Availabilities:
2024 unit offering information will be available in November 2023
Unit description
Applies a systems-based engineering approach to analysis and design of smart farming systems. Students will learn about the applications of smart agriculture tools and their impacts on farming and the agricultural industry using a showcase of typical systems. A scenario-based learning approach is used to guide students in applying a range of practical tools and techniques along with skills in systems analysis, engineering design and project management to a real industry-based engineering project.
Unit content
Module 1: GPS and GIS applications in agriculture
Module 2: Remote sensing in agriculture
Module 3: Sensor technology in agriculture
Module 4: Auto-guidance and autonomous systems
Module 5: Internet of Things for agriculture
Module 6: Agricultural robotics
Learning outcomes
Unit Learning Outcomes express learning achievement in terms of what a student should know, understand and be able to do on completion of a unit. These outcomes are aligned with the graduate attributes. The unit learning outcomes and graduate attributes are also the basis of evaluating prior learning.
| On completion of this unit, students should be able to: | |
|---|---|
| 1 | employ a systems approach that integrates a detailed technical knowledge of sensor technology, Internet of Things, autonomous systems and robotics in agriculture with other relevant contextual factors to address a complex problem related to smart farming systems |
| 2 | evaluate and creatively apply advanced engineering methods, techniques, tools and resources to analyse and design solutions to a complex problem related to smart farming systems |
| 3 | select, define, successfully complete and communicate the outcomes from a complex project related to smart farming systems |
| 4 | self-assess conduct and performance as a professional engineer in contributing to the successful completion of a complex project related to smart farming systems |
On completion of this unit, students should be able to:
- employ a systems approach that integrates a detailed technical knowledge of sensor technology, Internet of Things, autonomous systems and robotics in agriculture with other relevant contextual factors to address a complex problem related to smart farming systems
- evaluate and creatively apply advanced engineering methods, techniques, tools and resources to analyse and design solutions to a complex problem related to smart farming systems
- select, define, successfully complete and communicate the outcomes from a complex project related to smart farming systems
- self-assess conduct and performance as a professional engineer in contributing to the successful completion of a complex project related to smart farming systems
Teaching and assessment
Fee information
Domestic
Commonwealth Supported courses
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Fee paying courses
For postgraduate or undergraduate full fee paying courses please check Domestic Postgraduate Fees OR Domestic Undergraduate Fees
International
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