Do you want to learn how to increase sustainability in the broad discipline of crop science, livestock production and leisure using precision technology and data?
Expand your field of expertise in projects where, for example, you will:
· combine location and activity data for the early detection of claw diseases of cows;
· measure soil humidity and temperature using precision sensors to improve the quality of golf fields;
· analyse data from soil and crop sensors to predict and improve yields of different crops.
Smart Farming provides a learning environment for students with various backgrounds in which they acquire and apply knowledge and gain skills for developing innovative solutions, using data and technology in the agrofood sector.
Themes to be discussed are:
· New technologies in different sectors such as health care and leisure and examples of smart farming in different agricultural sectors
· Cross overs: gaining knowledge and skills from a multi-disciplinary perspective to find solutions for your own field of expertise
· You will develop your own set of tools: learning techniques such as biomimicry, sensing, robotics and data science covering different sectors such as health care, nature, geo-information and the internet of things
· (Big) data: from data to information using the data cycle: data acquisition, storage, analysis, visualisation, actions and evaluation
· Sustainability: people, planet, profit of smart farming
· Implement the previous themes in projects intended for different stakeholders
Why sign up for his course?
You will be prepared for the future of Smart Farming by:
· working in a multidisciplinary project
· looking at technical and biological aspects;
· handling the complex data cycle;
· being inspired by innovative precision technology;
· following a diverse program of (guest)lectures from experts;
· developing your talents and show your fellow students your own field of expertise
You will be able to:
1. Describe current precision techniques from different sectors and the application in your own field of expertise
2. Use the data analysis cycle in a specific field
3. Determine the relevance of each step in the data cycle
4. Evaluate the relevance of the end result of the data cycle for sustainable development
5. Reflect on one’s progress in knowledge and skills in the field of smart farming and multidisciplinary team work
- Cooperative learning and peer teaching – learn from each other
- Field trips – see current and future practices
- Guest lectures – learn from experts
- Project based learning – work on real-life projects for a company or organisation
- Practical training – learn to work with sensors and data
- Contribute to online educational resources – design course material for fellow students
To participate in this minor, you must have completed your first year and have earned at least 40 ECTS in your second year.
This minor is suitable for students with an affinity for farming (crop or livestock) or for a green environment. In addition, they should be interested in technology, data and big data.
lectures, practical training and assessment 50%
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