ENCE361-26S1 (C) Semester One 2026

Embedded Systems 1

15 points

Details:
Start Date: Monday, 16 February 2026
End Date: Sunday, 21 June 2026
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 1 March 2026
  • Without academic penalty (including no fee refund): Sunday, 10 May 2026

Description

Embedded Systems is the study of specialised computer hardware, such as microcontrollers, programmed to perform a series of tasks, typically using a high-level language such as C, and targeted towards dedicated applications.

This course aims to provide students with the essential knowledge of dedicated computer hardware and help students acquire, through the involvement in a practical group project, the software and interfacing skills to ensure key competencies for the design, implementation, testing and debugging of an application embedded system over an advanced low-power microcontroller.

• Design, build, test and debug an embedded system on an advanced low-power microcontroller through utilising peripherals, confirming to system specifications in a team environment.
• Account for the hardware and software interfaces, design requirements and constraints in the development of a real-time embedded application.
• Program an embedded system through algorithm design, C language coding and software modularisation for a real-time embedded application.
• Use a commercial high-level toolchain to locate and fix program bugs.
• Collaborate with a project team and communicate the design and testing outcomes in written form.

Learning Outcomes

  • At the conclusion of this course, you should be able to:

  • LO1: Analyse the CPU load, interrupt latency, potential race conditions and data processing latency under various task scheduling kernels and system designs. (WA1, WA2)

  • LO2: Identify and tailor hardware and software interfaces to meet design requirements and constraints of real-time embedded systems on data collection and human-computer interaction. (WA1, WA2, WA3, WA4)

  • LO3:  Design and apply low-complexity signal processing methods to realise data buffering, noise attenuation and feature extraction for real-time embedded applications. (WA1, WA2, WA3, WA4)

  • LO4: Identify, locate and fix program bugs through gathering experimental data, interpreting the results and drawing reasoned conclusions with the help of a commercial high-level toolchain.  (WA1, WA2, WA3, WA4, WA5)

  • LO5: Design, build and test a practical real-time embedded system over an advanced low-power microcontroller in a team environment, and communicate the design and testing results using written reports. (WA3, WA4, WA5, WA8, WA9)
    • University Graduate Attributes

      This course will provide students with an opportunity to develop the Graduate Attributes specified below:

      Critically competent in a core academic discipline of their award

      Students know and can critically evaluate and, where applicable, apply this knowledge to topics/issues within their majoring subject.

      Employable, innovative and enterprising

      Students will develop key skills and attributes sought by employers that can be used in a range of applications.

Prerequisites

Timetable 2026

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Monday 10:00 - 11:00 A1 Lecture Theatre
16 Feb - 29 Mar
20 Apr - 31 May
Lecture B
Activity Day Time Location Weeks
01 Tuesday 10:00 - 11:00 A1 Lecture Theatre
16 Feb - 29 Mar
20 Apr - 31 May
Lecture C
Activity Day Time Location Weeks
01 Thursday 13:00 - 14:00 A1 Lecture Theatre
16 Feb - 29 Mar
20 Apr - 31 May
Lab A
Activity Day Time Location Weeks
01 Monday 13:00 - 15:00 Elec 210 Electronics Lab (16/2-23/3, 20/4-25/5)
Elec 204 ESL Lab (16/2-23/3, 20/4-25/5)
16 Feb - 29 Mar
20 Apr - 31 May
02 Thursday 14:00 - 16:00 Elec 210 Electronics Lab (19/2-26/3, 23/4-28/5)
Elec 204 ESL Lab (19/2-26/3, 23/4-28/5)
16 Feb - 29 Mar
20 Apr - 31 May
03 Tuesday 12:00 - 14:00 Elec 210 Electronics Lab (17/2-24/3, 21/4-26/5)
Elec 204 ESL Lab (17/2-24/3, 21/4-26/5)
16 Feb - 29 Mar
20 Apr - 31 May

Examinations, Quizzes and Formal Tests

Test A
Activity Day Time Location Weeks
01 Tuesday 19:00 - 20:00 E8 Lecture Theatre
23 Mar - 29 Mar
02 Tuesday 19:00 - 20:00 Rata 222 & 223 Drawing Office
23 Mar - 29 Mar
03 Tuesday 19:00 - 20:00 E6 Lecture Theatre
23 Mar - 29 Mar

