Title:

Intelligent Sensors

Code:SEN
Ac.Year:2017/2018
Term:Winter
Curriculums:
ProgrammeBranchYearDuty
IT-MSC-2MBI-Elective
IT-MSC-2MBS-Compulsory-Elective - group B
IT-MSC-2MGM-Elective
IT-MSC-2MIN-Compulsory-Elective - group C
IT-MSC-2MIS-Elective
IT-MSC-2MMI-Elective
IT-MSC-2MMM-Elective
IT-MSC-2MPV-Compulsory-Elective - group C
IT-MSC-2MSK1stCompulsory-Elective - group N
Language:Czech
Private info:http://www.fit.vutbr.cz/study/courses/SEN/private/
Credits:5
Completion:accreditation+exam (written)
Type of
instruction:
Hour/semLecturesSem. ExercisesLab. exercisesComp. exercisesOther
Hours:2644018
 ExaminationTestsExercisesLaboratoriesOther
Points:55154422
Guarantee:Drahanský Martin, prof. Ing., Dipl.-Ing., Ph.D., DITS
Lecturer:Drahanský Martin, prof. Ing., Dipl.-Ing., Ph.D., DITS
Instructor:Dvořák Michal, Ing., DITS
Goldmann Tomáš, Ing., DITS
Heidari Mona, DITS
Maruniak Lukáš, Ing., DITS
Semerád Lukáš, Ing., DITS
Vyroubalová Jana, Ing., DITS
Faculty:Faculty of Information Technology BUT
Department:Department of Intelligent Systems FIT BUT
Prerequisites: 
Intelligent Systems (SIN), DITS
Schedule:
DayLessonWeekRoomStartEndLect.Gr.St.G.EndG.
WedlecturelecturesD020708:0009:501MITxxxx
WedlecturelecturesD020708:0009:502MITxxxx
 
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.
Description:
  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.
Knowledge and skills required for the course:
  Valid schooling of Edict No. 50 (work with electrical devices) is needed.
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.
Syllabus of lectures:
 
  1. Introduction - sensors, types of sensors, their parameters. Microelectronic and microelectromechanic systems.
  2. Electrical conductibility in different materials and components for the sensor production (semi-conductors, diodes, transistors, ...), brief introduction to the sensor production.
  3. Selected types of the measurement of the physical quantities (position estimation, measurement of the pressure, flow, temperature, optical, electrical, chemical, and magnetic quantities).
  4. Basic sensing principles (function and physical principles) - how do the sensors work?
  5. Sensor data acquirement. Basic principles of the acquirement and transmission of the data (signals and buses).
  6. Data processing. Pattern recognition and classification.
  7. Intelligent sensors I. Definitions, examples.
  8. Intelligent sensors II. Complex sensors, biometric sensors (fingerprint scanners, retina scanners, etc.).
  9. Soft-Computing (fuzzy logic, neural networks, agents), use in the intelligent sensors.
  10. Sensor networks I. Centralised and decentralised system of the measurement chains. Communication (IEEE 1415), distributed systems.
  11. Sensor networks II. Sensor networks as a multiagent systems.
  12. Practical examples of the intelligent sensors.
  13. Future of the intelligent sensors, trends (nanosensors, biosensors).
Syllabus of numerical exercises:
 
  1. Theoretical calculations - measurement, errors.
  2. Theoretical calculations - selected measurement processes.
Syllabus of laboratory exercises:
 
  1. Work with elementary sensors. Practical examples.
  2. Work with complex sensors. Practical examples.
Syllabus - others, projects and individual work of students:
 
  1. Processing of a project from the selected part of the course.
Fundamental literature:
 
  1. Martinek, R.: Senzory v průmyslové praxi, BEN - technická literatura, 2004, ISBN 80-7300-114-4
  2. Švec, J.: Příručka automatizační a výpočetní techniky, SNTL, 1975
  3. Fraden, J.: Handbook of Modern Sensors: Physics, Designs, and Applications, AIP Press, 2003, ISBN 0387007504
  4. Frank, R.: Understanding Smart Sensors, Artech House Publishers, 2000, ISBN 0890063117
  5. Brignell, J., White, N.: Intelligent Sensor Systems (Sensors), Institute of Physics Publishing, 1994, ISBN 0750302976
  6. Ristic, L.: Sensor Technology and Devices, Artech House Publishers, 1994, ISBN 0890065322
Study literature:
 
  1. Cai, Z.X.: Intelligent Control: Principles, Techniques and Applications, World Scientific, ICIA Vol. 7, 1997, p. 451, ISBN 981-02-2564-4.
  2. Martinek, R.: Senzory v průmyslové praxi, BEN - technická literatura, 2004, ISBN 80-7300-114-4.
  3. Fraden, J.: Handbook of Modern Sensors: Physics, Designs, and Applications, AIP Press, 2003, ISBN 0387007504.
  4. Frank, R.: Understanding Smart Sensors, Artech House Publishers, 2000, ISBN 0890063117.
  5. Yamasaki, H.: Intelligent Sensors, Elsevier, 1996, p. 298, ISBN 0-444-89515-9.
Progress assessment:
  
  1. Written midterm test
  2. Participation and active work in laboratories + exercises
  3. Project
Exam prerequisites:
  

Student must gain at least 15 points during the term.