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 + 01st 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.
Mode of Delivery Face to Face

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
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11PO 12
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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)14570
Assignments5840
Mid-terms11515
Final examination12828
Total Work Load

ECTS Credit of the Course





195

7,5
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2023-2024 Fall1İBRAHİM KÖK


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Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
CENG 545 NEXT GENERATION IOT APPLICATIONS 3 + 0 1 Turkish 2023-2024 Fall
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Asts. Prof. Dr. İBRAHİM KÖK ikok@pau.edu.tr MUH A0257 %
Goals 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.
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
Topics
Materials
Materials are not specified.
Resources
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam50Final Exam
Midterm Exam50Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes