Purpose & Scope
This training provides a practical introduction to using UWB and accelerometer sensors for livestock monitoring.
Participants learn to design, deploy, and analyse sensor networks to monitor behaviours such as lying, walking, rumination, and social interactions. Real-world datasets are used to demonstrate behaviour recognition, anomaly detection, and welfare assessment.
Hands-on sessions include data preprocessing, modelling basics, and visualisation using open-source tools such as Python and Grafana.
If you want to get more information about the training, please get in touch with Marijke.hunninck@ilvo.vlaanderen.be
Learning objectives
By the end of the training, participants will be able to:
- Understand the operating principles of UWB and accelerometers for cattle monitoring.
- Collect and preprocess sensor data from dairy barns.
- Apply basic AI techniques to classify cattle behaviours from sensor data.
- Evaluate the effectiveness of sensor systems in monitoring health and welfare.
- Demonstrate data visualisation methods using tools like Grafana and Python.
Learning outcomes
Participants completing this training will be able to:
- Identify key behavioural patterns in cattle using sensor data.
- Deploy and calibrate UWB and accelerometer systems in real-world barns.
- Interpret and communicate insights on animal behaviour and welfare using visualisation dashboards.
Who should attend?
EDIHs, researchers, agritech developers, livestock advisors, and professionals interested in sensor-based cattle monitoring and data-driven welfare assessment.
AI implementation
Dairy farming
Software / AI model
