Internet-of-Things (883H1)
Internet-of-Things and Embedded System Practice
Module 883H1
Module details for 2022/23.
15 credits
FHEQ Level 7 (Masters)
Module Outline
The Internet-of-Things (IoT) is the network of physical objects or "things" embedded with electronics, software, sensors and connectivity to enable it to achieve greater value and service by exchanging data with the manufacturer, operator and/or other connected devices. In this module, we will introduce IoT concepts and various building blocks, applications and ecosystems associated with the IoT. Students also get hands-on experience in building an IoT system by integrating embedded sensor devices and cloud to remotely monitor and control sensor data from any Internet devices, such as PC or smart phone. The module aims to give full support to students with a series of carefully constructed concepts and embedded system exercises which will start from basic principles to more advanced IoT system design.
An outline of the module is listed as follow:
1. Introduction to IoT
2. IoT architecture and components
3. IoT connectivity protocols
4. Cloud platform and management for IoT
5. Emerging software-defined networks and virtualization for IoT
6. IoT vertical applications (vehicle, industry, ehealth)
AHEP4 Learning Outcomes
M1, M2, M3, M4, M5, M6, M12, M13, M17
Module learning outcomes
Systematic understanding of IoT, including concepts, elements, applications and ecosystems.
In-depth analysis of the architecture and standards as well as connectivity protocols in IoT
Design and critically evaluate the performance of hardware and software modules to control: connectivity between embedded IoT nodes, including access protocols for gateway, cloud and end-user client access.
Critically evaluate embedded IoT applications with a focus on end-user applications and systematically identify effective designs.
| Type | Timing | Weighting |
|---|---|---|
| Coursework | 100.00% | |
| Coursework components. Weighted as shown below. | ||
| Oral assessment | T1 Week 11 (15 minutes) | 30.00% |
| Report | A1 Week 1 | 70.00% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
| Term | Method | Duration | Week pattern |
|---|---|---|---|
| Autumn Semester | Laboratory | 3 hours | 11111111110 |
| Autumn Semester | Lecture | 2 hours | 11111111110 |
How to read the week pattern
The numbers indicate the weeks of the term and how many events take place each week.
Dr Zhengguo Sheng
Assess convenor
/profiles/355346
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