1. SECOND CYCLE - MASTER'S DEGREE
  2. THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES
  3. COMPUTER ENGINEERING DEPARTMENT
  4. 1281 Computer Engineering
Course Information Course Learning Outcomes Course's Contribution To Program ECTS Workload Course Details
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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
CENG 545NEXT GENERATION IOT APPLICATIONS3 + 02nd Semester7,5

COURSE DESCRIPTION
Course Level Master's Degree
Course Type Elective
Course Objective In the future, IoT devices are expected to be smarter and context-aware with advanced memory, processing and reasoning abilities Also, it is predicted that the next generation IoT systems will have features such as self-configuring, self-optimizing, self-protection and self-healing. The aim of this course is to gain theoretical knowledge and practical skills about next generation IoT systems. In this context, it is aimed to develop self-optimizing semi-autonomous architectures and mechanisms by enabling the development of deep learning models based on fog and edge computing approaches.
Course Content Internet of Things (IoT) basic concepts, IoT Architecture and Components, IoT Communication / Messaging Protocols, Future Trends in IoT, Next Generation IoT (NGIoT) Concept and Applications, NGIoT and Big Data, NGIoT and Artificial Intelligence, Deep Learning Applications in NGIoT
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.

COURSE LEARNING OUTCOMES
1Explain the concepts of IoT and NGIoT
2List NGIoT requirements
3Compare the differences between NGIoT and IoT
4Analyze NGIoT application area problems
5Solve NGIoT problems using scientific research methods
6Interpret the gained knowledge in the field of NGIoT by integrating it with information from related disciplines
7Develop and deepen your knowledge in the NGIoT field to an expert level
8Use the expert theoretical and applied gained knowledge in the field of NGIoT

COURSE'S CONTRIBUTION TO PROGRAM
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Sub Total            
Contribution000000000000

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Hours for off-the-classroom study (Pre-study, practice)14342
Mid-terms12121
Final examination14040
Report / Project15050
Total Work Load

ECTS Credit of the Course





195

7,5
COURSE DETAILS
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L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes