Course detail
Intelligent Sensors
FIT-SENAcad. year: 2017/2018
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.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Learning outcomes of the course unit
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Student must gain at least 15 points during the term.
Course curriculum
- 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).
- Theoretical calculations - measurement, errors.
- Theoretical calculations - selected measurement processes.
- Work with elementary sensors. Practical examples.
- Work with complex sensors. Practical examples.
- Processing of a project from the selected part of the course.
Syllabus of numerical exercises:
Syllabus of laboratory exercises:
Syllabus - others, projects and individual work of students:
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
- Written midterm test
- Participation and active work in laboratories + exercises
- Project
Recommended optional programme components
Prerequisites and corequisites
Basic literature
Recommended reading
Classification of course in study plans
- Programme IT-MSC-2 Master's
branch MBI , 0 year of study, winter semester, elective
branch MSK , 1 year of study, winter semester, compulsory-optional
branch MMM , 0 year of study, winter semester, elective
branch MBS , 0 year of study, winter semester, compulsory-optional
branch MIS , 0 year of study, winter semester, elective
branch MIN , 0 year of study, winter semester, compulsory-optional
branch MGM , 0 year of study, winter semester, elective
branch MPV , 0 year of study, winter semester, compulsory-optional