Course details
Intelligent Sensors
SEN Acad. year 2015/2016 Winter semester 5 credits
Elementary sensors, types of sensors, their parameters. Conductance, electronic components and production of the sensors. Measurement of physical quantities. Acquirement, transmission, and processing of the sensor data. Definition of the intelligent sensors. Sensor networks - communication, centralised and decentralised system of the measurement chains, multiagent systems. Practical examples and future trends - nanosensors and biosensors.
Guarantor
Language of instruction
Completion
Time span
- 26 hrs lectures
- 4 hrs exercises
- 4 hrs laboratories
- 18 hrs projects
Department
Subject specific learning outcomes and competences
The the acquainted knowledge belongs the measurement of physical quantities, how to convert physical quantities to electronic form using sensors and how to transmit, process, and use acquired data. Everything is oriented on intelligent sensors, sensor networks and smart homes.
Learning objectives
To inform about the measurement of the physical quantities. To learn how the physical quantities are converted to an electronic form using sensors. To learn how to transmit, process and use data.
Prerequisite knowledge and skills
Valid schooling of Edict No. 50 (work with electrical devices) is needed.
Study literature
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- Cai, Z.X.: Intelligent Control: Principles, Techniques and Applications, World Scientific, ICIA Vol. 7, 1997, p. 451, ISBN 981-02-2564-4.
- Martinek, R.: Senzory v průmyslové praxi, BEN - technická literatura, 2004, ISBN 80-7300-114-4.
- Fraden, J.: Handbook of Modern Sensors: Physics, Designs, and Applications, AIP Press, 2003, ISBN 0387007504.
- Frank, R.: Understanding Smart Sensors, Artech House Publishers, 2000, ISBN 0890063117.
- Yamasaki, H.: Intelligent Sensors, Elsevier, 1996, p. 298, ISBN 0-444-89515-9.
Fundamental literature
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- Martinek, R.: Senzory v průmyslové praxi, BEN - technická literatura, 2004, ISBN 80-7300-114-4
- Švec, J.: Příručka automatizační a výpočetní techniky, SNTL, 1975
- Fraden, J.: Handbook of Modern Sensors: Physics, Designs, and Applications, AIP Press, 2003, ISBN 0387007504
- Frank, R.: Understanding Smart Sensors, Artech House Publishers, 2000, ISBN 0890063117
- Brignell, J., White, N.: Intelligent Sensor Systems (Sensors), Institute of Physics Publishing, 1994, ISBN 0750302976
- Ristic, L.: Sensor Technology and Devices, Artech House Publishers, 1994, ISBN 0890065322
Syllabus of lectures
- Introduction - sensors, types of sensors, their parameters. Microelectronic and microelectromechanic systems.
- Electrical conductibility in different materials and components for the sensor production (semi-conductors, diodes, transistors, ...), brief introduction to the sensor production.
- Selected types of the measurement of the physical quantities (position estimation, measurement of the pressure, flow, temperature, optical, electrical, chemical, and magnetic quantities).
- Basic sensing principles (function and physical principles) - how do the sensors work?
- Sensor data acquirement. Basic principles of the acquirement and transmission of the data (signals and buses).
- Data processing. Pattern recognition and classification.
- Intelligent sensors I. Definitions, examples.
- Intelligent sensors II. Complex sensors, biometric sensors (fingerprint scanners, retina scanners, etc.).
- Soft-Computing (fuzzy logic, neural networks, agents), use in the intelligent sensors.
- Sensor networks I. Centralised and decentralised system of the measurement chains. Communication (IEEE 1415), distributed systems.
- Sensor networks II. Sensor networks as a multiagent systems.
- Practical examples of the intelligent sensors.
- Future of the intelligent sensors, trends (nanosensors, biosensors).
Syllabus of numerical exercises
- Theoretical calculations - measurement, errors.
- Theoretical calculations - selected measurement processes.
Syllabus of laboratory exercises
- Work with elementary sensors. Practical examples.
- Work with complex sensors. Practical examples.
Progress assessment
Student must gain at least 15 points during the term.
Controlled instruction
- Written midterm test
- Participation and active work in laboratories + exercises
- Project
Course inclusion in study plans