on more traditional diagnostic methods that may be very imperfect, which may raise questions about the definition and quality of the reference measurement. Another type of issue of interest concerns human decision-making based on information generated by algorithms, which may be an indication of the occurrence of events, with or without uncertainty; or continuous score values. There are many other questions relating to measurement devices and methods of processing the information generated.


Rumba aims to generate research projects on the use of digital tools to improve the health and well-being of animal husbandry, by bringing together scientists, specialists and field actors interested in the different facets of these issues. This general objective can be subdivided into different sub-objectives :

  1. To create a discussion forum for scientists, specialists and field actors with knowledge in the following fields: animal husbandry, animal welfare and health, animal husbandry data collection systems, signal processing, data analysis and modelling.
  2. To bring out the scientific questions and needs in the field related to animal welfare and health that could be addressed by digital technologies
  3. Identify the methodological obstacles limiting the use of digital technologies in animal husbandry.


Madouasse Aurélien (SA, BIOEPAR), Taghipoor Masoomeh (Phase, MoSAR)