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Lecturer(s)
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Vavruška Jan, Ing. Ph.D.
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Mendřický Radomír, doc. Ing. Ph.D.
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Vavroušek Miroslav, Ing. Ph.D.
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Koblasa František, Ing. Ph.D.
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Course content
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Lectures (topics): 1. Industry 4.0 (CIM, Digital model/shadow/twin, IoT, XR technology, VID and MOCAP). 2. Introduction to artificial intelligence - categorization and possibilities of use in practice. 3. Practical basics of artificial intelligence - from traditional computational models to machine learning. 4. Development and trends of XR technologies. 5. 3D digitization of objects and scenes (3D scanning technology, the process of creating 3D models using photogrammetry). 6. Introduction to the development of modern visualization tools with support for virtual and augmented reality. 7. Security and ethical aspects of AI, XR. Exercises (topics): 1. Use of public LLMs for creating searches and for modeling optimization problems. 2. Application of artificial intelligence for solving decision-making problems. 3. Tasks using XR technologies and Industry 4.0 4. Practical creation of a 3D model using photogrammetry (from taking photos to creating a textured model, optimizing a 3D model for VR/AR). 5. Fundamentals of developing applications with XR support. 6. Preparation of materials for an XR assistant using AI
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Learning activities and teaching methods
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Self-study (text study, reading, problematic tasks, practical tasks, experiments, research, written assignments), Demonstration, Project teaching, Independent creative and artistic activities, Demonstration of student skills, Lecture, Practicum, E-learning, Task-based study method, Students' self-study
- Class attendance
- 28 hours per semester
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Learning outcomes
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The course focuses on the application of Artificial Intelligence (AI) and Extended Reality (XR) tools in mechanical engineering. Students will become familiar with technical tools such as artificial intelligence, machine learning, etc. including visualization tools such as Virtual reality (VR), augmented reality (AR), mixed reality (MR), etc. in mechanical engineering. The tools and their applications will be presented in the context of Industry 4.0.
Student will gain basic knowledge and an introductory overview of AI and XR in the context of Industry 4.0
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Prerequisites
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To complete this course is not necessary to complete any other courses.
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Assessment methods and criteria
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Student's performance analysis, Presentation of student research activity, Test
Project defense, passing tests, active participation in studies
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Recommended literature
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Jednoduše: Umělá inteligence. Universum. Praha: Euromedia Group, 2023. ISBN 978-80-242-9293-9.
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MAŘÍK, Vladimír; TRČKA, Michal a ČERNÝ, David. Proč se nebát umělé inteligence?: AI pohledem nejen českých odborníků. Brno, 2024. ISBN 978-80-7689-459-4.
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OSTAŠEVIČIUS, Vytautas. Digital twins in manufacturing: virtual and physical twins for advanced manufacturing. Cham, Switzerland. 2022.
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