Sensor Data and AI in Animal and Human Health

This Summer School is designed for domain experts working with animals or humans who want to use digital technologies more effectively, without becoming technical experts themselves. It is particularly relevant for:

Healthcare professionals, veterinarians and other practitioners who want to use data and sensors to improve health or welfare outcomes, but do not feel comfortable working with raw datasets or technical models.

Researchers and R&D professionals in academia and industry who see the potential of sensors and wearables in their work, but struggle to assess which technologies are suitable and which are not.

Product developers, business developers and managers in AgTech or life sciences who work with data scientists or technology providers and want to better understand the technology in order to steer development or investment decisions.

• Make informed decisions on sensor technologies
• Understand key biological signals and how they can be measured using sensors (e.g. movement, physiology, location) - without the engineering jargon;
• Evaluate sensors based on practicalities such as wearability, battery life, data resolution and biological fit (e.g. is it comfortable to wear?);
• Understand computational methods for sensors;
• Understand the basic logic behind commonly used computational approaches, including machine learning and AI, without engaging with mathematics or programming;;
• Assess whether a computational method is appropriate for a given question or unnecessarily complex;
• Understand how tools such as large language models and chatbots can support tasks like data exploration, summarisation or interpretation in biological contexts;l;
• Work more confidently with data scientists and technology providers
• Ask targeted, critical questions about data, models and assumptions when collaborating with technical experts;
• Interpret results well enough to judge their biological relevance and limitations;
• Avoid common pitfalls and unrealistic expectations when applying digital technologies in animal or human monitoring;

During this five-day Summer School, you will move step by step from biological question to technological application. Each day combines interactive lectures, real-world case studies, hands-on exercises, group discussions and excursions.

From bioresponse to sensor
We start with the biological question: what exactly do you want to measure in an animal or human---and why? You will explore meaningful bioresponses, common misconceptions about AI, and how different sensor types relate to biological signals. Through practical exercises, you will learn to link biological insight to technological possibilities.

Making informed technology choices
You will work on selecting and justifying sensor technologies, weighing practical trade-offs such as wearability, battery life and data quality. Sessions with pioneers in animal and human monitoring provide real-world case studies and honest insights into implementation.

Data collection and analytical approaches
The programme introduces core concepts in data collection and analysis, including regression, classification, and image or sound processing---without diving into complex mathematics. You will learn how to decide when advanced models add value and when simpler approaches are sufficient.

Integration and reality check
Excursions to applied settings in animal or human contexts allow you to see technologies in action. Throughout the week, we openly discuss what digital technologies can---and cannot---deliver, helping you avoid costly trial and error in your own work.

After completion of the course, participants will receive a certificate

• Dr Ali Youssef, WUR and University of Manitoba
• Dr Tomas Norton, KU Leuven