HFX315 Smart Livestock Production
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Showing course contents for the educational year starting in 2020 .
Course responsible: Marko Ocepek
Teachers: Harald Volden, Ruth Catriona Margaret Newberry, Gunnar Klemetsdal, Inger Lise Andersen
ECTS credits: 10
Faculty: Faculty of Biosciences
Teaching language: EN
(NO=norsk, EN=Engelsk)
(NO=norsk, EN=Engelsk)
Limits of class size:
60
Teaching exam periods:
This course starts in Autumn parallel. This course has teaching/evaluation in Autumn parallel.
Course frequency: Annually
First time: 2020H
Course contents:
This course explores the management of animal production systems that utilises novel digital technology and how we can use it to optimise animal production, while satisfying health, welfare, environmental and societal demands.
For these systems to be achieved and optimized, we will look into the importance of studying interrelationships between contributing factors and technology. Factors include feeding, housing and management, animal behavior and welfare, health, genetic, and overall impact on the environment. The course also covers the state-of-the-art digital monitoring and/or surveillance systems per production species (pig, cattle, chicken, sheep, goat). We will discuss the ongoing challenges of how to efficiently integrate the functions of all available on-farm systems to a smart farm-IoT (Internet of Things) and how to use the data collected by these systems, with the help of for example, AI/machine learning supported analyses.
Learning outcome:
Learning activities:
The course will assess management of animal production systems that utilises novel digital technology and how we can use it to optimise animal production, while satisfying health, welfare, environmental and societal demands. Student will also familiarize themselves with the digital monitoring and/or surveillance systems, how to efficiently integrate the functions of all available on-farm systems to a smart farm-IoT (Internet of Things), and how to use the data collected by these systems, with the help of, for example, AI/machine learning supported analyses. Course includes lectures/exercises, demonstrations of smart technology, students group work, presentations and project work.
Teaching support:
-
Syllabus:
The most recent literature, including up-to-date scientific publications related to smart animal production.
Prerequisites:
-
Recommended prerequisites:
HET201 / HET203
Mandatory activity:
Demonstrations/exercises. Course evaluations
Assessment:
The examination is a combination of assignments (30%) and exam (70%). Grading A-F
Nominal workload:
The total workload of 300 hours can be divided as follows: Lectures and course readings: 100 hours. Exercises: 30 hours. Project work with presentation: 170 hours.
Note:
The course is taught in English.
Examiner:
-
Examination details: Continuous exam: A - E / F