Syllabus

Internet of Things

Code
GMI2MD
Points
7.5 Credits
Level
First Cycle
School
School of Information and Engineering
Subject field
Microdata Analysis (XYZ)
Group of Subjects
Other Interdisciplinary Studies
Disciplinary Domain
Natural Science, 100%
This course can be included in the following main field(s) of study
Information Systems1
Microdata Analysis2
Progression indicator within (each) main field of study
1G1F
2G1F
Approved
Approved, 18 February 2021.
This syllabus is valid from 28 April 2021.

Learning Outcomes

After completing the education, the student should be able to:

Knowledge and Understanding

  • Explain the meaning of the IoT (Internet of Things) concept, as well as opportunities and challenges for digital transformation using IoT
  • Demonstrate an understanding of security aspects of IoT solutions
  • Explain and show understanding of how edge, joint and cloud computing interact and complement each other in an IoT system
  • Demonstrate understanding and explain how IoT solutions can be improved by choosing the right tools for data collection, analysis, processing and presentation

Skills and Abilities

  • Design, model and develop IoT solutions, using appropriate programming languages for edge, fog, and cloud technologies
  • Process, analyze, and present data collected through developed IoT solutions
  • Write, plan, design the required documentation and present to a group

evaluation ability and approach

  • Reflect and evaluate different IoT solutions from a sustainable, ethical and societal perspective

Course Content

The course focuses on some of the basic insights within IoT (Internet of Things): Why do we want to connect everything? What do we want to connect to? How do we connect everything?

The course initially contains an overview of the concept of IoT, where the effects of connecting previous, unconnected devices to the Internet, and the analysis of the data they generate, are discussed and what impact this has in industries around the world. Other key concepts that the course deals with are “automation“ and “data capture“ and how we by breaking down large amounts of data can gain insights into, or automate, smart behaviors that can lead to optimization of everything from global energy use to improving our health and well-being. The course further deals with the technical and soft skills needed to plan, design, prototype and present, end-to-end IoT solutions. This includes concepts such as sensors, single-board computers, network connections (both wired and wireless) and the ability to program / configure these, as well as the ability to process and analyze the collected data both locally (fog computing) and in the cloud (cloud computing). Concepts such as EDA (Exploratory Data Analysis) and GIS (Geographic Information System) help in understanding how IoT solutions can be improved by choosing the right tools for data collection, analysis, processing and presentation.

Assessment

Individual oral and written presentation of assignments and group presentation at a seminar (5.5 credits)

Exam (2.0 credits)

Forms of Study

Lectures, lessons, group project work, assignments and compulsory seminar.

Grades

The Swedish grades U–VG.

Individual oral and written presentation of assignments and group presentation at a seminar U - VG

Exam U - G

Prerequisites

  • Scripts Programming, 7.5 credits
  • Software Testing 1, 7.5 credits First Cycle
  • Data communications 1 7,5 credits

Other Information

Replaces GMI28V