Networked Sensors

Data is displayed for the academic year: 2024./2025.

Lecturers

Prof.
Vedran Bilas
PhD
Prof.
Darko Vasić
PhD
Asst. Prof.
Dinko Oletić
PhD

Seminar

Prof.
Vedran Bilas
PhD

Course Description

Low-power electronic systems design, Sensors and sensor applications, Embedded networked sensors, Energy sources and power management

Study Programmes

University graduate
[FER3-HR] Audio Technologies and Electroacoustics - profile
Elective Courses (2. semester)
[FER3-HR] Communication and Space Technologies - profile
Elective Courses (2. semester)
[FER3-HR] Computational Modelling in Engineering - profile
Elective Courses (2. semester)
[FER3-HR] Computer Engineering - profile
Elective Course of the profile (2. semester)
Elective Courses (2. semester)
[FER3-HR] Computer Science - profile
Elective Courses (2. semester)
[FER3-HR] Control Systems and Robotics - profile
Elective Courses (2. semester)
Elective Courses of the Profile (2. semester)
[FER3-HR] Data Science - profile
Elective Courses (2. semester)
[FER3-HR] Electrical Power Engineering - profile
Elective Courses (2. semester)
[FER3-HR] Electric Machines, Drives and Automation - profile
Elective Courses (2. semester)
[FER3-HR] Electronic and Computer Engineering - profile
Elective Courses (2. semester)
Elective Courses of the Profile (2. semester)
[FER3-HR] Electronics - profile
Elective Courses (2. semester)
[FER3-HR] Information and Communication Engineering - profile
Elective Courses (2. semester)
Elective Courses of the Profile (2. semester)
[FER3-HR] Network Science - profile
Elective Courses (2. semester)
Elective Courses of the Profile (2. semester)
[FER3-HR] Software Engineering and Information Systems - profile
Elective Courses (2. semester)

Learning Outcomes

  1. design low power sensor data acquisition
  2. develop battery operated low power embedded sensor systems
  3. design energy harvesting and power management for embedded networked sensors
  4. apply sensor networks in various applications
  5. Choose components of electronic subsystems of embedded sensor systems
  6. Analyze sources of power consumption of embedded sensor systems

Forms of Teaching

Lectures

Interactive teaching

Independent assignments

SOTA seminar

Grading Method

Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Seminar/Project 0 % 45 % 0 % 45 %
2. Mid Term Exam: Written 0 % 20 % 0 %
Final Exam: Oral 35 %
Exam: Written 0 % 20 %
Exam: Oral 35 %

Week by Week Schedule

  1. Low-power sensor operation
  2. Self calibaration, adaptation, Smart analog interfaces, A/D conversion
  3. Low-power IC, Low-power digital systems, Ultra low-power analog processing ans wake-up
  4. Bus interfaces, Telemetry
  5. Serial buses
  6. Wireless sensor networks
  7. Low-power communications, Wireless sensor networks
  8. Midterm exam
  9. Wireless sensor networks
  10. Power management, Energy harvesting
  11. Energy harvesting
  12. RFID systems
  13. Seminar
  14. Seminar
  15. Final exam

Literature

Massimo Alioto (2017.), Enabling the Internet of Things, Springer
Yen Kheng Tan (2017.), Energy Harvesting Autonomous Sensor Systems, CRC Press

General

ID 223697
  Summer semester
5 ECTS
L1 English Level
L1 e-Learning
30 Lectures
5 Seminar
0 Exercises
0 Laboratory exercises
0 Project laboratory
0 Physical education excercises

Grading System

90 Excellent
75 Very Good
60 Good
50 Sufficient

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