Internet of Things and Distributed Artificial Intelligence unit (KIT317)

Introduction

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

Summary

Unit name	Internet of Things and Distributed Artificial Intelligence
Unit code	KIT317
Credit points	12.5
College/School	Sciences and Engineering School of Information and Communication Technology
Discipline	Information & Communication Technology
Coordinator	Mr Troy Merritt
Available as an elective?	Yes
Delivered By	University of Tasmania
Level	Advanced

Availability

Specific information on 2027 unit availability will be available in August

Learning Outcomes

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

Fee Information

2027 fee information will be available in August.

Requisites

Prerequisites

KIT205 OR KIT206 OR KIT202 OR (P3R students only: KIT101, KMA153, KGG102, AND KGG103)

Teaching

Teaching Pattern	On-Campus enrolments in Hobart and Launceston:  Lectures: 2 hours weekly lecture Workshops (referred to as Tutorials in the Timetable): 2 hrs/wk - For this unit, students are expected to attend on-campus tutorials;
Assessment	Workshop Exercises (10%)|Assignment 1: Basic Sensor Programming with Web Authentication (20%)|Quizzes (x2) (20%)|Assignment 2: Faulty sensor detection (25%)|Assignment 3: Intelligent IoT system (25%)
Timetable	View the lecture timetable | View the full unit timetable

Textbooks

Required	Required readings will be listed in the unit outline prior to the start of classes.

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