TMPA230 Smart Farming Boot Camp

Credits (ECTS):5

Course responsible:Ibrahim Abdelfattah Abdelhameed

Campus / Online:Taught campus Ås

Teaching language:Engelsk, norsk

Course frequency:Anually

Nominal workload:

125 hours

of which approx. 60 hours work through the boot camp week including some preparation before the week

and 60-70 hours in order to write a full report within two months after the bootcamp week.

Teaching and exam period:

Intensive week first week in June.

Cases will be prepared, so students can get started immediately.

A complete report must be written within two months of the end of the bootcamp week.

About this course

Smart farming is highly interdisciplinary and contains areas within among other things, applied robotics, sensors, machine and tool development, collection of vital data and AI, image analysis, GIS mapping, and not least knowledge in plant, soil and fertilizer science. Students from several topic areas are invited to participate and are mixed in interdisciplinary groups, where the goal is to work actively together on concrete cases that have been announced and prepared in advance. The students go deeply into their definite area and finally present the work to the other students and the examiner. The students get a close look at advanced measuring equipment and possibilities for the digitization of Norwegian agriculture, for example by the use of drones and various cameras for mapping the existing and varying conditions in the field and how this can be optimized through site-specific dosing using VRA technology ( volume rate application). Students with different backgrounds and subject areas make the groups strong and complementary. Student innovation and active learning are emphasized. This can also provide a basis for further interdisciplinary Bachelor's or Master's theses work where different technologies can be used in different study programs & purposes of use.

Learning outcome

The student will become familiar with the most used technologies within the digitization of agriculture through hands-on teaching where the measurement methods are applied to relevant cases, preferably linked to existing projects within the area. The students will learn to work in groups with interdisciplinary students where the goal is through critical thinking and collaboration to further develop the solutions and assess what such equipment can mean for Norwegian agriculture both in the short and long term. The equipment and technology can also be used in other related areas such as forestry, greenhouses and green environments, animal husbandry in addition to conventional agriculture.

Learning activities
Work in groups with interdisciplinary subjects and knowledge levels.
Learn to collaborate, be creative and think of practical solutions for a given case.
Become familiar with advanced and new technological targeting methods and learn their strengths and weaknesses.
Present results from work to the examiner.
Listen to the other groups and learn from each other.
Finalize a full report of their work within two months after the bootcamp week.
Teaching support
Available research technical infrastructure at NMBU within the areas.
Textbooks & litterature online or by the NMBU library and other resources.
Access to results and status in ongoing relevant projects.
Technical support to ensure the equipment works
Mentors who assist the group
Each day starts with short academic presentations from professionals at NMBU in the area for all groups.
Each group then works on the selected case.
Prerequisites
No prior knowledge is required, but agronomic understanding or participation in relevant subjects is an advantage,
especially TMPA210 Precision Agriculture and Sensor Technology
possibly TMPA220 Landscape Engineering, Plant Establishment and Management
and JORD231-1 25V Fertilization planning and precision agriculture or similar courses.
But students from robotics, sensors, geomatics, image processing, computer science, mechanical engineering and so fort will also fit very well into the activities together with other interdisciplinary students with an agronomic background.
Recommended prerequisites
No prior knowledge is required, but agronomic understanding or participation in relevant subjects is an advantage,
especially TMPA210 Precision Agriculture and Sensor Technology
possibly TMPA220 Landscape Engineering, Plant Establishment and Management
and JORD231-1 25V Fertilization planning and precision agriculture or similar courses.
But students from robotics, sensors, geomatics, image processing, computer science, mechanical engineering and so fort will also fit very well into the activities. together with other interdisciplinary students with an agronomic background.
Assessment method
Examination takes place by the students presenting their group work together with the other student groups and an external examiner.
Any changes are made and a complete written report is submitted within two months of the end of the bootcamp week and evaluated by an internal examiner.
Examiner scheme
External examiner of final result at the end of the bootcamp week.
Internal examiner of final report submitted no later than two months after the end of the bootcamp week including the changes that emerge during the first external evaluation.
Mandatory activity
Active participation all days during the bootcamp period.
Solve cases in smart farming together with fellow students.
Follow the scheduled compulsory lectures (one at the start of each day)
Present the final work (could be in the form of a detailed powerpoint presentation) for an external examineer.
Review the work in a written presentation and/or show and demonstrate the final end result in another way in front of the external examiner.
Write a full report within two months after the boot camp week evaluated by internal sensor.
Notes
The first BootCamp was organized in 2024 with very successful results. It will also be run in 2025 as a special curriculum and then from 2026 as a separate subject code. Smaller adaptations will occur after the experiences that are continuously made, but such student-active learning seems to have a very good effect.
Teaching hours
30 hours of lectures.
90-100 hours of independent work and student innovation in groups with mentor support when needed
Preferential right
Students who come from the areas mentioned below have preferential rights:
TMPA210 Precision Agriculture and Sensor Technology
possibly TMPA220 Park and greenery technology, new facilities and maintenance
and JORD231-1 25V Fertilization planning and precision agriculture or similar courses.
Students from robotics, sensors, geomatics, image processing, computer science, mechanical engineering will also fit in well with the activities. together with other interdisciplinary students with an agronomic background.
Reduction of credits
No
Admission requirements
Case for the subject will vary according to current developments and possibilities at the university.
The students are divided into groups at the start of the semester