Course Title: Wireless Sensor Networks and the Internet of Things

Part A: Course Overview

Course Title: Wireless Sensor Networks and the Internet of Things

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

EEET2370

City Campus

Undergraduate

125H Electrical & Computer Engineering

Face-to-Face

Sem 2 2011,
Sem 2 2012,
Sem 2 2013,
Sem 2 2014,
Sem 2 2015,
Sem 2 2016

EEET2370

City Campus

Undergraduate

172H School of Engineering

Face-to-Face

Sem 2 2017

EEET2371

City Campus

Postgraduate

125H Electrical & Computer Engineering

Face-to-Face

Sem 2 2011,
Sem 2 2012,
Sem 2 2013,
Sem 2 2014,
Sem 2 2015,
Sem 2 2016

EEET2371

City Campus

Postgraduate

172H School of Engineering

Face-to-Face

Sem 2 2017,
Sem 2 2018

Course Coordinator: Dr Akram Hourani

Course Coordinator Phone: +61 3 9925 9640

Course Coordinator Email: akram.hourani@rmit.edu.au

Course Coordinator Location: 12.08.14

Course Coordinator Availability: By appointment


Pre-requisite Courses and Assumed Knowledge and Capabilities

It is recommended that you have successfully completed EEET2096 Embedded System Design and Implementation and EEET2290 Network Engineering and EEET2254 Communication Engineering 1 or equivalent. This is not an enforced pre-requisite.

It will be assumed that you have C/C++ programming experience, Matlab and have fundamental knowledge of TCP/IP networks, wireless networks and electronics.


Course Description

An Internet-of-Things network generally consists of compact low power sensors, which collect information and pass the information via wireless networks to achieve a high level of desired monitoring and control in coordinated manners. Designing IoT systems requires integrated skills in network engineering, embedded system engineering, wireless networks and cloud computing. IoT applications can be found in areas such as environmental monitoring, smart energy systems, industry and home automation, agriculture and in smart cities.  

This course covers the fundamentals of IoT systems with emphasis on translating theoretical bases into practical network design and technologies. It covers the bigger picture of IoT systems with a focus on wireless IoT technologies, network design, system architecture and hardware implementation, where you will be developing small-scale IoT networks and devices in the laboratory.

After completing this course you should understand the principle, technologies and applications of IoT systems and be able to design an IoT network and develop related hardware.

Contents of the course:

  • IoT applications and architecture
  • Wireless access technologies and design for IoT networks
  • Implementation and requirements for of IoT devices
  • IoT networks and platforms


Objectives/Learning Outcomes/Capability Development

At undergraduate level this course develops the following Program Learning Outcomes:

1.3 In-depth understanding of specialist bodies of knowledge within the engineering discipline.

2.1 Application of established engineering methods to complex engineering problem solving.

2.2  Fluent application of engineering techniques, tools and resources

3.2. Effective oral and written communication in professional and lay domains.

3.6. Effective team membership and team leadership.

At postgraduate level this course contributes to the following Program Learning Outcomes:

  1. High levels of technical competence in the field
  2. Be able to apply problem solving approaches to work challenges and make decisions using sound engineering methodologies
  3. Be able to apply a systematic design approach to engineering projects and have strong design and research skills in the chosen discipline specialisation
  4. Communicate effectively across all modes: listen, speak, write and draw
  5. Balance the technical, economic, social and ethical demands of a problem in sustainable and culturally sensitive ways.


On completion of this course you should be able to:

  1. Apply the knowledge of Internet-of-Things (IoT) technologies to various application areas.
  2. Design and implement IoT wireless networks
  3. Undertake embedded systems development for IoT devices and IoT platforms
  4. Conduct performance analysis of IoT systems.
  5. Formulate and solve problems creatively in the areas of IoT.


Overview of Learning Activities

Student Learning occurs through the following experiences and evaluation processes:

  • Lectures that provide guided learning of key topics.
  • Self-paced learning using reference material as a guide.
  • Mid-Semester test and quizzes
  • Laboratory based assignments and a mini project to explore specific topics in depth.

Laboratory practice-based assignments are used to assess the understanding of concepts and basic skills of IoT application and embedded system design and development.

The mini project is on IoT system development and is used to apply students’ knowledge in developing a small-scale IoT network catering for realistic industry scenarios. The mid-semester test and quizzes will keep the students engaged throughout the semester and will provide opportunity for the early rectification of learning gaps. The final exam is for the overall assessment of understanding IoT concepts and design principles


Overview of Learning Resources

Course information and learning materials (lecture notes, laboratory guide, lists of relevant reference texts and free online resources) are provided through RMIT University’s online systems. Student will also use state-of-the-art laboratory equipment and computer software within the school during the laboratory practice and the mini project.

Recommended reference texts include:

  • D. Hanes et al. “IoT Fundamentals: Networking Technologies, Protocols, and Use Cases for the Internet of Things” Published Jun 2017 by Cisco Press. ISBN: 9781587144561
  • O. Liberg et al. “Cellular Internet of Things: Technologies, Standards, and Performance”, September 2017, published by Academic Press. ISBN: 9780128124581

 


Overview of Assessment

☒ This course has no hurdle requirements.

 

Assessment Task 1: Laboratory practices (Demo and Reports) and Mini-project (Demo, Report, Presentation)
Weighting 30%
This assessment task supports CLOs 1,2,3,4,5

Assessment Task 2: Mid-Semester Test and Quizzes
Weighting 20%
This assessment task supports CLOs 1,2,4,5

Assessment Task 3: Final Exam 
Weighting 50%
This assessment task supports CLO 1,2,4,5