module specification

CS5053 - Cloud Computing and the Internet of Things (2024/25)

Module specification Module approved to run in 2024/25
Module title Cloud Computing and the Internet of Things
Module level Intermediate (05)
Credit rating for module 15
School School of Computing and Digital Media
Total study hours 150
38 hours Assessment Preparation / Delivery
76 hours Guided independent study
36 hours Scheduled learning & teaching activities
Assessment components
Type Weighting Qualifying mark Description
Coursework 50%   Logbook + Case-Study Report (1500 words)
Unseen Examination 50%   2-hour unseen exam
Running in 2024/25

(Please note that module timeslots are subject to change)
Period Campus Day Time Module Leader
Autumn semester North Friday Morning

Module summary

This module will enable students to understand the Internet of Things (IoT) and Cloud Computing concepts, building blocks, ecosystems, infrastructure,  and  applications.  This will enrich their knowledge and understanding of the core technologies and platforms for IoT and Clouds, that allows digitally enabled  devices  or  objects  to  collect,  gather,  and  transfer  data  over  a  network  without involving human-to-human or human-to-machine interaction.

The module will place emphasis on IoT components and delivery models, IoT system architecture, key wireless/mobile/sensor technologies, IoT communication protocols, issues of privacy and trust, cloud platform, and virtualization technologies in the development of IoT cloud infrastructure and applications.

Students will be supported with a series of exercises performed using a powerful network simulation tool, that will cover the range of basic principles to more advanced IoT system design. This will allow students to get real world experience in building IoT system by integrating sensor devices and cloud for creating interconnected solutions to smart cities, homes, and enterprises.  Some basic knowledge of Python will be used throughout. By the end of the module, you will get experience in solving real-world problems (IoT and Cloud  system  implementation)  efficiently  using  simulation modelling.


1.Introduction to IoT–Theory, Evolution, Elements of an IoT Ecosystem, Applications, and Implications. [LO1]

2.Sensors & Actuators for IoT Systems. [LO1]

3.Communication Protocols and Networks–Wireless Technologies, Protocol Stacks for the Edge Devices, Wireless Sensor Networks. [LO1]

4.IoT Networking and Messaging Protocols –CoAP, MQTT, REST, AMQP, WebSocket. [LO1]

5.Cloud Computing -Architecture: Infrastructure, Virtualisation, Platforms and Software. [LO1, LO2]

6.Cloud Platform and Management for IoT–Application Development and Integration, Hardware Development Boards and Software Platforms for IoT, Issues and Challenges, Security, trust and Privacy Issues. [LO2, LO3, LO4, LO5]

7.Design a simple IoT system by integrating sensor devices, data processing units,  wireless networks, and    cloud-based    analytics    for    creating interconnected solutions. [LO1, LO2, LO3, LO4]

8.IoT Case Studies:   Industrial   IoT, Business   Impact   of   the   IoT/Cloud Computing. [LO3, LO5]

Balance of independent study and scheduled teaching activity

Teaching activity will be a combination of formal lectures, supported by tutorial and workshop sessions, and blended learning as follows:

Lecture Materials (1 hour / week): Theoretical background, underpinning principles, and concepts identified in the syllabus will be delivered and discussed during the lectures.

Tutorial/ Workshop (2 hour / week): Complementing lectures by supervised tutorial sessions to gain competency  in  application  of  these  principles  using  suitable  computational/simulation  tool. via Conducting class and group discussions for consolidating understanding of topics introduced in the lecture session.

Blended learning: Contents will be delivered using the University’s VLE and a few other online tools. Assessment and feedback will be provided, to encourage active learning, and to enhance student engagement in the learning process.

All required learning material for the module (lectures/ tutorials/ workshops/ recordings / links etc) will be available to students on University VLE (Weblearn). The module page on VLE will be continuously updated with announcements and need based additional information to ensure appropriate support for students’ learning.

Students  will be encouraged  to  provide reflective  commentaries concerning  their  action  plan  for personal  development  on  the  learning  activities  and for  the tasks  that  they  have  carried  out  to complete  the project  report e.g.,in  the  form  of a reflective  discussion/critical  analysis section  of their coursework report. Students will be encouraged to keep logbook for reflective learning and regular feedback.

Learning outcomes

On successful completion of this module, the student will be able to:

- LO1: Understand the core IoT concepts, system components, infrastructure, and applications. Understand the key components that make up an IoT system, including (passive and active) sensors, actuators, physical communications layer, and message protocols. Know the key wireless technologies used in IoT systems, such as WiFi, 6LoWPAN, Bluetooth and ZigBee.

- LO2: Evaluate the strengths and weaknesses of different types of cloud-based architectures. Analyse and critically assess the link between IoT, cloud computing, and data analytics.

- LO3: Express a critical understanding of how IoT concept fits within the industry (Industry 4.0) and future trends.  Appraise the potential of Internet of things (IoT) in  an  industrial  context  (also known as Industrial IoT or IIoT) for automating specific tasks, through drawing case studies from the industrial applications of IoT and Cloud Computing.

- LO4: Gain real world experience in designing and building a simple IoT system by integrating sensor devices, data processing units, wireless networks and  cloud-based  analytics for  creating interconnected solutions.

- LO5: Apply broad skill in writing a report as a tool to communicate the results or findings of the case studies. Gain exposure to the practice of formulating and structuring problems.