Course Coordinator

Le Yang

Lecturers

Ciaran Moore and Lui Holder Pearson

Tutor

Fredy Youssif

Assessment

Assessment Due Date Percentage 
Project Milestone 1 3%
Test 20%
Project Milestone 2 5%
Project Demo 15%
Project Code 10%
Project Report 7%
Final Exam 40%

Textbooks / Resources

Recommended Reading

C. Noviello; Mastering STM32 ; 2nd; 2024.

J. Yiu; The Definitive Guide to ARM Cortex-M0 and Cortex-M0+ Processors ; 2nd Edition; Elsevier Science & Technology, 2015.

Lacamera, Daniele; Embedded systems architecture : explore architectural concepts, pragmatic design patterns, and best practices to produce robust system ; Packt, 2018.

P. Warden and D. Situnayake; TinyML: Machine Learning with TensorFlowLite on Arduino and Ultra-Low-Power Microcontrollers ; O'Reilly, 2020.

Simon, David E; An embedded software primer ; Addison Wesley, 1999.

White, Elecia; Making embedded systems : design patterns for great software ; O'Reilly Media, 2012.

Additional Course Outline Information

Academic integrity

Scaling of marks
In order to maintain consistency across courses and fairness for students, scaling of raw marks occurs. In the Faculty of Engineering, target course GPAs are calculated based on the performance of the cohort of students in their courses in the previous year. Scaling of the raw total course marks is normally performed so that when converted to grades (using UC Grade Scale) the outgoing GPA is in line with the target GPA for a course. Scaling up or down can occur. The Grading Scale for the University can be found in
https://www.canterbury.ac.nz/study/study-support-info/study-related-topics/grading-scale.

Artificial Intelligence Tools
The use of Artificial Intelligence (AI) tools for each of the assessments in ENCE361 is summarised below. No AI use is allowed in the tests and exam because these are closed-book invigilated assessments. Students are always responsible for the accuracy of the submitted works, regardless of which tools are used.

Assessment Item and Permitted use of AI

Labs, demo and code:  Generative AI tools are not restricted for this assessment.

Project report: Generative AI Tools Are Permitted for Certain Parts of This Assessment

Test: Generative AI tools cannot be used for this assessment.

Exam: Generative AI tools cannot be used for this assessment.

Generative AI Tools Are Permitted for Certain Parts of This Assessment
In these assessments (Project Report), you are permitted to use generative artificial intelligence (AI) for the purpose of proof reading and editing the document, and for gathering and summarising knowledge. No other use of generative AI is permitted. To assist with maintaining academic integrity, you must appropriately acknowledge any use of generative AI in your work. Please include a Statement of AI use (if no AI tool has been used, then this must also be stated) and a listing of all prompts provided to the AI tool, clearly indicating which AI tools were used and how they contributed to your assessment.

Late submission of work

Lateness Penalties
For Project Code and Report, a lateness penalty of 10% (in absolute terms) per day or part day late will be deducted from the original mark. For example, an assignment with a nominal mark of 83% submitted 0-24 hours late will receive a mark of 73% and submitted 24-48 hours late will receive 63%.

Mahi ā-Ākonga | Workload (expected distribution of student hours, note 15 points = 150 hours):

Contact Hours

Lectures: 36 hours
Tutorials: 0 hours
Workshops: 0 hours
Laboratories: 60 hours

Independent study

Review of lectures: 36 hours
Test and exam preparation: 18 hours
Assignments: 0 hours
Tutorial preparation: 0 hours
Laboratory calculations: 0 hours

Total 150

Mahi ā-Ākonga | Workload (expected distribution of student hours, note 15 points = 150 hours):

Contact Hours

Lectures: 36 hours
Tutorials: 0 hours
Workshops: 0 hours
Laboratories: 60 hours

Independent study

Review of lectures: 36 hours
Test and exam preparation: 18 hours
Assignments: 0 hours
Tutorial preparation: 0 hours
Laboratory calculations:0 hours

Total 150

Indicative Fees

Domestic fee $1,190.00

International fee $6,488.00

* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.

For further information see Electrical and Computer Engineering .

All ENCE361 Occurrences

  • ENCE361-26S1 (C) Semester One 2026