At the end of this course, the students; 1) Know the basic concepts, definitions and personal and industrial application areas of IoT. 2) Know IoT architecture and components, platforms and communication protocols used for IoT. 3) Know IoT communication protocols. 4) Design, develop, test and deploy an IoT application and architecture. 5) Know machine learning and deep learning applications with IoT. 6) Know security and used methods, techniques and tools in IoT applications.
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
None
COURSE DEFINITION
The goal of this course is to gain knowledge and skills to identify and classify Internet of Things (IoT) approaches, methods, technical tools, and equipment, and to develop appropriate hardware and software for IoT projects. RFID, NFC, BLE Beacon, WSN, GSM used to develop IoT software with IoT business models, IoT connection and communication technologies and protocols, big data processing with IoT, components of IoT architectural design, Restful, CoAP, MQTT, DDS, AMQP communication protocols etc. are the study topics, which are also are among the course topics to be covered.
COURSE CONTENTS
WEEK
TOPICS
1st Week
Introduction of the course and presenting its objectives, concepts and definitions related to IoT, application areas (personal, industrial, smart applications, etc.)
2nd Week
Overview of IoT architecture and components, platforms and communication protocols used for IoT
3rd Week
Design of an architecture for IoT applications, installation of application development platform sand integration problems with other systems.
4th Week
IoT communication protocols (Restful, CoAP, MQTT, DDS, AMQP communication protocols and RFID, NFC, BLE Beacon, WSN, GSM technologies used to develop IoT software)
5th Week
Design and development of IoT applications
6th Week
Design and development of IoT applications
7th Week
Testing, deployment and maintenance of IoT applications
8th Week
Midterm
9th Week
Storage, data integrity check, processing and analysis of IoT data
10th Week
IoT and artificial intelligence applications (machine learning, deep learning)
11th Week
Security methods, techniques and tools used for IoT applications
12th Week
Cloud computing and Edge applications with IoT
13th Week
Research assignments and presentations
14th Week
Term project presentations and evaluation
RECOMENDED OR REQUIRED READING
1. Misra S. , Mukherjee A. and Roy A. (2021). Introduction to IoT, Cambridge University Press, UK. 2. Vuppalapati C. (2020). Building Enterprise IoT Applications, CRS Press, USA. 3. Chakravarthi, V.S. (2021). Internet of Things and M2M Communication Technologies: Architecture and Practical Design Approach to IoT in Industry 4.0, Springer, USA. 4. James, Alice, Seth A.V. and Mukhopadhyay, S.C. (2022). IoT System Design: Project Based Approach, Springer, USA. 5. Madhumathy P.M, Vinoth K.and Umamaheswari R. (2022). Machine Learning and IoT for Intelligent Systems and Smart Applications, CRS Press, USA. 6. Nayak P., Ray N. and Ravichandran (2022). IoT Applications, SecurityThreats, and Countermeasures, CRS Press, USA. 7. Nayak P., Ray N. and Ravichandran (2022). Industrial IoT Application Architectures, CRS Press, USA. 8. Peng S.-L., Pal S. and Huang L. (2020). Principles of Internet of Things (IoT) Ecosystem: Insight Paradigm, Springer, USA.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
Lecture,Questions/Answers, Grup Projesi
ASSESSMENT METHODS AND CRITERIA
Quantity
Percentage(%)
Mid-term
1
40
Project
1
30
Total(%)
70
Contribution of In-term Studies to Overall Grade(%)
70
Contribution of Final Examination to Overall Grade(%)
30
Total(%)
100
ECTS WORKLOAD
Activities
Number
Hours
Workload
Midterm exam
1
1,5
1,5
Preparation for Quiz
Individual or group work
14
1
14
Preparation for Final exam
1
22
22
Course hours
14
3
42
Preparation for Midterm exam
1
14
14
Laboratory (including preparation)
Final exam
1
1,5
1,5
Homework
Presentation (including preperation)
1
3
3
Project
1
24
24
Report writing
1
23
23
Total Workload
145
Total Workload / 30
4,83
ECTS Credits of the Course
5
LANGUAGE OF INSTRUCTION
Turkish
WORK PLACEMENT(S)
No
KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)
