Course detail
Intelligent Systems
FIT-SINAcad. year: 2019/2020
Intelligent systems, mechatronic, sociotechnical and cyber-physical systems. Artificial Intelligence Methods in Systems Design and Implementation. Discrete event systems. Control Systems Architectures. Internet of things, communication infrastructure. Smart Building, Smart Home. Smart City, Traffic Telematics, Intelligent Vehicle. Industry 4.0.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Learning outcomes of the course unit
Students acquire knowledge of principles, architectures and design of intelligent systems of various kinds.
Prerequisites
Students can use any other special knowledge to implement an individual project.
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
- Mid-term written test
- Individual project
Course curriculum
Work placements
Aims
The course is suitable for students of all specializations taught at FIT.
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
Recommended reading
Cassandras, C. G., Lafortune, S.: Introduction to discrete event systems, Springer, 2008.
David, R., Alla, H.: Petri Nets and Grafcet: Tools for Modelling Discrete Event Systems, Prentice Hall, 1992, ISBN-10: 013327537X, ISBN-13: 978-0133275377
Mehta, B.R., Reddy, Y.J.: Industrial Process Automation Systems: Design and Implementation, Elsevier, 2015, ISBN 978-0-12-800939-0
Přibyl, P., Svítek, M.: Inteligentní dopravní systémy, Nakladatelství BEN, Praha 2001, ISBN 80-7300-029-6
Russel, S., Norvig, P.: Artificial Intelligence, a Modern Approach, Pearson Education Inc., 2003, ISBN 0-13-080302-2
Valeš, M.: Inteligentní dům. Brno, Vydavatelství ERA, 2006.
Zeigler, B.P.: Theory of Modeling and Simulation, Academic Press; 2 edition (March 15, 2000), ISBN 978-0127784557
Classification of course in study plans
- Programme IT-MSC-2 Master's
branch MMI , 0 year of study, winter semester, elective
branch MBI , 0 year of study, winter semester, compulsory-optional
branch MSK , 2 year of study, winter semester, compulsory-optional
branch MMM , 0 year of study, winter semester, elective
branch MBS , 0 year of study, winter semester, elective
branch MPV , 0 year of study, winter semester, compulsory-optional
branch MIS , 0 year of study, winter semester, compulsory-optional
branch MIN , 2 year of study, winter semester, compulsory
branch MGM , 0 year of study, winter semester, compulsory-optional - Programme MITAI Master's
specialization NBIO , 0 year of study, winter semester, elective
specialization NSEN , 0 year of study, winter semester, elective
specialization NVIZ , 0 year of study, winter semester, elective
specialization NGRI , 0 year of study, winter semester, elective
specialization NISD , 0 year of study, winter semester, elective
specialization NSEC , 0 year of study, winter semester, elective
specialization NCPS , 0 year of study, winter semester, elective
specialization NHPC , 0 year of study, winter semester, elective
specialization NNET , 0 year of study, winter semester, elective
specialization NMAL , 0 year of study, winter semester, elective
specialization NVER , 0 year of study, winter semester, elective
specialization NIDE , 0 year of study, winter semester, elective
specialization NEMB , 0 year of study, winter semester, elective
specialization NSPE , 0 year of study, winter semester, elective
specialization NADE , 0 year of study, winter semester, elective
specialization NMAT , 0 year of study, winter semester, elective
specialization NISY , 2 year of study, winter semester, compulsory
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
- Introduction. Motivation and goals of the course.
- Mechatronic, sociotechnical and cyber-physical systems.
- Discrete event systems in control systems design.
- Softcomputing and expert systems in system design.
- Control system architectures and components.
- Agent paradigm. Learning and adaptive control systems.
- Markov decision process and learning controller.
- SCADA systems and distributed control systems.
- Internet of Things (IoT), IoT Architecture, Communication Protocols.
- Intelligent buildings - sensors, networks, actuators, intelligent control.
- Smart Home. Smart City. Smart Grid.
- Intelligent transportation systems - telematic systems, traffic management, intelligent vehicle.
- Smart manufacturing, Industry 4.0.
Fundamentals seminar
Teacher / Lecturer
Syllabus
- Application of soft computing in intelligent systems.
- Intelligent systems design methods.
Project
Teacher / Lecturer
Syllabus
- Individual project - implementation of intelligent control in a simulated environment. The application area can be Smart Home, Transportation Systems Telematics, Smart Manufacturing, etc.