MEng Software Engineering

Year of entry: 2020

Course unit details:
The Internet of Things: Architectures and Applications

Unit code COMP32412
Credit rating 10
Unit level Level 3
Teaching period(s) Semester 2
Offered by Department of Computer Science
Available as a free choice unit? Yes

Overview

Augmenting objects, otherwise designed to perform a specific task, with the ability to connect to the Internet has led to a new technological paradigm called the Internet of Things (IoT). This course will introduce the students to this concept where high level tasks such as data analytics and fundamental hardware components, such as sensors and actuators are integrated to produce complex systems aimed at improving quality of life and benefit society. Considering the upcoming IoT revolution, this course unit offers a timely opportunity to familiarise yourself with the fundamental principles and primary issues that define the IoT. We put emphasis on the versatility of components that can be integrated into such systems, as well as the diversity of data types produced by the IoT edge-nodes. Successful development of IoT applications also requires communication between different levels (layers) of IoT architectures with the associated security and privacy issues.

Pre/co-requisites

Unit title Unit code Requirement type Description
Distributed Computing COMP28112 Pre-Requisite Compulsory
Students who are not from the School of Computer Science must have permission from both Computer Science and their home School to enrol.

Aims

Demystify the IoT concept. Offer insight into the IoT components and explain the different principles and the several aspects of designing the IoT architectures. The course will be focused towards the edge of the IoT that is the “Things” (i.e., the edge devices). Several IoT areas of application will be analysed, such as smart grids, home automation, and industrial IoT to demonstrate the different requirements and constraints in designing practical IoT architectures for these segments. Furthermore, the course will analyse the importance of the security, trust, and privacy issues for IoT and present techniques that address these. The course will also demonstrate the interplay and the role of diverse engineering and computer science fields that compose the IoT ecosystem.

Learning outcomes

  •  Identify the basic organization and components that underpin IoT systems.

  • Construct IoT reference architectures in step-by-step manner based on specific design principles and use-related requirements.

  • Apply a design methodology to design IoT systems from specifications to deployment.

  • Describe and compare the heterogeneous communication mechanisms supported by IoT systems at the physical and link layers.

  • Evaluate the characteristics of wireless radio channels and define the basic principles of modulating techniques used in wireless communication networks.

  • Identify the security threats at all levels of the IoT and respective security techniques used to mitigate these threats.

  • Analyse knowledge inferred from data monitoring in IoT systems to optimize smart grids.

 

Syllabus

·         Introduction and evolution of IoT (1)

·         Organisation and primary components of IoT systems (4)

o   Structure of IoT systems

o   IoT backend modules

o   IoT gateways

o   The IoT edge

·         A reference IoT architecture (3)

o   Design principles and design requirements for the reference architecture

o   Real-world constraints

·         Design issues for the IoT edge (4)

o   Sensors and actuators for IoT systems

o   Interoperability and reliability issues

o   Communication protocols and protocol stacks for the edge devices

o   Hardware security for edge devices

·         Security, trust, and privacy issues in IoT (2)

o   Identity management of IoT edge devices

·        IoT case studies (6)

o   Smart grid (2)

o   Home automation (2)

o   Industrial IoT (2)

Teaching and learning methods

Up to 20 lectures (2 hrs per week)

6 lab sessions per term combining/alternating pen & paper questions with laboratory hands on tasks.

Employability skills

Analytical skills
Innovation/creativity
Project management
Problem solving
Research
Written communication

Assessment methods

Method Weight
Written exam 70%
Practical skills assessment 30%

Feedback methods

Via questions and answers and weekly office hours

Recommended reading

COMP32412 reading list can be found on the School of Computer Science website for current students.

Study hours

Scheduled activity hours
Lectures 20
Practical classes & workshops 6
Independent study hours
Independent study 74

Teaching staff

Staff member Role
Vasileios Pavlidis Unit coordinator

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