Sensorics and Elements of Artificial Intelligence
FSI-GSEAcad. year: 2019/2020
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.
Recommended optional programme components
Recommended or required reading
Getting Started with NI LabVIEW Student Training, National Instruments, dostupné z http://zone.ni.com/devzone/cda/tut/p/id/7466 (EN)
Handbook of Modern Sensors: Physics, Designs, and Applications 5th ed. 2016 Edition, Springer International Publishing, Switzerland 2016 (EN)
LabVIEW Measurements Manual, National Instruments, April 2003 Edition, Part Number 322661B-01, dostupné z www.ni.com (EN)
Frank Lamb: Industrial Automation: Hands-On, McGraw-Hill Education, 2013 (EN)
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
Theoretical fundamentals and practical know-how of applied sensorics. Sensor applications are pointed to automation and mechatronics. Acquired knowledge enables students to integrate into realisation teams solving system development, projection and production of intelligent systems and interdisciplinary tasks 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.
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
labs and studios
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
eLearning: currently opened course