The University of Sheffield
School of Computer Science

COM3505 The Internet of Things

Summary

The Internet of Things (IoT) connects various types of sensors, devices and embedded systems with cloud-based analytics, utilising data analytic and machine learning to process real-world information. As IoT continues to expand, engineers with expertise in its technologies and security will be in high demand.

This module explores the fundamentals of IoT, covering key hardware, communication protocols, security, and cloud-based data analytics. Students will gain hands-on experience developing IoT applications using Azure IoT Hub and AWS IoT, integrating sensors with general computing devices.

Session Spring 2025/26
Credits 10 credits
Assessment
  • Coursework [70%]
  • Formal examination [30%]
Lecturer(s) Prof. Po Yang & Dr Shaoxiong Sun
Resources
Aims

This module aims to...

  • prepare students for tasks that commission, design and develop Internet of Things (IoT) technologies
  • cover a broad range of IoT, approaches and platforms
  • deliver practical experience programming IoT devices, capturing their data and developing visual analytics of that data
Learning Outcomes 

By the end of the module, a student will be able to...

  • analyse and evaluate competing approaches to IoT devices and platforms
  • capture IoT device data in the cloud and analyse that data
  • demonstrate a practical application of an IoT device
Content

This module is significantly revised for Academic Year 2025/26, with a new teaching team.

The content covers an overview of the history and usage of IoT devices, with a strong focus on the tools and techniques used to process the data generated by such devices. Students will gain practical experience of deploying and using IoT devices, including how to manage the generated data to transform it into useful information.

Restrictions

Students should be competent programmers to take this course.

Optional modules within the school have limited capacity. We will always try to accommodate all students but cannot guarantee a place. 

Teaching Method One hour lecture each week and two hours of supporting classes, a mixture of tutorials and lab sessions.
Feedback During supporting classes.