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.
Supervisor
Department
Learning outcomes of the course unit
Ability to model and design intelligent (smart) systems and their control using current methods and technologies.
Students acquire knowledge of principles, architectures and design of intelligent systems of various kinds.
Prerequisites
Basics of systems theory, simulation.
Students can use any other special knowledge to implement an individual project.
Co-requisites
Not applicable.
Recommended optional programme components
Not applicable.
Recommended or required reading
Russel, S., Norvig, P.: Artificial Intelligence, a Modern Approach, Pearson Education Inc., 2003, ISBN 0-13-080302-2
Zeigler, B.P.: Theory of Modeling and Simulation, Academic Press; 2 edition (March 15, 2000), ISBN 978-0127784557
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
Valeš, M.: Inteligentní dům. Brno, Vydavatelství ERA, 2006.
Přibyl, P., Svítek, M.: Inteligentní dopravní systémy, Nakladatelství BEN, Praha 2001, ISBN 80-7300-029-6
Automatizace. http://www.automatizace.cz/
Planned learning activities and teaching methods
Not applicable.
Assesment methods and criteria linked to learning outcomes
- Mid-term written test
- Individual project
Language of instruction
Czech
Work placements
Not applicable.
Aims
To acquaint students with principles, architectures, and methods of design of intelligent systems of various kinds.
The course is suitable for students of all specializations taught at FIT.
Classification of course in study plans
- Programme IT-MGR-2 Master's
branch MBI , any year of study, winter semester, 5 credits, compulsory-optional
branch MPV , any year of study, winter semester, 5 credits, compulsory-optional
branch MGM , any year of study, winter semester, 5 credits, compulsory-optional
branch MIS , any year of study, winter semester, 5 credits, compulsory-optional
branch MBS , any year of study, winter semester, 5 credits, optional
branch MMI , any year of study, winter semester, 5 credits, optional
branch MMM , any year of study, winter semester, 5 credits, optional - Programme MITAI Master's
specialization NADE , any year of study, winter semester, 5 credits, optional
specialization NBIO , any year of study, winter semester, 5 credits, optional
specialization NGRI , any year of study, winter semester, 5 credits, optional
specialization NNET , any year of study, winter semester, 5 credits, optional
specialization NVIZ , any year of study, winter semester, 5 credits, optional
specialization NCPS , any year of study, winter semester, 5 credits, optional
specialization NSEC , any year of study, winter semester, 5 credits, optional
specialization NEMB , any year of study, winter semester, 5 credits, optional
specialization NHPC , any year of study, winter semester, 5 credits, optional
specialization NISD , any year of study, winter semester, 5 credits, optional
specialization NIDE , any year of study, winter semester, 5 credits, optional
specialization NMAL , any year of study, winter semester, 5 credits, optional
specialization NMAT , any year of study, winter semester, 5 credits, optional
specialization NSEN , any year of study, winter semester, 5 credits, optional
specialization NVER , any year of study, winter semester, 5 credits, optional
specialization NSPE , any year of study, winter semester, 5 credits, optional - Programme IT-MGR-2 Master's
branch MSK , 2. year of study, winter semester, 5 credits, compulsory-optional
branch MIN , 2. year of study, winter semester, 5 credits, compulsory - Programme MITAI Master's
specialization NISY , 2. year of study, winter semester, 5 credits, compulsory
Type of course unit
Lecture
26 hours, optionally
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
4 hours, compulsory
Teacher / Lecturer
Syllabus
- Application of soft computing in intelligent systems.
- Intelligent systems design methods.
Project
22 hours, compulsory
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.
eLearning
eLearning: currently opened course