TrackLab with farm animals

The future of farming

Friday, 9 August, 2013

GPS has always seemed to me to be a kind of magic technology.  The idea that a grid of satellites so far above my head that I cannot even see them can tell me exactly where I am and help give me directions where to go is pretty stupendous. And you do not even have to pay for the information! GPS is such a powerful technology that it is being applied to a great diversity of areas. One example is precision agriculture. For instance, if you are growing crops, they will often need water, pesticides and fertilizer.  If you don’t give them enough they will have a reduced yield and if you give them too much you spend too much money and you might cause pollution. The image on the right [1] shows a crop that needs watering.  But only the red areas are dry. So if that data is fed into a GIS databank and that is coupled to a GPS receiver on the irrigation system, the farmer will know precisely where to give water (or chemicals) so that the crop gets the right amount and there is minimal waste and runoff.

Virtual fencing

That sort of technology has been around for a few years now. GPS is also very suitable for moving objects, including farm animals. A technique which has not really taken off yet, but could well be very interesting in the future is that of virtual fencing.  When a farmer puts up an electric fence, the animals have to learn that the shock they get from touching it means that they should not try and cross the fence. You can use the same principle with an animal with a GPS collar.  That can be programmed so that when the animal crosses a line on a digital map, it receives a signal persuading it to turn back. Virtual fencing has been used in that way to keep in farm animals in large extensive farms (e.g. sheep farms in Australia [2]) and to keep animals such as wolves [3] or elephants [4]  from getting in and damaging crops or farm animals.

Behavior detection by GPS

The next generation of GPS hardware and software takes this a step further. GPS is now sufficiently accurate that you can not only use it to know roughly where your animals are and where they have been, but you can also measure their behavior. Currently this is for fairly simple behaviors such as walking or lying/standing still [5]. Ruminating and standing cannot be separated with GPS data alone. However, recent work combining GPS data with accelerometer data  has shown that if the two data streams are put together, then more behaviors can be separated. This opens up a whole range of possibilities for future use of GPS and precision farming. Simple techniques already in use such a using pedometers to predict if a cow is in oestrus or for monitoring welfare [7, 8] could be improved and made more accurate. The welfare of farm animals could be better monitored and predicted. Better information about the use of the land by the animals (are they mostly grazing or just lying down in that corner of the field?) can lead to improved land management. New systems such as TrackLab will help make this possible. With animal welfare and resource scarcity becoming increasingly important topics, it may not be long before we begin to see cows equipped with GPS tags like in the photo above [9].


  1. Image: Susan Moran, Landsat 7 Science Team and USDA Agricultural Research Service.
  2. Umstatter C (2010). The evolution of virtual fences: A review. Computers and Electronics in Agriculture, 75, 10-22.
  3. Licht et al. (2010). Using small populations of wolves for ecosystem restoration and stewardship. BioScience, 60, 147-153.
  5. Anderson D.M. et al. 2012. Characterising the spatial and temporal activities of free-ranging cows from GPS data. The Rangeland Journal, 34, 149-162.
  6. Spink A.J., Cresswell B., Kölzsch A., Van Langevelde F., Neefjes M., Noldus L.P.J.J., Van Oeveren H., Prins H., Van der Wal T., De Weerd N., & De Boer W.F. 2013 (in press).  Proceedings of Joint European Conference on Precision Livestock Farming, Leuven, 2013. See also: TrackLab website.
  7. Brehme U., Stolberg U., Strickeler B., v. Niederhäuser R. & Zurkinden H. (2006). Investigations of daily biorhythm in different horse keeping systems for well-being measured with ALT pedometer. In: International conference on methods and techniques in behavioral research; Proceedings of measuring behavior 2005.
  8. Løvendahl P. & Chagunda M.G.G. (2010). On the use of physical activity monitoring for oestrus detection in dairy cows. Journal of Dairy Science, 93 (1) 249–259.
  9. Image courtesy of Wageningen UR, Resource Ecology research group.