Course: Sensors for Embedded Systems

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Course title Sensors for Embedded Systems
Course code KIV/SES-E
Organizational form of instruction Lecture + Tutorial
Level of course Bachelor
Year of study not specified
Semester Winter and summer
Number of ECTS credits 5
Language of instruction English
Status of course Compulsory
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Mainzer Tomáš, Ing. Ph.D.
Course content
1. Sensor classification. Sensor interface. Control system architecture. 2. Resolution, Precision, Errors, Algorithm for scaling, linearisation and filtration  3. Regulation loop, system control, System type 4. PID regulator algorithm, implementation, Time-delay and remote control problematic 5. Digital Signal Filtering, Noise reduction, Frequency filters, Algorithms 6. Physical sensors and its interface 7. Sensor related peripheral in microcontrolers 8. Local Bus based sensors and protocols 9. Industrial sensors and protocols 10. Wireless sensors, sensor networks 11. User interface - Touch sensors, displays, cameras, keys 12. Relays, motors, servos. 13. Multiple sensors, Sensor fusion, Sensor safety

Learning activities and teaching methods
  • Preparation for formative assessments (2-20) - 10 hours per semester
  • Contact hours - 52 hours per semester
  • Preparation for an examination (30-60) - 30 hours per semester
  • Presentation preparation (report) (1-10) - 6 hours per semester
  • Undergraduate study programme term essay (20-40) - 32 hours per semester
prerequisite
Knowledge
Special Knowledge - basic knowledge of algorithmization, programming and boolean logic. Basic knowledge of physics, electronics and mathematics.
Skills
Special Skills - programming and algorithmization skills, Understanding of mathematics notations and operations, understanding of basic electrotechnical units and its measurements.
Competences
General Competences - planning and controlling of study, cooperation and discussion, active using and evaluation of information sources.
learning outcomes
Knowledge
Special Knowledge - knowledge of miscellaneous types of sensors, signal processing algorithms, control system and algorithms, analysis of sensor properties
Skills
Expertise - experiments with miscellaneous types of sensor, create software for signal processing and basic control algorithms, analysis of sensor types and system requirements
Competences
General Competences - applying of knowledge, self-reliance decision in area of expertise.
teaching methods
Knowledge
Lectures, Exercises, Labs, Self-study Individual consultation
Skills
Labs, Self-study, Presentation, Individual consultation
Competences
Lectures with discussion, Problem solving, Selfstudy, Presentation
assessment methods
Knowledge
Examination, Seminar paper, Individual presentation
Skills
Seminar paper, Test, Practical demonstration, Individual presentation
Competences
Examination, Seminar paper, Continuous assessment
Recommended literature
  • Jacob Fraden. Handbook of Modern Sensors: Physics, Designs, and Applications. 2015. ISBN 3319193031.
  • Steven W. Smith. The Scientist and Engineer?s Guide to Digital Signal Processing. 1999. ISBN 0-9660176-7-6.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester