Pig Health Assessment Based on Applied Sensors – Smart Pig Health

Leveraging digitised sensors and prediction models to predict diseases among pigs early on and providing transparent information to all stakeholders. 


Pig health and animal welfare are inextricably linked with the use of antibiotics and are of growing importance for society and farmers alike. Therefore, this Flagship Innovation Experiment (FIE) employs a holistic approach to improve pig health while reducing Antimicrobial Resistance (AMR). To reach this objective all relevant stakeholders in the pig production sector are integrated to provide consumers with transparent information. The digitalisation of prediction models and sensor implementation enables a continuous health assessment through data analytics using self-developed algorithms based on machine learning and Artificial Intelligence (AI). Moreover, this predicts diseases and mal conditions at an early stage, giving the farmer the ability to initiate the necessary countermeasures to keep their pigs healthy.

Research results indicate that criteria like humidity, temperature, noise, water and feed consumption significantly impact animal welfare. At the moment, however, those biological and economic parameters are not recorded or taken into account continuously. Consequently, this FIE addresses this strategic challenge to farmers and veterinarians while also addressing the societal concern of antibiotics use and pig health, through a sustainable ecosystem.



The following sensors were implemented on a farm:

  • 12 sensors to measure the water consumption
  • 18 sensors to measure temperature
  • 5 sensors to measure humidity
  • 1 NH3 sensor
  • 1 CO2 sensor
  • Camera to measure pig’s movement


We focus on identifying the following issues: skin lesions, flank biting, lameness, nose discharge, ear injuries, tail injuries, respiratory symptoms, diarrhoea, abnormal behaviour.

Our system would also allow the farmer to be updated on detrimental alterations to the pig's environment: water supply, feed supply, ventilation, mortality, treatments and other events. 

Lessons Learnt 

During the tests some problems occurred, such as an interrupted server connection. Therefore, the camera system was optimized to take care of some problems, for example, to save the data on an external hard drive as a backup in case of an interrupted server connection.
To protect the sensors and the camera from environmental influences and the pigs in the barn, self-build casings or protective devices were built, as you can observe in the pictures below. 


To measure the water consumption flow meters were installed. Over time we noticed a difference between the calculated consumption per pen and the increased figures from the sensors. We then identified that the flow meters were clogged. Either we have to get another flow meter or the farmers have to improve the quality of the water system.