ECE5704 · Smart sensors and embedded systems

Overview

Start your exploration into embedded systems and their pivotal role in shaping the Internet of Things (IoT) with this comprehensive unit. Gain a profound understanding of how embedded systems are applied in IoT, with a particular focus on integrating smart sensors. You will learn to design state-of-the-art embedded systems specifically tailored for a wide range of IoT applications, including smart environments and homes. Furthermore, you will explore techniques to optimise power consumption in smart sensor nodes, equipping you with the knowledge needed for energy-efficient IoT implementations. Through hands-on labs and projects, you will personally develop the essential software and hardware components required to demonstrate IoT-enabled embedded systems, ensuring they meet specific requirements and constraints. By the course's conclusion, you'll be well-prepared to harness the potential of embedded systems in IoT and contribute to the ongoing revolution in smart technology innovation.

Areas of study: E6013 Master of Applied Engineering - Specialisation: IoT systems and technologies

Offerings

Assessment

The Handbook lists an examination for this unit.

Continuous assessment: 50% Final assessment: 50% This unit contains a hurdle requirement that you must achieve to be able to pass the unit. You are required to achieve at least 45% in the total continuous assessment component and at least 45% in the final assessment component. The consequence of not achieving a hurdle requirement is a fail grade (NH) and a maximum mark of 45 for the unit.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

The Handbook lists no prerequisite, corequisite or prohibition for this unit.

Learning outcomes

1. Describe the application of embedded systems in smart sensor technologies for IoT.
2. Construct smart sensor-integrated embedded systems for use in IoT cases such as smart environments and homes.
3. Investigate energy-efficient techniques to optimise power consumption for smart sensor nodes in IoT applications.
4. Construct necessary software and hardware to demonstrate IoT-enabled embedded systems described with a set of requirements or constraints.

Workload

The minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of 3-6 hours of scheduled learning activities and 6-9 hours of independent study per week. Scheduled activities may include a combination of teacher-directed learning, peer-directed learning and online engagement. Independent study may include associated readings, assessment and preparation for scheduled activities.

Student experience, not official rules. Nothing here changes what the Handbook says.