Course detail

Sensorics and Elements of Artificial Intelligence

FSI-GSE-AAcad. year: 2018/2019

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.

Language of instruction

English

Number of ECTS credits

6

Mode of study

Not applicable.

Guarantor

Ing. Pavel Houška, Ph.D.

Department

Institute of Automation and Computer Science (ÚAI)

Offered to foreign students

Of all faculties

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.

Prerequisites

Theoretical knowledge about control, design of control systems and electronics fundamentals.

Co-requisites

Not applicable.

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.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

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.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Fraden, Jacob: Handbook of Modern Sensors - Physics, Designs and Applications (3rd Edition), Springer - Verlag, 2004
Isermann, Rolf: Mechatronic systems—fundamentals, Springer Netherlands, 2008
LabVIEW Measurements Manual, National Instruments, April 2003 Edition, Part Number 322661B-01, dostupné z www.ni.com
Mitchell, H.B: Multi-Sensor Data Fusion - An Introduction, Springer - Verlag, 2007

Recommended reading

Daďo S., Kreidel M.: Senzory a měřicí obvody. Praha. ČVUT 1996
Getting Started with NI LabVIEW Student Training, National Instruments, dostupné z http://zone.ni.com/devzone/cda/tut/p/id/7466
Husák M.: Senzorové systémy. Praha, ČVUT 1993
Zehnula, K.: Čidla robotů. Praha, SNTL 1990

Classification of course in study plans

  • Programme M2I-Z Master's

    branch M-STI , 1 year of study, winter semester, recommended course

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

Ing. Pavel Houška, Ph.D.

Syllabus

1. Introduction, basic terminology and general characteristic of sensors
2. Sensor modelling and identification
3. Methods of sensor connection - analog connections
4. Methods of sensor connection - digital interfaces
5. Principles of SMART sensors
6. Integrated and MEMS sensors
7. Sensors for electrical quantities measurement
9. Sensors for positions, velocity and acceleration measurement
10. Sensors for pressure, tension, force and torque measurement
11. Sensors for flow, flow rate and mass measurement
12. Sensors for level, density and viscosity measurement
13. Special sensors