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BSEN30210

Academic Year 2025/2026

Precision Agriculture (BSEN30210)

Subject:
Biosystems Engineering
College:
Engineering & Architecture
School:
Biosystems & Food Engineering
Level:
3 (Degree)
Credits:
5
Module Coordinator:
Dr Dimitrios Argyropoulos
Trimester:
Spring
Mode of Delivery:
Blended
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

This module focuses on the principles and theories that underpin the concept of Precision Agriculture. Students will be introduced to the toolbox of technologies (e.g., Absolute and Relative Positioning, PC-Tractor-Implement Communication, Proximal Sensing, Machine Vision, Variable Rate Technology, Yield Mapping) that enable Precision Agriculture, and the theory of how they are used to manage spatial and temporal variability of soil and crops. The technologies will be considered in the context of Irish, European and world agriculture, and how they can be best put to use for gaining environmental and economic benefits for farmers. This module integrates gamification in teaching of Precision Agriculture as a new, futuristic learning technique. To this end, students will design, implement and evaluate their own precision agriculture use case using the Farming Simulation video game developed by GIANTS Software.

About this Module

Learning Outcomes:

Upon completion of the module, students should be able to:
- LO1: Reflect on fundamental concepts and principles of precision agriculture technologies.
- LO2: Compare and contrast the functionality of a toolbox of sensor and sensing technologies used in agricultural machinery.
- LO3: Analyse and interpret soil and crop variability data.
- LO4: Advise on how to introduce precision agriculture strategies to a farm.
- LO5: Design, implement and evaluate precision agriculture concepts using the Farming Simulator software.

Indicative Module Content:

The module content is as follows:

- Introduction to Precision Agriculture (PA)
Challenges, technologies, requirements and expectations
- Spatial variability of soils and crop plants
Understanding variability, measuring principles and visualization
- Proximal sensing and machine vision
Description, assessment and use
- Absolute and relative Positioning
GNSS, sensing and sensor fusion
- PC-Tractor-Implement Communication
International Standardization, ISOBUS interoperability, with display and terminal demonstrations
- Variable Rate Technology
Tillage, sowing, spraying, fertilisation
- Harvesting
Data logging and yield mapping
- Adoption of PA technologies
Current status, advantages, limitations and barriers
- Future Technology (Farming Simulator)
Precision - Smart - Digital Farming

Student Effort Hours:
Student Effort Type Hours
Lectures

24
Specified Learning Activities

24
Autonomous Student Learning

60
Online Learning

4
Total

112

Approaches to Teaching and Learning:
To get the maximum out of this module students should attend all lectures and complete all assignments, reports and presentations.

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Exam (Open Book): Class Test: An exam will take place at the end of the module Week 12 Graded No
60
 No
Individual Project: Students design, implement and evaluate their own Precision Agriculture use case on the Farming Simulator software Week 11 Graded No
30
 No
Assignment(Including Essay): Report on Precision Agriculture use case design Week 8 Graded No
10
 No

Carry forward of passed components
Yes
 

Resit In Terminal Exam
Autumn Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, post-assessment

How will my Feedback be Delivered?

Feedback individually to students, post-assessment if requested.

Brett Whelan, James Taylor (2013). Precision agriculture for grain production systems.
or
Hermann J. Heege (2013). Precision in Crop Farming.

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Spring Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Wed 11:00 - 12:50
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