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Internet of Things (ELEC0033)

Key information

Faculty
Faculty of Engineering Sciences
Teaching department
Electronic and Electrical Engineering
Credit value
15
Restrictions
This module is restricted to students who have been enrolled into ELEC0032.
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

SUMMARY:
The module introduces the key concepts, technologies and applications associated with the Internet of Things (IoT). It expands students’ knowledge of basic networking concepts to introduce cutting edge IoT applications as well as tools and techniques for the design of typical IoT systems.

AIMS:
Network technologies and the communications systems that underpin them have enabled the information revolution and drive advances from the way we do business, the way we deliver healthcare and most fundamentally, changed the way we interact as human beings. This course is the third module of the IEP Minor on Connected System, which will provide students with a comprehensive coverage of these connected systems and technologies that have driven the modern world. In this last module, students will learn how to design an IoT project, developing at the technical level, but also at the business, ethical and sustainability level – all aspects equally important when designing a IoT system. Students will plan their own IoT project, designing the IoT edge, deciding the sensors and the connectivity protocols better fit the system requirements. They will then discuss the business case for the project, as well as privacy, ethics, security and sustainability of the project. Last students will familiarize with cloud processing and data wrangling and key inference methodology.

LEARNING OUTCOMES:
On completion of this course, you should be able to:
• explain the definition and usage of the term 'the internet of things' in different contexts
• be able to select the right sensors and hardware technology
• be able to select the right wireless technology for a specific IoT project
• understand privacy, security and ethical issues beyond data and data collection
• be familiar with the key data analytics algorithms used in IoT systems, such as linear regression, and logistic regression.
• be able to implement basic data analytics algorithms in the cloud
• be able to select the right data analytics algorithms for a specific IoT project
• design a simple IoT system made up of sensors, wireless network connection, data analytics and display/actuators

Module deliveries for 2024/25 academic year

Intended teaching term: Term 2 ÌýÌýÌý Undergraduate (FHEQ Level 6)

Teaching and assessment

Mode of study
In person
Methods of assessment
100% Coursework
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
28
Module leader
Mr Thomas Gilbert
Who to contact for more information
eee-ug-admin@ucl.ac.uk

Last updated

This module description was last updated on 8th April 2024.

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