Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics

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    Intelligent Sensors

    A tantárgy neve magyarul / Name of the subject in Hungarian: Intelligens szenzorok

    Last updated: 2015. február 11.

    Budapest University of Technology and Economics
    Faculty of Electrical Engineering and Informatics
    Budapest University

     

    of Technology and Economics

     

    Faculty of Electrical and Electronics Engineering

     

    Branch of Electrical Engineering

     

    Elective Subject

     

    Course ID Semester Assessment Credit Tantárgyfélév
    VIEEAV05   4/0/0/v 4  
    3. Course coordinator and department Dr. Hosszú Gábor, Elektronikus Eszközök Tanszéke
    4. Instructors
    Name:

     

    Position:

     

    Department.:

     

    Ferenc Kovács, DSc.

     

    Professor

     

    Department of Electron Devices

     

    Gábor Hosszú PhD.

     

    Associate Professor

     

    Department of Electron Devices

     

    5. Required knowledge

    Digital Technics, Electronics, Microelectronics

    6. Pre-requisites
    Ajánlott:
    -
    7. Objectives, learning outcomes and obtained knowledge Obtaining deeper knowledge in the architecture and operation of the latest sensors, processing the measured signals; moreover, the methods of telemetric and telemedicine

     

    8. Synopsis Week 1:     Types of the microelectronic integrated sensors, chemical sensors, cantilevers, micro-heaters, ISFETs, and ChemFET sensors, SAW sensors, integrated biological sensors, Lab-on-Chip electrochemical analyzers, intelligent pressure sensors.

     

    Week 2:     Features of the intelligence of the sensors, self-calibration, signal-digitalization, removing the artefacts, reconfigurability, data compression, adaptivity, communication capability.

     

    Week 3:     Methods for preprocessing the measured signals, digital and analogue integrated processing methods, circuit implementations of the self-calibrating A/D converters.

     

    Week 4:     The elements of the VHDL language used in the hardware design. Modeling the inherent parallelism of the hardware with VHDL language tools. VHDL descriptions of example circuits.

     

    Week 5:     Abstraction levels in the digital system modeling. VHDL description of the digital logic processing circuits of the sensors. The fundamentals of the VHLD based circuit synthesis.

     

    Week 6:     Comparison of the signal conditioning in case of the measured signals, frequency filtering, time-frequency transformations. A case study.

     

    Week 7:     Intelligent sensors in the medicine, pulse, blood pressure, ECG measurements, anemometers, blood-oxygen measure, touch-sensors.

     

    Week 8:     The fundamental features of the P2P computer networks. The most important procedures of the routing on the wireless sensors.

     

    Week 9:     Mobile sensors, wireless solutions, System-on-Chip Body sensor networks and communication interfaces.

     

    Week 10:  Architectures and communication electronics of the sensors of Body Area Network (BAN). Power supply of the implemented sensors, implanted sensors for pressure-measuring, multipath data communication solutions, protocols

     

    Week 11:  Medical supervisor tools, supervision of nursing homes of elders, touch-free location-free sensor system

     

    Week 12:  Telemetric systems in the telemedicine, systems based on mobile networks and Internet. Case studies of present-day solutions. Databases, expert systems.

     

    Week 13:  Multimedia processing in telemedical sensor networks. Processing-partitioning in case of wide, shared sensor networks.

     

    Week 14:  Data security of the telemedicine networks, security of the personal data with the possibilities of the conciliar, case study.

     

    9. Method of instruction Oral presentation with case studies

     

    10. Assessment a.           In the study period:

     

    Passing the midterm

     

    b.          In the examination period:

     

    Oral examination

     

    c.        Preliminary examination:

     

    Its precondition is the good result of the midterm.

     

    11. Recaps The failed midterm can be repeated in the examination period in the repeated midterm.
    The failed repeated midterm can be repeated once again for extra fee.

     

    12. Consultations Consultation is possible based on the reconciliation with the teacher.

     

    13. References, textbooks and resources F. Kovács, Cs. Horváth, Á. T. Balogh, G. Hosszú: Extended Non-Invasive Fetal Monitoring by Detailed Analysis of Data Measured with Phonocardiography, IEEE Trans. on Biomed. Eng. 58, 1 (Jan. 2011), pp. 64-70

     

    F. Kovács, M. Török, Cs. Horváth, Á. T. Balogh, T. Zsedrovits, A. Nagy, G. Hosszú: A New, Phonocardiography-Based Telemetric Fetal Home Monitor System, Telemedicine and e-Health, 16,8 (Oct. 2010), pp.878-882.

     

    G. Hosszú: “Reliability Issues of the Multicast-based Mediacommunication” chapter in book, Encyclopedia of Multimedia Technology and Networking, Editor: Margherita Pagani, Idea Group Reference, Hershey, USA, 2005, ISBN: 1-59140-561-0, pp. 875-881.

     

    G. Hosszú: “Current Multicast Technology” chapter in book, Encyclopedia of Information Science and Information Technology, Vol. I-V., Editor: Mehdi Khosrow-Pour, Idea Group Reference, Hershey, USA, 2005, ISBN: 1-59140-553-X, pp. 660-667.

     

    14. Required learning hours and assignment
    Classes56
    Preparation for classes14
    Preparation for test20
    Homework 
    Learning the prescribed matters 
    Preparation for exam30
    Sum120
    15. Syllabus prepared by
    Name:

     

    Position:

     

    Department.:

     

    Ferenc Kovács, DSc.

     

    Professor

     

    Department of Electron Devices

     

    Gábor Hosszú PhD.

     

    Associate Professor

     

    Department of Electron Devices