Module manager: Dr Maryam Hafeez
Email: m.hafeez@leeds.ac.uk
Taught: Semesters 1 & 2 (Sep to Jun) View Timetable
Year running 2025/26
This module is not approved as a discovery module
This module provides an introduction to core aspects of Internet-of-Things (IoT) technologies. The module is tailored to develop students' knowledge and skills in the development of IoT systems. The principles, techniques and tools of networking and communications, edge computing and other core aspects of IoT systems are studied.
This module has the following objectives:
- To understand the principles, techniques and tools of networking and communications, edge computing and other core aspects of IoT systems.
- To gain knowledge and skills in the development of IoT systems.
- To develop a good grasp of technical aspects of IoT including different devices, platforms and computing tools which are essential for the development of IoT systems.
On successful completion of the module students will have demonstrated the following learning outcomes:
1. Apply knowledge of mathematics, statistics, natural science and engineering principles to the solution of broadly-defined internet-of-things problems.
2. Apply appropriate computational and analytical techniques to model broadly-defined internet-of-things problems.
3. Apply an integrated or systems approach to the solution of broadly-defined internet-of-things problems.
4. Select and apply appropriate materials, equipment, engineering technologies and processes.
Skills Learning Outcomes
On successful completion of the module students will have demonstrated the following skills:
a) Application of science, mathematics and/or engineering principles
b) Application of computational and analytical techniques
c) Integrated systems approach
d) Technical awareness of engineering materials, equipment, technologies, and processes
- Introduction to Sensors and Sensor Signal Processing
- Introduction to Internet-of-Things and Industrial IoT
- Introduction to Wireless Communication
- Networking and Connectivity for the IoT
- IoT Solution Design Choices
- Practical Deployment Challenges
- Inference and Intelligence on Sensed Data
- Introduction to Edge Computing
- Edge Platform and Frameworks
- Edge Artificial Intelligence (EdgeAI) and Devices
- Emerging Trends and Technologies for EdgeAI
- Visualisation and Dashboards
- Cloud Computing and Digital Twins
- End-to-End System Design
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Consultation | 12 | 1 | 12 |
| Lecture | 12 | 2 | 24 |
| Practical | 12 | 2 | 24 |
| Seminar | 3 | 2 | 6 |
| Independent online learning hours | 54 | ||
| Private study hours | 80 | ||
| Total Contact hours | 66 | ||
| Total hours (100hr per 10 credits) | 200 | ||
Students studying ELEC modules will receive formative feedback in a variety of ways, including the use of self-test quizzes on Minerva, practice questions/worked examples and (where appropriate) through verbal interaction with teaching staff and/or post-graduate demonstrators.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| In-course Assessment | Coursework 1 | 20 |
| In-course Assessment | Coursework 2 | 30 |
| Total percentage (Assessment Coursework) | 50 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
| Exam type | Exam duration | % of formal assessment |
|---|---|---|
| Standard exam (closed essays, MCQs etc) | 3.0 Hrs 0 Mins | |
| Total percentage (Assessment Exams) | 0 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
The reading list is available from the Library website
Last updated: 30/04/2025
Errors, omissions, failed links etc should be notified to the Catalogue Team