Unit Outline

Internet of Things (IoT) is rising set of technologies that provides access to a large quantity of data through sensors. Such devices are ubiquitous today in industrial processes, vehicles, robots, environmental monitoring, farms, hospitals, and on our personal item such as phones. IoT enables users to visualize, monitor, analyse and predict aspects of their environments that would otherwise be impossible to do manually. The ability to connect devices to the internet allows humans to have access to data in real time. Large amount of data collected over time can lead to discovery of specific patterns using machine learning and artificial intelligence which could in turn lead to improvement of the system, the IoT is observing. Many standard technologies have been developed to empower IoT, such as low-cost micro-controllers and communication mechanisms which impacts the development of distributed and intelligent IoT applications. The aim of this unit is to explore modern technologies surrounding sensor networks with intelligent edge computing in context of IoT. This unit will refine critical thinking and skills when considering Internet of things applications. Also, based on practical field components such as micro-controllers, you will develop the skills to process the data generated in a distributed manner from IoT using Artificial Intelligence and Machine Learning methods

Intended Learning Outcomes

As per the Assessment and Results Policy 1.3, your results will reflect your achievement against specified learning outcomes.

On completion of this unit, you will be able to:


1.	Build IoT using sensor networks and technology
2.	Design, build and deploy efficient sensor networks fit for purpose.
3.	Determining the correct technologies such as software architectures and data formats for IoT applications.
4.	Analyse the data from sensor networks using artificial intelligence and machine learning methods.

Requisites


REQUISITE TYPE	REQUISITES
Pre-requisite	KIT205 OR KIT206 OR KIT202

Alterations as a result of student feedback

Assessment tasks revised.

Teaching arrangements


ATTENDANCE MODE	TEACHING TYPE	LEARNING ACTIVITY	CONTACT HOURS	FREQUENCY
On Campus	Lecture (Online)	A real-time (i.e. synchronous) interactive activity involving the whole class whose primary purpose is the presentation and structuring of information/ideas/skills to facilitate student learning. All students are expected to attend.	2	Weekly
On Campus	Tutorial	A structured real-time (i.e. synchronous) activity in a small-group setting where the primary purpose is the clarification, exploration or reinforcement of subject content presented or accessed at another time or place (e.g. lecture, preparatory work). It is reliant on student-teacher and student-student interaction and dialogue for the achievement of its learning outcomes. The students enrolled in the tutorial are expected to attend.	2	Weekly

Attendance / engagement expectations

If your unit is offered On campus, it is expected that you will attend all on-campus and onsite learning activities. This is to support your own learning and the development of a learning community within the unit. If you are unable to attend regularly, please discuss the situation with your course coordinator and/or our UConnect support team.

If your unit is offered Online, it is expected you will engage in all those activities as indicated in the Unit Outline, including any self-directed learning.

If you miss a learning activity for a legitimate reason (e.g., illness, carer responsibilities) teaching staff will attempt to provide alternative activities (e.g., make up readings) where it is possible.

How will I be Assessed?

For more detailed assessment information please see MyLO.

Assessment schedule


ASSESSMENT TASK #	ASSESSMENT TASK NAME	DATE DUE	WEIGHT	LINKS TO INTENDED LEARNING OUTCOMES
Assessment Task 1:	Assignment 1: Basic Sensor Programming with Web Authentication	Week 6	20 %	LO1, LO2, LO3, LO4
Assessment Task 2:	Assignment 2: Faulty sensor detection	Week 10	25 %	LO2, LO3, LO4
Assessment Task 3:	Assignment 3: Intelligent IoT system	Week 14	25 %	LO1, LO2, LO3, LO4
Assessment Task 4:	Workshop Exercises	Refer to Assessment Description	10 %	LO1, LO2, LO3, LO4
Assessment Task 5:	Quizzes (x2)	Refer to Assessment Description	20 %	LO1, LO2, LO3, LO4

Assessment details

Assessment Task 1: Assignment 1: Basic Sensor Programming with Web Authentication

Task Description:

Assignment 1: Programming with sensors and clouds.
Students will be required to configure and program sensors to store data using the correct formats.

Task Length:

5 weeks Code and File submission via MyLO

Due Date:

Week 6

Weight:

20 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Configure and program sensors	LO1, LO2
2	Store data using correct formats	LO3, LO4
3	Demonstrate the operation of different sensors	LO3

Assessment Task 2: Assignment 2: Faulty sensor detection

Task Description:

Assignment 2: Students will be given sensor and sensor data to classify between proper functioning and faulty behavior with machine learning algorithms.

Task Length:

4 weeks Code and File submission via MyLO

Due Date:

Week 10

Weight:

25 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Successful demonstration of data analysis	LO2, LO4
2	Successful demonstration of behavior detection	LO2, LO3

Assessment Task 3: Assignment 3: Intelligent IoT system

Task Description:

Assignment 3: Analysing real-time Data

Students will analyze data sets generated or collected and create a responsive IoT web application.

Task Length:

4 weeks Code and File submission via MyLO

Due Date:

Week 14

Weight:

25 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Design Website to display data from IoT sensor network	LO2, LO3
2	Store data using correct formats	LO1, LO3
3	situation detection and decision making based on data	LO3, LO4

Assessment Task 4: Workshop Exercises

Task Description:

Students are to participate in the workshop tasks in which their completion of the task will be assessed.

Task Length:

To be completed during the Workshop

Due Date:

Refer to Assessment Description

Weight:

10 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Configure and program sensors	LO1, LO2
2	Store data using correct formats	LO3, LO4
3	Connect device to internet	LO2

Assessment Task 5: Quizzes (x2)

Task Description:

Students will complete 2 Quizzes for this unit that will focus on the theory delivered from the lectures of the unit.

Quiz 1 will be administered in Week 7 (on content up to Week 6). Quiz 2 will be administered in Week 13 (on contents in Week 7-12).

How your final result is determined

To pass this unit, you need to demonstrate your attainment of each of the Intended Learning Outcomes, achieve a final unit grade of 50% or greater, and pass any hurdle tasks.

Submission of assignments

Where practicable, assignments should be submitted to an assignment submission folder in MYLO. You must submit assignments by the due date or receive a penalty (unless an extension of time has been approved by the Unit Coordinator). Students submitting any assignment in hard copy, or because of a practicum finalisation, must attach a student cover sheet and signed declaration for the submission to be accepted for marking.

Requests for extensions

If you are unable to submit an assessment task by the due date, you should apply for an extension.

A request for an extension should first be discussed with your Unit Coordinator or teaching support team where possible. A request for an extension must be submitted by the assessment due date, except where you can provide evidence it was not possible to do so. Typically, an application for an extension will be supported by documentary evidence: however, where it is not possible for you to provide evidence please contact your Unit Coordinator.

The Unit Coordinator must notify you of the outcome of an extension request within 3 working days of receiving the request.

Late penalties

Assignments submitted after the deadline will receive a late penalty of 5% of the original available mark for each calendar day (or part day) that the assignment is late. Late submissions will not be accepted more than 10 calendar days after the due date, or after assignments have been returned to other students on a scheduled date, whichever occurs first. Further information on Late Penalties can be found on the Assessments and Results Procedure.

Review of results and appeals

You are entitled to ask for a review of the marking and grading of your assessment task if there is an irregularity in the marking standards or an error in the process for determining the outcome of an assessment. Details on how to request a review of a mark for an assignment are outlined in the Review and Appeal of Academic Decisions Procedure.