WM380-15 Internet of Things
Introductory description
WM380-15 Internet of Things
Module aims
This module introduces the concept, implementation and applications of digitally enabled objects that can transfer data over a network without requiring human-to-human or human-to-computer interaction.
The potential of Internet of things (IoT) in various use cases such as industrial context (also known as Industrial IoT or IIoT) smart cities and smart homes for automating specific tasks such as industrial machine control, self-diagnostics in machines, control of domestic appliances and predictive maintenance will be introduced. Different IoT systems architecture will be taught to acquire and process data using hardware kits such as Raspberry Pi, microcontrollers and energy monitors.
Outline syllabus
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
Introduction of IoT ecosystem and architecture
--- IoT reference architecture
--- Utilised protocols in IoT
--- System and network design approaches and use cases
IoT-enabled network elements
--- Sensors and actuators
--- Smart nodes
--- Legacy nodes and hybrid use cases
Network architecture (carriers & services)
--- Last mile wired/wireless connections
--- Local networks
--- The internet
--- Edge/Fog
--- IoT cloud platforms
IoT-related Configurations
--- Addressing schemes
--- IoT registration and IoT gateways
--- Local and remote IoT servers
--- Security and other special topics
--- On-Going IoT Operations
Learning outcomes
By the end of the module, students should be able to:
- Identify the main IoT system components, IoT ecosystem and IoT network design principles
- Assess where the IoT concept fits within various use cases such as smart cities/homes, the industry (Industry 4.0) and future trends
- Demonstrate various network protocols used in IoT and know the key wireless technologies used in IoT systems, such as WiFi, 6LoWPAN, Bluetooth and ZigBee.
- Analyse and compare the link between IoT, big data, cloud computing and data analytics
- Design an IoT system/network composed of sensors/actuators, data processing units, wireless and backhaul networks and their implementation wherever possible
Indicative reading list
- D. N. Serpanos, “Internet of things (IoT) systems: architectures, algorithms and methodologies”, Springer, 2018, ISBN : 9783319697154.
- M. De Saulles, “The internet of things and business”, Routledge, 2017, ISBN: 9781315537849.
- J. Mongay Batalla, “Beyond the Internet of things; everything interconnected”, Springer, 2017, ISBN: 9783319507583.
- R. R. Yager, “New advances in the Internet of things”, Springer, 2018, ISBN: 9783319581903.
Subject specific skills
IoT System Design;
Corresponding Software Development;
Corresponding Technical Documentation;
Transferable skills
Team working;
Problem solving;
Critical thinking;
Digital literacy;
Study time
| Type | Required |
|---|---|
| Lectures | 18 sessions of 1 hour (15%) |
| Seminars | 5 sessions of 1 hour (4%) |
| Tutorials | 2 sessions of 1 hour (2%) |
| Practical classes | 5 sessions of 1 hour (4%) |
| Work-based learning | 32 sessions of 1 hour (27%) |
| Private study | 56 hours (47%) |
| Total | 118 hours |
Private study description
Self-study (to include exam revision, report writing, software exercises).
Costs
No further costs have been identified for this module.
You must pass all assessment components to pass the module.
Assessment group A1
| Weighting | Study time | Eligible for self-certification | |
|---|---|---|---|
| Project | 100% | 32 hours | No |
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This project is linked with the materials delivered in the module “Internet of Things” and: |
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Feedback on assessment
Feedback given as appropriate to the assessment type:
- verbal feedback given during seminar/tutorial sessions
- formative feedback on the individual contributions
- written feedback on the final group reports
Courses
This module is Core for:
- Year 2 of DWMS-H655 Undergraduate Digital and Technology Solutions (Cyber) (Degree Apprenticeship)
- Year 2 of DWMS-H652 Undergraduate Digital and Technology Solutions (Data Analytics) (Degree Apprenticeship)
- Year 2 of DWMS-H653 Undergraduate Digital and Technology Solutions (Network Engineering) (Degree Apprenticeship)
- Year 2 of DWMS-H654 Undergraduate Digital and Technology Solutions (Software Engineering) (Degree Apprenticeship)