Entry requirements

• Bachelor of Science in Engineering (at least 180 credits) or a bachelor’s degree in computer science or related fields such as computer engineering, computer and information science, software engineering, informatics, telecommunications or electrical engineering.
• At least 15 credits in programming.
• Equivalent of English 6 in secondary school.

Progression level in relation to degree requirements

This course is part of the main field of Computer Science and may be included in the degree requirements for the master’s degree (120 credits) in computer science.

Course contents

• Sensors, actuators and wireless sensor networks
• Microprocessor technology for IoT devices (edge computing)
• Relevant network and communication technologies, such as WiFi, ZigBee and Bluetooth
• Security risks related to IoT
• Privacy issues related to IoT
• Mobile systems for IoT
• Platforms and cloud-based solutions for IoT
• Service design for IoT
• Key application areas for the IoT, such as ‘smart homes’, ‘smart cities’, ‘mobile health’ and ‘industry 4.0’, and their relation to the global goals for sustainable development.

Learning outcomes

Knowledge and understanding
To pass the course, the student must be able to:

1. describe central technologies within the area of IoT and the application of IoT in different types of services
2. describe the security risks within IoT
3. describe the privacy risks in IoT

Skills and abilities
To pass the course, the student must be able to:

4. develop simple IoT-based services
5. analyse IoT-based services in various application areas, from both technical and sustainability perspectives

Judgement and approach
To pass the course, the student must be able to:

6. critically discuss the advantages and disadvantages of IoT for different types of services
7. critically discuss the advantages and disadvantages of various technology choices in IoT applications.

Learning activities

Lectures, lab work, a supervised project and independent study.

Assessment

In order to achieve a passing grade (A-E), all the parts must have been completed with a grade of E or G.

• Passed laboratory work (5 credits) – learning outcome 4
• Passed written exam (4 credits) – learning outcomes 1, 2, 3, 5, 6 & 7
• Passed project with reflection (6 credits) – learning outcomes 5, 6 & 7

The final grade is based on criteria from an assessment matrix provided by the course coordinator.

Laboratory work is assessed UG while written examination and projects with reflection are assessed A-U.

Course literature

• Tsiatsis, V, Karnouskos, S Holler, J, Boyle, D, Mulligan, C (2018).Internet of Things, 2nd Edition, Technologies and Applications for a New Age of Intelligence. Academic Press

Reference materials:

• Kurniawan, Agus (2021). IoT Projects with Arduino Nano 33 BLE Sense: Step-By-Step Projects for Beginners. Apres.
• Scientific articles provided by the teacher during the course.

Course evaluation

The University provides students who are taking or have completed a course with the opportunity to share their experiences of and opinions about the course in the form of a course evaluation that is arranged by the University. The University compiles the course evaluations and notifies the results and any decisions regarding actions brought about by the course evaluations. The results shall be kept available for the students. (HF 1:14).

Interim rules

When a course is no longer given, or the contents have been radically changed, the student has the right to re-take the examination, which will be given twice during a one year period, according to the syllabus which was valid at the time of registration.

Additional information

If a student has a Learning support decision, the examiner has the right to provide the student with an adapted test, or to allow the student to take the exam in a different format.

The syllabus is a translation of a Swedish source text.