M.SC. in Computer Engineering (Without Thesis)

EEE 522 | Course Introduction and Application Information

Course Name

RF ID systems

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
EEE 522	Fall/Spring	3	0	3	7.5

Prerequisites	None
Course Language	English
Course Type	Elective
Course Level	Second Cycle
Mode of Delivery	-
Teaching Methods and Techniques of the Course	-
National Occupation Classification	-
Course Coordinator	-
Course Lecturer(s)	Doç. Dr. Diaa GADELMAVLA
Assistant(s)	-

Course Objectives

The aim of this course is to familiarize students with all aspects of technology used in modern RFID systems, including near and far field varieties. The physics, design, data structures and control mechanisms for RFID systems are covered. Students will also be familiarized with associated standards, emerging business process models, applications, and social issues arising from the use of RFID.

Learning Outcomes

#	Content	PC Sub	* Contribution Level
#	Content	PC Sub	1	2	3	4	5
1	To know the physical phenomena that governs the operation of near and far field RFID systems at the electro-magnetic and RF spectrum levels.
2	To understand how these physical phenomena dictate the characteristics of RFID components, especially readers and tags, and how these characteristics will have impact on the intended use of these components.
3	To know the industry standard algorithms used to discover, disambiguate, and encode data on RFID tokens.
4	To be able to select RFID system components based on physical measurement requirements and application specifications.
5	To be able to implement RFID technology in ICT systems to satisfy application needs in the areas of ID management, tracking, sensing, electronic payment, and industrial automation.
6	To know how security can be protected with respect to the RFID tokens, and the limitations of security methods used with respect to user privacy, robustness, application requirements and cost.

Course Description

Electro-magnetic resonance and magnetic curve based methods, Near field load modulated passive RFID methods, Full active transponders, Spectrum use and performance limitations, Data formats, encoding methods and standards, Data integrity and security for RFID, Multi-tag arbitration and addressing algorithms.

Course Category	Core Courses
	Major Area Courses
	Supportive Courses
	Media and Management Skills Courses
	Transferable Skill Courses

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week	Subjects	Related Preparation	Learning Outcome
1	Electro-magnetic resonance and magnetic curve based methods	Daniel M. Dobkin, The RF in RFID, Passive UHF RFID in Practice, Elsevier Newnes, 2007
2	Near field load modulated passive RFID methods	Daniel M. Dobkin, The RF in RFID, Passive UHF RFID in Practice, Elsevier Newnes, 2007
3	Semi-passive RFID methods	Daniel M. Dobkin, The RF in RFID, Passive UHF RFID in Practice, Elsevier Newnes, 2007
4	Full active transponders	Daniel M. Dobkin, The RF in RFID, Passive UHF RFID in Practice, Elsevier Newnes, 2007
5	Spectrum use and performance limitations	Daniel M. Dobkin, The RF in RFID, Passive UHF RFID in Practice, Elsevier Newnes, 2007
6	Data formats, encoding methods and standards	Daniel M. Dobkin, The RF in RFID, Passive UHF RFID in Practice, Elsevier Newnes, 2007
7	Data integrity and security for RFID	Daniel M. Dobkin, The RF in RFID, Passive UHF RFID in Practice, Elsevier Newnes, 2007
8	Multi-tag arbitration and addressing algorithms	Daniel M. Dobkin, The RF in RFID, Passive UHF RFID in Practice, Elsevier Newnes, 2007
9	Complex tag architectures for extra functions	Daniel M. Dobkin, The RF in RFID, Passive UHF RFID in Practice, Elsevier Newnes, 2007
10	Business models and systems for RFID use, and competing technologies	Daniel M. Dobkin, The RF in RFID, Passive UHF RFID in Practice, Elsevier Newnes, 2007
11	Social considerations arising from the use of RFID	Daniel M. Dobkin, The RF in RFID, Passive UHF RFID in Practice, Elsevier Newnes, 2007
12	In-class Presentations
13	In-class Presentations
14	In-class Presentations
15	In-class Presentations
16	Review of the Semester

Course Notes/Textbooks	The textbook referenced above and course slides
Suggested Readings/Materials	Related Research Papers

EVALUATION SYSTEM

Semester Activities	Number	Weighting	LO 1	LO 2	LO 3	LO 4	LO 5	LO 6
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury	1	20
Project	1	40
Seminar / Workshop
Oral Exams
Midterm
Final Exam	1	40
Total

Weighting of Semester Activities on the Final Grade	2	60
Weighting of End-of-Semester Activities on the Final Grade	1	40
Total

ECTS / WORKLOAD TABLE

Semester Activities	Number	Duration (Hours)	Workload
Theoretical Course Hours (Including exam week: 16 x total hours)	16	3	48
Laboratory / Application Hours (Including exam week: '.16.' x total hours)	16		0
Study Hours Out of Class	16	5	80
Field Work			0
Quizzes / Studio Critiques			0
Portfolio			0
Homework / Assignments			0
Presentation / Jury	1	45	45
Project	1	50	50
Seminar / Workshop			0
Oral Exam			0
Midterms			0
Final Exam	1	2	2
		Total	225

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#	PC Sub	Program Competencies/Outcomes	* Contribution Level
#	PC Sub	Program Competencies/Outcomes	1	2	3	4	5
1	Accesses information in breadth and depth by conducting scientific research in Computer Engineering, evaluates, interprets and applies information.		-	-	-	-	-
2	Is well-informed about contemporary techniques and methods used in Computer Engineering and their limitations.		-	-	-	-	-
3	Uses scientific methods to complete and apply information from uncertain, limited or incomplete data, can combine and use information from different disciplines.		-	-	-	-	-
4	Is informed about new and upcoming applications in the field and learns them whenever necessary.		-	-	-	-	-
5	Defines and formulates problems related to Computer Engineering, develops methods to solve them and uses progressive methods in solutions.		-	-	-	-	-
6	Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs.		-	-	-	-	-
7	Designs and implements studies based on theory, experiments and modelling, analyses and resolves the complex problems that arise in this process.		-	-	-	-	-
8	Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations, can work independently and takes responsibility.		-	-	-	-	-
9	Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale.		-	-	-	-	-
10	Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.		-	-	-	-	-
11	Is knowledgeable about the social, environmental, health, security and law implications of Computer Engineering applications, knows their project management and business applications, and is aware of their limitations in Computer Engineering applications.		-	-	-	-	-
12	Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity.		-	-	-	-	-