TRC3500 · Sensors and artificial perception

Overview

The unit provides an introduction to the principles of sensing circuits and the inferential techniques required to deploy them for applications in artificial perception. We survey the components of a basic sensor’s circuit architecture in the context of a range of sensing technologies and provide hands-on practice in their construction and characterisation. Applications in biomedical technology, robotics and automation are considered alongside a theoretical framework for understanding the complexity of data collected in real-world environments. You will gain an appreciation for how decisions in circuit design and signal processing impact artificial sensation and perception in practice.

Areas of study: E3001 Bachelor of Engineering (Honours) - Specialisation: Biomedical engineering E3001 Bachelor of Engineering (Honours) - Specialisation: Robotics and mechatronics engineering Minor: Electric vehicle technology Minor: Internet of Things (IoT) Minor: Networks for connectivity Minor: Sensory systems in Industry 4.0 Minor: Smart manufacturing

Offerings

Assessment

The Handbook lists an examination for this unit.

Continuous assessment: 60% Final assessment: 40% This unit contains threshold hurdle requirements 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

Learning outcomes

1. Describe physical principles of sensing and transduction such as resistive, capacitive, inductive and piezoelectric effects.
2. Formulate signal processing pipelines for a desired I/O mapping, taking into account considerations, such as analog-to-digital conversion, sampling and filtering.
3. Analyse sources of noise in systems at the circuit, signal and inferential levels to make optimal inferences under uncertainty.
4. Construct a complete sensory system by designing and implementing hardware, embedded systems and software components.
5. Synthesise sensor and performance data to justify circuit design decisions and produce effective written and graphical summaries to communicate a sensing system's performance.

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.