COMPUTER ENGINEERING
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Ders Genel Tanıtım Bilgileri

Course Code:

1410002022

Ders İsmi:

Autonomous Systems

Ders Yarıyılı:

Fall

Ders Kredileri:

Theoretical	Practical	Credit	ECTS
3	0	3	5

Language of instruction:

Ders Koşulu:

Ders İş Deneyimini Gerektiriyor mu?:

Type of course:

Bölüm Seçmeli

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Dr.Öğr.Üyesi Recep DURANAY

Course Lecturer(s):

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:

To teach the conceptual structure of the types of intelligent and autonomous systems

Course Content:

Definition and Analysis of Autonomic Systems, Autonomic Nervous System and
Energy for Hypothalamus, Intelligent and Autonomous Systems, Autonomous Systems
Collection Autonomous (Driverless) Vehicles and Autonomous Vehicle Creator Sub
Systems, Precision Positioning System and Global Orbit Planning
System, Environmental Perception and Meaning System. Decision Making
system. Local Trajectory Planning System, Decision Implementation and Support
system. A Simple Application Example, BGP (Border Gateway
Protocol Fundamentals, Autonomous Robots Introduction, Industry 4.0
and Autonomous Robots, Autonomous Unmanned Aerial Vehicles, Autonomous security
multipurpose drones, Autonomous Flight System, unmanned systems, aviation,
cockpit systems, systems engineering, software engineering and management,
Embedded System Solutions for Autonomous Systems Embedded for Drones
System Solutions

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Knows the operating system design that makes access to resources on autonomous systems understandable for the user.
2) Knows the properties and properties of distributed systems.
3) Knows resource management and design principles, inter-process communication principles, process/processor management, consistency control algorithms, memory and file management in distributed systems and conducts current research on these issues.
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
1) Stability analysis for autonomous systems with Lyapunov approach / Stability analysis for non-autonomous systems with Lyapunov-like approaches
2) Will be able to analyze the stability of autonomous systems with Lyapunov approach.
Field Specific Competence
1) It supports the design of products with high market value. It is geared towards the technologies of the future with its Innovative Thinking and Problem Solving approach.
Competence to Work Independently and Take Responsibility
1) As an approach that develops with Innovative Thinking and Problem Solving approach, it offers solutions suitable for today's technological needs.

Ders Akış Planı

Week	Subject	Related Preparation
1)	Definition and Analysis of Autonomous Systems
2)	Energy Harvesting for Autonomous Systems
3)	Autonomous (Driverless) Vehicles and Subsystems that Make up the Autonomous Vehicle
4)	Precise Positioning System and Global Orbital Planning System	Course Book
5)	Environmental Perception and Meaning System
6)	Local Orbital Planning System
7)	Decision Implementation and Support System
8)	Midterm
9)	Basics of BGP (Border Gateway Protocol)
10)	Autonomous Robots Introduction
11)	Industry 4.0 and Autonomous Robots
12)	Autonomous Unmanned Aerial Vehicles
13)	Autonomous Military drones	Course Book
14)	Autonomous Flight System, unmanned systems
15)	Final

Sources

Course Notes / Textbooks:	Intelligent Autonomous Systems: Foundations and Applications, editör: Dilip Kumar Pratihar,Lakhmi C. Jain, 2. A. Tanenbaum, “Distributed Systems”, Prentice Hall, 3. G. Coulouris e.al, "Distributed Systems
References:	Intelligent Autonomous Systems: Foundations and Applications, editör: Dilip Kumar Pratihar,Lakhmi C. Jain, 2. A. Tanenbaum, “Distributed Systems”, Prentice Hall, 3. G. Coulouris e.al, "Distributed Systems

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları	1	2	3	4	5	6	7
Program Outcomes
1) PO 1.1) Sufficient knowledge in mathematics, science and computer engineering
2) PO 1.2) Ability to apply theoretical and applied knowledge in mathematics, science and computer engineering for modeling and solving engineering problems.
3) PO 2.1) Identifying complex engineering problems
4) PO 2.2) Defining complex engineering problems
5) PO 2.3) Formulating complex engineering problems
6) PO 2.4) Ability to solve complex engineering problems
7) PO 2.5) Ability to choose and apply appropriate analysis and modeling methods
8) PO 3.1) Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions.
9) PO 3.2) Ability to apply modern design methods under realistic constraints and conditions for a complex system, process, device or product
10) PO 4.1) Developing modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications
11) PO 4.2) Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications
12) PO 4.3) Ability to use information technologies effectively.
13) PO 5.1) Examination of complex engineering problems or discipline-specific research topics, designing experiments
14) PO 5.2) Examination of complex engineering problems or discipline-specific research topics, experimentation
15) PO 5.3 ) Analysis of complex engineering problems or discipline-specific research topics, data collection
16) PO 5.4) Analyzing the results of complex engineering problems or discipline-specific research topics
17) PO 5.5) Examining and interpreting complex engineering problems or discipline-specific research topics

Ders - Öğrenme Kazanımı İlişkisi

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	PO 1.1) Sufficient knowledge in mathematics, science and computer engineering
2)	PO 1.2) Ability to apply theoretical and applied knowledge in mathematics, science and computer engineering for modeling and solving engineering problems.
3)	PO 2.1) Identifying complex engineering problems
4)	PO 2.2) Defining complex engineering problems
5)	PO 2.3) Formulating complex engineering problems
6)	PO 2.4) Ability to solve complex engineering problems
7)	PO 2.5) Ability to choose and apply appropriate analysis and modeling methods
8)	PO 3.1) Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions.
9)	PO 3.2) Ability to apply modern design methods under realistic constraints and conditions for a complex system, process, device or product	5
10)	PO 4.1) Developing modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications
11)	PO 4.2) Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications
12)	PO 4.3) Ability to use information technologies effectively.
13)	PO 5.1) Examination of complex engineering problems or discipline-specific research topics, designing experiments
14)	PO 5.2) Examination of complex engineering problems or discipline-specific research topics, experimentation
15)	PO 5.3 ) Analysis of complex engineering problems or discipline-specific research topics, data collection
16)	PO 5.4) Analyzing the results of complex engineering problems or discipline-specific research topics
17)	PO 5.5) Examining and interpreting complex engineering problems or discipline-specific research topics

Öğrenme Etkinliği ve Öğretme Yöntemleri

Ölçme ve Değerlendirme Yöntemleri ve Kriterleri

Yazılı Sınav (Açık uçlu sorular, çoktan seçmeli, doğru yanlış, eşleştirme, boşluk doldurma, sıralama)
Homework

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
total		%
PERCENTAGE OF SEMESTER WORK		% 0
PERCENTAGE OF FINAL WORK		%
total		%

İş Yükü ve AKTS Kredisi Hesaplaması

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Midterms	1	30	30
Final	1	40	40
Total Workload			112