ACIT4015 Internet of Things Course description

The Internet of Things (IoT) enables the development of unique, innovative products and services. In this course, students will gain an advanced understanding of some of the most important principles relating to IoT.

Students will become familiar with architecture and intelligent algorithms that govern IoT and pervasive computing and will get to investigate a particular IoT related case in more depth. The goal of the course is to give students an overall understanding of IoT from a technical point of view and in relation to the consequences for society (for example privacy preservation, security) when billions (or trillions) of units communicate with each other in ‘the cloud’.

Grade scale A-F.

No requirements over and above the admission requirements.

After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and competence:

Knowledge

The student

• has a thorough technical understanding of the functioning of Internet and computer networks
• has an overview of the most important principles in ambient computing, pervasive computing, and the Internet of Things (which include wearable devices, context aware computing, health monitoring, smart houses, crowd sensing, smart grids and ambient intelligence)
• understands the basic technical principles behind  the Internet of Things
• has an overview of important principles in IoT-adjacent knowledge areas such as information security and information privacy / data protection
• has a deep understanding of how the Internet of Things and pervasive computing affect security and the protection of privacy in our society
• has good knowledge of the scientific advances and technology leaps that enabled the Internet of Things
• has insight into the use cases and applications of IoT.

Skills

The student

• masters basic concepts and has an overview of algorithms used on the internet and in data communication
• is capable of conceptualising architecture for solutions based on the Internet of Things and pervasive computing
• is able to contrast and discuss IoT-related designs relative to their own field of study                   

General competence

The student

• is capable of understanding and evaluating solutions based on the principles behind the Internet of Things and pervasive computing
• is capable of communicating aspects of IoT in relationship to their own field of study

The course will mainly consist of lectures and supervisory sessions. Students work individually on exercises or reading assignments given throughout the course. In addition, students will work in groups of two on a project involving IoT. In rare cases, the size of the group may be adjusted, depending on the judgement of the course responsible. A project report documenting the project and its results will be handed in at the end of the course. 

The course will provide background and preparatory reading materials. Reading assignments and media will be provided on the electronic learning platform.

No requirements over and above the admission requirements.

After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge The student is capable of:

• using linear algebra to determine eigenvalues and solving systems of differential equations and solving second order linear differential equations with constant coefficients 
• discussing functions of multiple variables and apply partial derivatives to various problems
• explaining convergence and power series representations of functions
• explaining key concepts in set theory, probability theory, parameter estimation, hypothesis testing and choice of model
• explaining normal, binomial, Poisson and exponential probability distributions, as well as typical problems to which they can be applied

Skills

The student is capable of:

• calculating eigenvectors and diagonalising matrices
• applying diagonalisation of matrices to solve systems of differential equations
• determining the convergence of series using the ratio test, and finding the Taylor series of known functions
• describing and discussing functions of multiple variables using e.g. level curves and partial derivatives
• determining and classifying critical points of functions of two variables
• applying statistical principles and concepts from their own field
• basic calculus of probability with discrete and continuous probability distributions and parameter estimation
• calculating confidence intervals and testing hypotheses
• applying mathematical tools to matrices and functions of two variables

General competence

The student is capable of:

• identifying the connection between mathematics and their own field of engineering
• transferring a practical problem from their own field into mathematical form, so it can be solved analytically or numerically
• using mathematical methods and tools that are relevant to the field
• using statistical ways of thinking to solve problems in engineering and communicating them orally and in writing
• solving problems in engineering by use of probability calculations, statistical planning of trials, data collection and analysis

The course is taught through joint lectures and exercises. In the exercise sessions, the students work on assignments, both individually and in groups, under the supervision of a lecturer.

None.

Individual written exam, 3 hours.

The exam result can be appealed.

Aids enclosed with the exam question paper, and a handheld calculator that cannot be used for wireless communication or to perform symbolic calculations. If the calculator’s internal memory can store data, the memory must be deleted before the exam. Random checks may be carried out.

One internal examiner. External examiners are used regularly.