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Unit outline_

ELEC5514: IoT Wireless Sensing and Networking

Semester 2, 2024 [Normal day] - Camperdown/Darlington, Sydney

This unit aim to teach the fundamentals concepts associated with: IoT, networked Embedded Systems, wireless sensor networks; Wireless channel propagation and radio power consumption; Wireless networks, ZigBee, Bluetooth, etc. ; Sensor principle, data fusion, source detection and identification; Multiple source detection, multiple access communications; Network topology, routing, network information theory; Distributed source channel coding for sensor networks; Power-aware and energy-aware communication protocols; Distributed embedded systems problems such as time synchronization and node localisation; Exposure to several recently developed solutions to address problems in wireless sensor networks and ubiquitous computing giving them a well-rounded view of the state-of the-art in the networked embedded systems field. Student involvement with projects will expose them to the usage of simulators and/or programming some types of networked embedded systems platforms. Ability to identify the main issues and trade-offs in networked embedded systems; Understanding of the state-of-the-art solutions in the area; Based on the above understanding, ability to analyse requirements and devise first-order solutions for particular networked embedded systems problems; Familiarisation with a simulator platform and real hardware platforms for network embedded systems through the students involvement in projects.

Unit details and rules

Academic unit School of Electrical and Computer Engineering
Credit points 6
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

ELEC3305 AND ELEC3506 AND ELEC3607 AND ELEC5508

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Zihuai Lin, zihuai.lin@sydney.edu.au
Tutor(s) Tania Han, xue.han@sydney.edu.au
The census date for this unit availability is 2 September 2024
Type Description Weight Due Length
Supervised exam
? 
ELEC5514 final exam
some exam questions need to be answered
40% Formal exam period 2 hours
Outcomes assessed: LO1 LO4 LO5 LO6
Assignment group assignment Lab work 1
by the end of wk7, the students need to hand in one lab report
15% Week 08 maximum 5 pages / wk2-wk7
Outcomes assessed: LO1 LO2 LO3 LO4 LO5
Assignment group assignment lab work 2
at the end of wk 13, the students need to submit one project report
25% Week 13 maximum 5 pages / wk 8-wk13
Outcomes assessed: LO2 LO3 LO4 LO5 LO6
Attendance In-class quizzes
2 in-class quizzes, each 10 marks
20% Week 13
Due date: 04 Nov 2024 at 23:59
2 in-class quizzes, each 15 minutes
Outcomes assessed: LO1 LO4 LO5 LO6
group assignment = group assignment ?

Assessment summary

  • For lab work, the students need to hand in one lab report and one project report
  • For the project, students must submit 4 reports as per details in Canvas.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range

Description

High distinction

85 - 100

 

Distinction

75 - 84

 

Credit

65 - 74

 

Pass

50 - 64

 

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see sydney.edu.au/students/guide-to-grades.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

5 pts penalties for late submissions for both lab and first 3 project reports Late submission of final exam report is not allowed

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy 2023 reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy 2023. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

WK Topic Learning activity Learning outcomes
Week -02 Pre Lab - Introduction Science laboratory (2 hr) LO1 LO3
Week -03 Lab 1 - Serial communication between board and PC Science laboratory (2 hr) LO1 LO3 LO4
Week -04 Lab 2 - Serial Commands to board Science laboratory (2 hr) LO1 LO2 LO3 LO4 LO5
Week -05 Lab 3 - BLE Service and Commands Science laboratory (2 hr) LO2 LO3 LO4 LO5
Week 01 Introduction in networked embedded systems: what is a NES? Examples and applications Lecture (2 hr) LO1
Week 02 Network embedded systems: fundamental Lecture (2 hr) LO1 LO2
Week 03 1. Sensor principle; 2. Energy efficient WSN Lecture (2 hr) LO2 LO3
Tutorial 1 Lecture and tutorial (1 hr) LO1 LO4 LO5
Week 04 1. Digital communication; 2. Bluetooth; 3. ZigBee Lecture (2 hr) LO3 LO4 LO5
Tutorial 2 Lecture and tutorial (1 hr) LO1 LO4 LO5
Week 05 Source detection & identification Lecture (2 hr) LO4 LO5
Tutorial 3 Lecture and tutorial (1 hr) LO1 LO4 LO5
Week 06 Distributed source coding for wireless sensor network Lecture (2 hr) LO5 LO6
Lab 4 - BLE Real-time Communications Science laboratory (2 hr) LO2 LO3 LO4 LO5 LO6
Tutorial 4 Lecture and tutorial (1 hr) LO1 LO4 LO5
Week 07 MAC issues with wireless sensor networks Lecture (2 hr) LO3 LO4
Lab 5 - LoRaWAN and Gateway Science laboratory (2 hr) LO3 LO4 LO5 LO6
Tutorial 5 Lecture and tutorial (1 hr) LO1 LO4 LO5
Week 08 MAC issues with body area networks Lecture (2 hr) LO3 LO4
Lab 6 - LoRa Communications Science laboratory (2 hr) LO3 LO4 LO5 LO6
Tutorial 6 Lecture and tutorial (1 hr) LO1 LO4 LO5
Week 09 Routing for wireless sensor networks Lecture (2 hr) LO4 LO5 LO6
IoT project Project (2 hr) LO2 LO3 LO4 LO5 LO6
Tutorial 7 Lecture and tutorial (1 hr) LO1 LO4 LO5
Week 10 Networking and Network coding Lecture (2 hr) LO4 LO5 LO6
IoT project Project (2 hr) LO2 LO3 LO4 LO5 LO6
Tutorial 8 Lecture and tutorial (1 hr) LO1 LO4 LO5
Week 11 Industrial IoT, LORAWAN, NB-IoT, Sigfox Lecture (2 hr) LO2 LO4 LO5
IoT project Project (2 hr) LO2 LO3 LO4 LO5 LO6
Tutorial 9 Lecture and tutorial (1 hr) LO1 LO4 LO5
Week 12 1. Synchronisation; 2. Localisation and time 3. Energy management in sensor network Lecture (2 hr) LO4 LO5 LO6
IoT project Project (2 hr) LO2 LO3 LO4 LO5 LO6
Tutorial 10 Lecture and tutorial (1 hr) LO1 LO4 LO5
Week 13 Summary Lecture (2 hr) LO1 LO2 LO5 LO6
IoT project Project (2 hr) LO1 LO2 LO3 LO4 LO5 LO6

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. demonstrate proficiency in undertaking knowledge development, drawing on various sources and demonstrating the capacity to synthesise complex and at times contradictory information for the specific engineering projects assigned
  • LO2. write reports and make presentations to deliver technical and often complex material in clear and concise terms on specific engineering topics
  • LO3. assume diverse team roles with the purpose of working with a research paper on a specific topic in a group; exercise leadership, negotiation and receptiveness skills as a means to better draw out the knowledge and ability of other team members concomitant to one's own input
  • LO4. design a small scale wireless network using a systematic approach based on knowledge acquired and with the purpose of solving a clearly defined problem
  • LO5. demonstrate an understanding of topics in wireless sensor networks using principles developed
  • LO6. demonstrate proficiency in assessing and debugging wireless sensor networks and other system problems, using concepts and techniques developed throughout the course.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

adaptation to the 12-week semester

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.