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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
  • 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

  1. define systems, information and communication
  2. differentiate the physical and symbolic realities
  3. work with the concept of structure of awareness
  4. characterise the internet of things (IoT) and cyber-physical systems
  5. model and analyse systems as constituted by physical, information and decision-making layers
  6. 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. Lecture notes and other material can be found on the course platform.

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.

esineiden internet, asioiden internet, Python kirjastot, teollisuus, IoT järjestelmä, jonoteoria

Responsible teacher

LUT University
Pedro Nardelli

Further information about the course

LUT University
Niko Nevaranta

Contact person for applications

FITech Network University
Fanny Qvickström, Student services specialist
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Category:
ICT Studies
Topic:
Industrial internet
Course code:
BL40A2010
Credits:
4 ECTS
Price:
0 €
Level:
Teaching period:
5.9.–31.10.2022
Application deadline:
28.8.2022
Host university:
LUT University
Study is open for:
Adult learner,
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.
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