Faculty of Information Technology, BUT

Course details

Intelligent Systems

SIN Acad. year 2019/2020 Winter semester 5 credits

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.

Guarantor

Deputy Guarantor

Language of instruction

Czech

Completion

Examination (written)

Time span

26 hrs lectures, 4 hrs exercises, 22 hrs projects

Assessment points

70 exam, 15 half-term test, 15 projects

Department

Lecturer

Instructor

Subject specific learning outcomes and competences

Ability to model and design intelligent (smart) systems and their control using current methods and technologies.

Generic learning outcomes and competences

Students acquire knowledge of principles, architectures and design of intelligent systems of various kinds.

Learning objectives

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.

Why is the course taught

The course combines theoretical knowledge of modelling systems and methods of artificial intelligence with technologies used in the practical implementation of smart systems.

Prerequisite kwnowledge and skills

Basics of systems theory, simulation.
Students can use any other special knowledge to implement an individual project.

Study literature

  1. Russel, S., Norvig, P.: Artificial Intelligence, a Modern Approach, Pearson Education Inc., 2003, ISBN 0-13-080302-2
  2. Zeigler, B.P.: Theory of Modeling and Simulation, Academic Press; 2 edition (March 15, 2000), ISBN 978-0127784557
  3. Cassandras, C. G.,  Lafortune, S.: Introduction to discrete event systems, Springer, 2008.
  4. David, R., Alla, H.: Petri Nets and Grafcet: Tools for Modelling Discrete Event Systems, Prentice Hall, 1992, ISBN-10: 013327537X, ISBN-13: 978-0133275377
  5. Mehta, B.R., Reddy, Y.J.: Industrial Process Automation Systems: Design and Implementation, Elsevier, 2015, ISBN 978-0-12-800939-0
  6. Valeš, M.: Inteligentní dům. Brno, Vydavatelství ERA, 2006.
  7. Přibyl, P., Svítek, M.: Inteligentní dopravní systémy, Nakladatelství BEN, Praha 2001, ISBN 80-7300-029-6
  8. Automatizace. http://www.automatizace.cz/

Fundamental literature

  1. Russel, S., Norvig, P.: Artificial Intelligence, a Modern Approach, Pearson Education Inc., 2003, ISBN 0-13-080302-2
  2. Zeigler, B.P.: Theory of Modeling and Simulation, Academic Press; 2 edition (March 15, 2000), ISBN 978-0127784557
  3. Cassandras, C. G.,  Lafortune, S.: Introduction to discrete event systems, Springer, 2008.
  4. David, R., Alla, H.: Petri Nets and Grafcet: Tools for Modelling Discrete Event Systems, Prentice Hall, 1992, ISBN-10: 013327537X, ISBN-13: 978-0133275377
  5. Mehta, B.R., Reddy, Y.J.: Industrial Process Automation Systems: Design and Implementation, Elsevier, 2015, ISBN 978-0-12-800939-0
  6. Valeš, M.: Inteligentní dům. Brno, Vydavatelství ERA, 2006.
  7. Přibyl, P., Svítek, M.: Inteligentní dopravní systémy, Nakladatelství BEN, Praha 2001, ISBN 80-7300-029-6
  8. Automatizace. http://www.automatizace.cz/

Syllabus of lectures

  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.

Syllabus of numerical exercises

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

Syllabus - others, projects and individual work of students

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

Progress assessment

  • Mid-term written test
  • Individual project

Schedule

DayTypeWeeksRoomStartEndLect.grpGroupsInfo
Monlecturelectures D105 18:0019:50 1MIT 2MIT MIN xx
Monexerciselectures D105 20:0020:50 1MIT 2MIT MIN xx

Course inclusion in study plans

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