49227 Wireless Sensor Networks
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Credit points: 6 cp
Subject level:
Postgraduate
Result type: Grade and marksRequisite(s): 120 credit points of completed study in Bachelor's Degree owned by FEIT OR 120 credit points of completed study in Bachelor's Honours Embedded Degree owned by FEIT OR 120 credit points of completed study in Bachelor's Combined Degree owned by FEIT OR 120 credit points of completed study in Bachelor's Combined Degree co-owned by FEIT OR 120 credit points of completed study in Bachelor's Combined Honours Degree owned by FEIT OR 120 credit points of completed study in Bachelor's Combined Honours Degree co-owned by FEIT
These requisites may not apply to students in certain courses. See access conditions.
Description
Internet of Things (IoT) is spawning the use of sensors that are both pervasive and ubiquitous in every aspect of our lives. Sensor technology is a key part of IoT, which is experiencing a rapid growth and is believed to be a multi-billion dollar industry. Wireless sensor networks are distributed systems, in which autonomous devices, sometimes called Motes, collect environmental data (such as location, speed, temperature, humidity and sound level) or, more recently, medical data (such as heart rate, blood oxygen level and pulse rate). This data is collected across a network, aggregated and fed into business applications. Sensor networks are an enabler for a broad range of applications in different sectors such as agriculture, healthcare, manufacturing, mining, smart cities, etc. In this subject, students will learn WSN theory and technology such as routing and security as well as hands-on skills and practical knowledge in WSN.
Subject learning objectives (SLOs)
Upon successful completion of this subject students should be able to:
| 1. | Demonstrate hands-on skills and practical knowledge in WSN through design and implementation of basic sensor networks using hardware as an enabler for applications. (C.1) |
|---|---|
| 2. | Troubleshoot a sensor network to conduct real environmental experiments and analyse sensor-produced data that can be aggregated that may feed into business applications. (D.1) |
| 3. | Apply knowledge in WSN theory and technology such as routing and security to stay up to date with the current R&D. (D.1) |
| 4. | Communicate WSN concepts to a range of audiences. (E.1) |
Course intended learning outcomes (CILOs)
This subject also contributes specifically to the development of the following Course Intended Learning Outcomes (CILOs):
- Design Oriented: FEIT graduates apply problem solving, design and decision-making methodologies to develop components, systems and processes to meet specified requirements. (C.1)
- Technically Proficient: FEIT graduates apply abstraction, mathematics and discipline fundamentals, software, tools and techniques to evaluate, implement and operate systems. (D.1)
- Collaborative and Communicative: FEIT graduates work as an effective member or leader of diverse teams, communicating effectively and operating within cross-disciplinary and cross-cultural contexts in the workplace. (E.1)
Contribution to the development of graduate attributes
Engineers Australia Stage 1 Competencies
Students enrolled in the Master of Professional Engineering should note that this subject contributes to the development of the following Engineers Australia Stage 1 competencies:
- 1.3. In-depth understanding of specialist bodies of knowledge within the engineering discipline.
- 2.2. Fluent application of engineering techniques, tools and resources.
- 2.3. Application of systematic engineering synthesis and design processes.
- 3.2. Effective oral and written communication in professional and lay domains.
Teaching and learning strategies
Lab tutorials complement classes. Students will practice new knowledge and skills they will need in the workplace such as interpersonal, time management, and communications written and oral by writing academic reports, delivering presentation and receiving detailed feedback. Improve their collaboration with peers across different areas of study by engaging in learning activities, team projects and team presentations/demonstrations. Encourage student’s multicultural collaborations inside the classroom/lab to foster the valuing and awareness of diverse perspectives (international, multicultural…) Industry-focused projects are designed to engage students in real-world challenges such as precision farming.
During lab tutorials, students will be required to work collaboratively on research inspired and Industry-focused assignments that are designed to encourage students to build their transdisciplinary and research skills. They can develop creativity and complex problem solving skills through conducting literature survey, brain storm, discuss about current challenges, generate ideas and finally propose solutions. Continuous feedback is provided in class and is critical to this teaching-learning environment. Students will integrate how they used feedback to make further progress on their work.
Lab tutorials also develop hands on skills such as programming and hardware implementation. Students are required to design and implement a sensor network using hardware (raspberry pi, sensor) and software, create a demo of their work, conduct experiments and troubleshoot the sensor network.
Classes are interactive learning environments in which students will engage with practical and real-world examples from latest theoretical and technological advances. Animations, diagrams, conversations and exercises are designed to both bring concepts to life and to offer opportunities for feedback and to encourage deeper understanding.
Learning in these interactive classes aims to prepare students for the quizzes which is designed to include learners from different backgrounds and provide students with opportunities to demonstrate how they apply their understanding of subject learning objectives. WSN aims to produce graduates ready to explore new opportunities in the future work environment.
Assessment
Assessment task 1: Design, Implementation and Documentation
| Intent: | Project Teams should provide WSN Architecture/Design and possibly a mock-up UI. Consideration should be given to use of Open Source hardware/software and COTS components (hardware toolkits, IDEs, Frameworks, DBMS, libraries, and middleware, etc.) |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2 and 4 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): C.1, D.1 and E.1 |
| Type: | Report |
| Groupwork: | Group, group and individually assessed |
| Weight: | 30% |
| Length: | Maximum 40 pages |
Assessment task 2: Project Presentation, Demonstration
| Intent: | Demonstration of the prototype WSN application. Delivery of the project's artefacts and the final report. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2 and 4 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): C.1, D.1 and E.1 |
| Type: | Demonstration |
| Groupwork: | Group, group and individually assessed |
| Weight: | 30% |
| Length: | Slides (including demos) should be prepared to deliver 10-15 minute oral presentations |
Assessment task 3: Quizzes
| Intent: | For individual students to evaluate their learning and understanding of the key concepts based on the given materials (lecture notes and handbook). |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 3 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): D.1 |
| Type: | Quiz/test |
| Groupwork: | Individual |
| Weight: | 40% |
| Length: | 15 to 30 minutes |
Minimum requirements
In order to pass the subject, a student must achieve an overall mark of 50% or more.