Course detail

Sensorics and Elements of Artificial Intelligence

FSI-GSEAcad. year: 2020/2021

Fundamentals of electrical quantities measurement, data processing. Sensors fundamentals, selection, utilization and characteristics of sensors: temperature, proximity, position, velocity and acceleration; force, torque, mass, pressure and flow. Selection of control systems, DAQ, signal conditioning, communication busses, SMART sensors and complex sensors systems.

Learning outcomes of the course unit

Measurement fundamentals, signal processing methods (DAQ) and sensors overview based on various physical principles and sensors applications in practice. Introduction to modern sensor trends, sensor fusion and integration, artificial intelligence methods.


Theoretical knowledge of physics, fundamentals of electronics and algorithmization.


Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

Getting Started with NI LabVIEW Student Training, National Instruments, dostupné z (EN)
Handbook of Modern Sensors: Physics, Designs, and Applications 5th ed. 2016 Edition, Springer International Publishing, Switzerland 2016 (EN)
Frank Lamb: Industrial Automation: Hands-On, McGraw-Hill Education, 2013 (EN)
LabVIEW Measurements Manual, National Instruments, April 2003 Edition, Part Number 322661B-01, dostupné z (EN)
Daďo S., Kreidel M.: Senzory a měřicí obvody. Praha. ČVUT 1996 (CS)
Husák M.: Senzorové systémy. Praha, ČVUT 1993 (CS)
Zehnula, K.: Čidla robotů. Praha, SNTL 1990 (CS)

Planned learning activities and teaching methods

The course is taught through lectures explaining the basic principles and theory of the discipline. Teaching is suplemented by practical laboratory work.

Assesment methods and criteria linked to learning outcomes

Course credit award requirements: active participation in laboratories, elaboration and commit of laboratory reports. Examinations: written and oral, classified by ECTS.

Language of instruction


Work placements

Not applicable.


Theoretical fundamentals and practical know-how of applied sensors. Sensor applications are pointed to automation and mechatronics. Acquired knowledge enables students to integrate into teams dealing with implementation of advanced systems within interdisciplinary fields in engineering practice.

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

Attendance at lectures is recommended, attendance at seminars is monitored. Maximally two absence are compensated by individual missing laboratory reports working out.

Classification of course in study plans

  • Programme M2A-P Master's

    branch M-MET , 2. year of study, winter semester, 6 credits, compulsory

Type of course unit



26 hours, optionally

Teacher / Lecturer


1. Introduction, basic terminology and general characteristic of sensors
2. Inputs and output of the digital systems
3. DAQ introduction
4. Temperature sensors
5. Opto-electrics sensors
6. Position sensors and detectors
7. Acceleration sensors and gyroscopes
8. Force, torque and mass sensors
9. Pressure sensors
10. Flow and level sensors
11-13. Communications protocols

Laboratory exercise

13 hours, compulsory

Teacher / Lecturer


1-3. Introduction to LabVIEW and DAQ
4-6. Static characteristic of Aripot
7-9. Temperature sensing
10-12. Position and velocity measuremnt
13. Laboratory works finishing , credit