Outline

Overview

This unit aim to teach the fundamentals concepts associated with: 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

Type	Description	Weight	Due	Length
Assignment	Project report 1 Topic and plan	5%	Week 03	1 page
Outcomes assessed:
Presentation	Literature review and project overview Individual presentation on literature review and project overview	5%	Week 06	5 mins + 2 mins Q&A
Outcomes assessed:
Assignment	Project report 2 Literature review report	10%	Week 06	>=3 pages, and 30 references
Outcomes assessed:
Assignment	Lab work 1 by the end of wk6, the students need to hand in one lab report	15%	Week 07	maximum 5 pages / wk1-wk6
Outcomes assessed:
Assignment	Project report 3 Progress report	5%	Week 09	2 pages
Outcomes assessed:
Assignment	lab work 2 at the end of wk 12, the students need to submit one project report	25%	Week 12	maximum 5 pages / wk 7-wk12
Outcomes assessed:
Presentation	Project findings presentation Individual presentation of your project findings	5%	Week 12	10 mins + 5 mins Q & A
Outcomes assessed:
Assignment	Final project report project programming, presentation and report	30%	Week 12	5xA4 pages
Outcomes assessed:
= 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 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.

Learning support

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.

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction in networked embedded systems: what is a NES? Examples and applications	Lecture (2 hr)
Week 02	Network embedded systems: fundamental	Lecture (2 hr)
Week 03	1. Sensor principle; 2. Energy efficient WSN	Lecture (2 hr)
Week 04	1. Digital communication; 2. Bluetooth; 3. ZigBee	Lecture (2 hr)
Week 05	Networking	Lecture (2 hr)
Week 06	Distributed source coding for wireless sensor network	Lecture (2 hr)
Week 07	MAC issues with wireless sensor networks	Lecture (2 hr)
Week 08	MAC issues with body area networks	Lecture (2 hr)
Week 09	Routing for wireless sensor networks	Lecture (2 hr)
Week 10	Source detection & identification	Lecture (2 hr)
Week 11	Industrial IoT	Lecture (2 hr)
Week 12	1. Synchronisation; 2. Localisation and time 3. Energy management in sensor network	Lecture (2 hr)

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

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.

Outcomes
Graduate qualities

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
Learning outcomes

Responding to student feedback

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.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

ELEC5514: Networked Embedded Systems

Semester 2, 2020 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect