After successful completion of the course, students are able to...
After the successful completion of the course, students are able to understand and classify types of virtual, augmented, and mixed reality and a machine vision. The student will be able to apply his knowledge of implementation in IIoT systems. The course will provide further details on the classification of extended reality (Augmented, Virtual and Mixed reality) and features of the architecture of the system (software and hardware components).This course will be an introduction to scientific research and practical tasks of design and implementation tasks of building and using the modern technologies in IIoT systems. This can could lead students to understand mathematical models which can be used in such technologies and their structural realization.
Topic 1. Extended Reality.
Basic terms and definitions. The main components of extented reality (XR). Classification of types of extended reality. The main examples of XR use in industrial Internet of Things systems.
Topic 2. Augmented reality.
Classification of types of augmented reality. Types of software and examples of using augmented reality in IIOT systems.
Topic 3. Virtual reality (VR).
Classification of types of virtual reality. Architecture of the virtual reality system. Examples of the implementation of virtual reality in IIOT systems.
A virtual reality. Classification of types of hardware for creating virtual reality for IIOT systems.
A virtual reality. Classification of software types and examples of the use of virtual reality in IIOT systems. Virtual reality quality indicators.
Topic 4. Mixed reality (MR).
Classification of types of mixed reality. Architecture of a mixed reality system. Types of software and examples of using mixed reality in AIOT systems.
Topic 5. Augmented and virtual reality in the implementation of digital twins in IIOT systems.
The concept of digital twin. Features of the implementation of a digital twin using augmented and virtual reality technologies.
Topic 6. Machine (computer) vision.
Basic terms and definitions. The essence of the implementation of machine vision. Features of its application in IIOT systems.
Machine (computer) vision. System architecture with machine vision. Hardware for the implementation of machine vision in IIOT systems. Machine vision cameras in combination with AI-powered vision processing.
Machine (computer) vision. Software for the implementation of machine vision in AIOT systems. Edge Insights for Industrial - Image Store. Video analytics frameworks. The Canny edge detector algorithm for image processing.
The content of the lecture will be presented interactively with the students, with video presentations, use-cases, and discussion
