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Introduction to IoT-based systems
Individual course
The course introduces Internet of Things (IoT) systems as well as basics of concepts that are necessary to understand IoT systems.
Course contents
- Introduction to IoT systems where the definition of systems, information and communication are learnt.
- Introduction to networks and their different topologies.
- The structure of awareness.
- Reflexive-active systems.
- Basics of queuing theory.
- Basics of game theory.
- Examples of IoT-based systems.
Learning outcomes
After the course, the student will be able to
- define systems, information and communication
- differentiate the physical and symbolic realities
- work with the concept of structure of awareness
- characterise the internet of things (IoT) and cyber-physical systems
- model and analyse systems as constituted by physical, information and decision-making layers
- use basic Python libraries in Jupyter notebooks to analyse IoT-based systems.
These skills are needed to built IoT systems for practical industrial applications.
Teaching methods
Weekly video lectures that are available online.
Completion methods
Weekly assignments 60 % + final work 40 %.
More information in the LUT University study guide.
You can get a digital badge after completing this course.
Responsible teacher
LUT University
Pedro Nardelli
Pedro.Juliano.Nardelli(at)lut.fi
Further information about the course
LUT University
Niko Nevaranta
niko.nevaranta(at)lut.fi
Contact person for applications
FITech Network University
Monica Sandberg, Student services specialist
monica.sandberg(at)fitech.io
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Category:
ICT Studies
Topic:
Industrial internet
Course code:
BL40A2010
Credits:
4 ECTS
Price:
0 €
Level:
Teaching period:
10.1.–25.2.2022
Application deadline:
Application period has ended
Host university:
LUT University
Study is open for:
Adult learner,
Degree student
Degree student
Teaching methods:
Online
Language:
English
General prerequisites:
Basic mathematical and programming skills.
Study suitable for:
Engineering, economics, business and computer science students who desire to learn more about the role of information networks in the system dynamics.
