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

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

doc. Ing. Vladimír Janoušek, Ph.D.

Department

Department of Intelligent Systems (UITS)

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.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

  • Mid-term written test
  • Individual project

Course curriculum

Not applicable.

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.

Specification of controlled education, way of implementation and compensation for absences

Not applicable.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

Automatizace. http://www.automatizace.cz/
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

26 hod., optionally

Teacher / Lecturer

doc. Ing. Vladimír Janoušek, Ph.D.

Syllabus

  1. Introduction. Motivation and goals of the course. 
  2. Mechatronic, sociotechnical and cyber-physical systems.
  3. Discrete event systems in control systems design.
  4. Softcomputing and expert systems in system design.
  5. Control system architectures and components.
  6. Agent paradigm. Learning and adaptive control systems.
  7. Markov decision process and learning controller.
  8. SCADA systems and distributed control systems. 
  9. Internet of Things (IoT), IoT Architecture, Communication Protocols.
  10. Intelligent buildings - sensors, networks, actuators, intelligent control.
  11. Smart Home. Smart City. Smart Grid.
  12. Intelligent transportation systems - telematic systems, traffic management, intelligent vehicle.
  13. Smart manufacturing, Industry 4.0.

Fundamentals seminar

4 hod., compulsory

Teacher / Lecturer

doc. Ing. Vladimír Janoušek, Ph.D.

Syllabus

  1. Application of soft computing in intelligent systems.
  2. Intelligent systems design methods.

Project

22 hod., compulsory

Teacher / Lecturer

doc. Ing. Vladimír Janoušek, Ph.D.

Syllabus

  • Individual project - implementation of intelligent control in a simulated environment. The application area can be Smart Home, Transportation Systems Telematics, Smart Manufacturing, etc.