IoT embedded systems - course description

General information

Course name	IoT embedded systems
Course ID	11.3-WE-INFD-IoTES-Er
Faculty	Faculty of Computer Science, Electrical Engineering and Automatics
Field of study	Computer Science
Education profile	academic
Level of studies	Second-cycle Erasmus programme
Beginning semester	winter term 2022/2023

Course information

Semester	3
ECTS credits to win	4
Course type	obligatory
Teaching language	english
Author of syllabus	prof. dr hab. inż. Alexander Barkalov dr inż. Michał Doligalski

Classes forms

The class form	Hours per semester (full-time)	Hours per week (full-time)	Hours per semester (part-time)	Hours per week (part-time)	Form of assignment
Lecture	15	1	-	-	Credit with grade
Laboratory	30	2	-	-	Credit with grade
Project	15	1	-	-	Credit with grade

Aim of the course

to familiarize students with tools and techniques and architecture of the Internet of Things systems
developing understanding of the need to ensure the highest quality of IT systems in the area of the Internet of Things
shaping the ability to design and verify Internet of Things systems, in particular the use of development tools
developing skills, using a variety of hardware and software solutions to implement Internet of Things systems

Prerequisites

Designing information systems, programming basics, modeling methods for digital systems

Scope

Fundamentals of Internet of Things (IoT and. Internet of Things) systems. The role and use of embedded systems in the area of the Internet of Things. Application of IoT systems. Communication protocols and architecture of IoT systems. Increased reliability of IoT systems. IoT system as a distributed system. Optamalization of IoT systems including in the area of energy consumption. The role of formal models in the design of IoT systems (e.g. FSM). Implementation of IoT system components using: Reprogrammed systems, ASIC systems, Single Board Computers. Development tools in the design of IoT systems. IoT systems testing.

Teaching methods

lecture: conventional lecture

laboratory: laboratory exercises

project: project method

Learning outcomes and methods of theirs verification

Outcome description	Outcome symbols	Methods of verification	The class form

Assignment conditions

Lecture - the pass condition is to obtain a positive grade from the final test carried out in writing. A condition for joining the colloquium is a positive evaluation from the laboratory.

Laboratory - the condition for passing is obtaining positive grades from all laboratory exercises, planned to be implemented under the laboratory program (80%) and activity in the classroom (20%).

Project - a pass condition is to obtain a positive grade from the project

Components of the final grade = lecture: 40% + laboratory: 30% + project: 30%

Notes

Modified by dr inż. Michał Doligalski (last modification: 23-04-2022 07:41)

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