SylabUZ
Course name | Industrial IoT |
Course ID | 11.9-WE-INFD-IndIoT-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 |
Semester | 2 |
ECTS credits to win | 4 |
Course type | obligatory |
Teaching language | english |
Author of syllabus |
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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 |
- Acquaintance with the basics of functioning and IIoT technologies,
- Mastering the principles of designing and implementing IIoT systems,
- Analysis of network traffic in IIoT systems.
Basics of computer and industrial networks. Safety engineering, machine learning.
Introduction to Industrial Internet of Things (IIoT). IIoT architecture. IIoT platforms. Sensors and actuators in IIoT networks. IIoT hubs and gates. Communication with IIoT nodes. IIoT communication protocols. Data collection and processing. IIoT security. Rules for creating IIoT applications, quick application prototyping. OT and IT technologies in IIoT applications. Network traffic analysis. IIoT integration with the enterprise network and production analysis. Designing IIoT systems. Centralized and distributed systems. Network Services. Machine learning in edge analysis IIoT. Differences between IIoT and IoT and WoT. IIoT applications.
lecture: discussion, consultation, conventional lecture,
laboratory: discussion, consultation, group work, laboratory exercises,
project: discussion, consultation, group work, project method.
Outcome description | Outcome symbols | Methods of verification | The class form |
Lecture - the pass condition is to obtain a positive grade from the colloquium,
Laboratory - the condition of getting credit is obtaining positive grades from all laboratory exercises, planned to be implemented under the laboratory program,
Project - the condition for getting credit is the completion of a design task commissioned by the teacher.
Components of the final grade = lecture: 30% + laboratory: 40% + project 30%.
Modified by dr inż. Emil Michta, prof. UZ (last modification: 14-04-2022 21:39)