Information Package

Master's of Defence Electronics and Software with Thesis

SEY519

SENSOR NETWORKS

Course Code
SEY519
Semester
-
Theory+Practice
3 + 0
ECTS
10
Course TypeElective Course
Course LevelMaster's Degree With Thesis
Year of Study-
Semester-
ECTS10
Name of Lecturer(s) -
Learning Outcomes

At the end of this course, the students;

  1. Types and characteristics of sensors used in defense technologies
  2. Wireless sensor networks
  3. Time-series analysis
  4. Internet of Objects (IoT)
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme ComponentsNone.
Course Descriptionypes and characteristics of sensors used in defense technology. Wireless sensor networks. Sensor signal processing. Specification. Time-series analysis. Time-series alignment. Similarity metrics. Classification. Analysis of multi-channel sensor data. Sensor data patterns. Data structures and algorithms for sensors. Internet of Objects (IoT).
Course Contents
WEEK TOPICS
1st Week Types and characteristics of sensors used in defense technologies
2nd Week Types and characteristics of sensors used in defense technologies
3rd Week Wireless sensor networks
4th Week Sensor signal processing
5th Week Property
6th Week Time-series analysis
7th Week Time-series alignment
8th Week Midterm
9th Week Similarity metrics
10th Week Classification
11th Week Analysis of multi-channel sensor data
12th Week Sensor data patterns
13th Week Data structures and algorithms for sensors
14th Week Internet of Objects (IoT)
Recommended or Required ReadingWireless Sensor Networks: Design Principles for Scattered Systems,Thomas Haenselmann,Werlag.
Planned Learning Activities and Teaching Methods
  • Lecture
  • Discussion
  • Questions/Answers
  • Case Study
  • Project
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 40
Total(%) 40
Contribution of In-term Studies to Overall Grade(%) 40
Contribution of Final Examination to Overall Grade(%) 60
Total(%) 100
ECTS Allocated Based on Student Workload
Activities Quantity Duration (Hour) Total Workload (Hour)
Midterm exam 1 2 2
Preparation for Quiz
Individual or group work 14 11 154
Preparation for Final exam 1 69 69
Course hours 14 3 42
Preparation for Midterm exam 1 44 44
Laboratory (including preparation)
Final exam 1 2 2
Homework
Total Work Load313
Total Work Load / 30 (h)10.43
ECTS Credit of the Course10
Language of InstructionTurkish
Work Placement(s)No
LO1 LO2 LO3 LO4
K1 X X
K2 X X X
K3 X X X
K4 X X
K5 X X X X
K6 X X
K7 X
K8 X X
K9 X X
K10 X X
K11 X X X