Using 'Internet of Things' (IoT) technology to improve slurry management on farms.

The aim of this project was to better understand what role IoT technology has when trying to help farmers with their slurry management. Soil condition, water table level, rainfall levels and air temperature all influence the likelihood of water run-off from fields. When it occurs after slurry application it can waste a valuable source of nutrients and risks polluting natural water courses. 

This project tested a range of sensors at Glynllifon College and two other dairy farms in North West Wales, Hen Dŷ near Caernarfon and Erw Fawr near Holyhead. The farmers hoped that by gaining real-time information on the conditions of the land it would allow them to quickly and safely make decision on slurry management.

Various IoT sensors were positioned on each of the three farms:

  1. Water table sensors - aimed to test if accurately monitoring the water table level would provide farmers with useful knowledge of when it is suitable to apply slurry onto a field.   
  2. Soil moisture sensors - to test the quality of the data generated against the number of sensors per field and layout pattern.    
  3. Rain Gauge – to enable farmers to monitor the amount of rainfall in the area. This would factor into the overall decision over whether conditions are correct to apply slurry or not.
  4. Slurry Pit Level Sensor - Good slurry management includes ensuring adequate safe storage on-farm. This data would provide the farmer with accurate information on storage capacity.

 

Project Outcomes

  • This project was the first of its kind in Wales to evaluate the use of IoT technology in slurry management.
  • The technology trialled does work for collecting data on farm conditions and this project has laid the foundations for IoT technology to provide better information when managing a nutrient rich source to improve farming and reduce water pollution.
  • The data provided by the sensors fed into the ‘Pethau’ dashboard (which was developed separately to the project) which has shown potential to aid farmers in their decision on which fields are suitable for slurry application.
  • The project also evaluated the opportunity for IoT to be used for self-auditing purposes by logging environmental conditions and weather forecasts for farms.
  • This project supports better decision making beyond slurry application. For example, a soil temperature sensor could assist a farmer to decide when best to apply nitrogen fertiliser at the start of a new season when using the T-SUM 200 model.