module specification

CS7080 - 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 Masters (07)
Credit rating for module 20
School School of Computing and Digital Media
Total study hours 200
 
48 hours Scheduled learning & teaching activities
52 hours Assessment Preparation / Delivery
100 hours Guided independent study
Assessment components
Type Weighting Qualifying mark Description
Coursework 50%   Individual-based, consisting of a written research 2500 words report into an agreed student-selected research topic
Group Coursework 50%   Group-based research 3000 words report plus Implementation code, involving analysis, design, development, programming
Running in 2024/25

(Please note that module timeslots are subject to change)
Period Campus Day Time Module Leader
Spring semester North Thursday Afternoon

Module summary

This module provides students with an in-depth appreciation of the Internet of Things (IoT) and Cloud Computing concepts, models, infrastructures, and capabilities. The module will place emphasis on modern system architecture and design, Autonomous Intelligent Systems (AIS), key wireless/mobile/sensor technologies, and issues of privacy and trust, in the development of Cloud-based IoT systems. Practical work within the module will provide students with real, hands-on, experience of building a basic Internet of Things infrastructure that can access Cloud Computing services and the opportunity to develop their Python programming skills and abilities. Some basic knowledge of Python will be used throughout. Understanding of various Intelligent, wired, and wireless technologies could be an advantage.

Prior learning requirements

N/A

Syllabus

1. Internet of Things (IoT) – Principles, Fundamentals and Business Context
2. Cloud Computing – Architecture: Infrastructure, Platforms and Software
3. Electronics, Sensors/Actuators, Arduino, and Raspberry Pi
4. IoT Hardware Development Boards and App Development Platforms
5. Machine to Machine (M2M) Radio Frequency Communications
6. Network Security Challenges and RF Protocol Stacks
7. Application Protocols
8. Autonomous Intelligent Systems (AIS), Connected and Autonomous Vehicles (CAVs)
9. Operationalizing Data Analytics and ML Pipelines
10. Data Space Support in Data Platform
11. Current Research within Cloud Computing and IoT
12. Module Overview

Balance of independent study and scheduled teaching activity

Teaching activity will be a combination of formal lectures and practical workshops. Concepts and theoretical background and context will be delivered and discussed during the lectures. Competency of software and hardware tools will be gained during the workshop sessions, which will be conducted within the Cyber Security Research Centre.

Learning outcomes

LO1 Design and critically assess the strengths and weaknesses of different IoT system architectures and components, showing understanding of their key features, including (passive and active) sensors, actuators, physical communications layer, message protocols, programming frameworks, and energy and bandwidth constraints
LO2 Apply extensive hands-on application development skills for building multi-tier cloud-based IoT systems as members of a development team and evaluate the strengths and weaknesses of different types of cloud-based architectures
LO3 Express a critical understanding of current research areas associated with the Internet of Things, Cloud Computing and Autonomous Intelligent Systems (AIS), including the commercial context and any privacy/security issues, legal, social, ethical, and professional issues related to the design, development, and implementation of Cloud Computing and IoT technologies and systems
LO4 Apply broad skill in writing professional reports as vehicles for communicating research ideas
LO5 Demonstrate ability for professional presentation, delivery, and peer assessment of research work

Bibliography