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.

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

  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 hours, compulsory

Teacher / Lecturer

Syllabus

  1. Application of soft computing in intelligent systems.
  2. 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.

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