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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS ISM 2032 ARTIFICIAL INTELLIGENCE AND AUTOMATION IN CONSTRUCTION MACHINERY ELECTIVE 2 1 0 3

Offered By

HEAVY EQUIPMENT OPERATOR

Level of Course Unit

Short Cycle Programmes (Associate's Degree)

Course Coordinator

DOCTOR YASEMIN YAHŞI

Offered to

HEAVY EQUIPMENT OPERATOR

Course Objective

To ensure that students studying in the field of construction equipment operation have basic knowledge about artificial intelligence, automation and digital technologies; to understand the working principles of artificial intelligence-supported construction equipment and operator support systems; to teach the effects of artificial intelligence on construction equipment in terms of safety, efficiency and sustainability; and to help students develop their skills to work with these technologies in the future.

Learning Outcomes of the Course Unit

1   Explains the basic concepts and working principles of artificial intelligence. 2   Defines the areas of use of artificial intelligence technologies in construction equipment. 3   Evaluates the role of simulation and virtual reality applications in operator training. 4   Recognizes artificial intelligence-supported safety and maintenance systems and explains the advantages of these systems. 5   Explains the basic features of sensors, data collection and analysis systems used in construction equipment. 6   Understands the importance of continuous learning by adapting to new technologies.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to Artificial Intelligence: Definition, history and basic concepts 2 Basics of Machine Learning and Automation Systems 3 Industrial Applications of Artificial Intelligence and Its Reflection in Construction Equipment 4 Autonomous and Semi-Autonomous Construction Equipment: Working logic 5 Smart Sensors, Data Collection and Real-Time Monitoring Systems 6 AI-supported Safety and Accident Prevention Systems 7 Midterm Exam 8 Training with Virtual Reality and Simulation 9 Training with Virtual Reality and Simulation 10 Training with Virtual Reality and Simulation 11 Construction Equipment Simulators: Review and practical examples 12 Construction Equipment Simulators: Review and practical examples 13 Current Developments: Autonomous trucks, construction sites and robotic excavation systems 14 Final

Recomended or Required Reading

To be announced.

Planned Learning Activities and Teaching Methods

Theoretical knowledge presentation Simulation and virtual reality applications

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MT MIDTERM 2 FINS FINAL EXAM 3 FCGR FINAL COURSE GRADE (RESIT) MT*0.40+FINS*0.60 4 RST RESIT 5 FCGR FINAL COURSE GRADE (RESIT) MT*0.40+RST*0.60

Further Notes About Assessment Methods

None

Assessment Criteria

Attendance, participation, midterm and final exams

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Dr. Yasemin YAHŞI yasemin.yahsi@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 13 2 26 Tutorials 13 1 13 Preparations before/after weekly lectures 13 1 13 Preparing presentations 1 6 6 Preparation for midterm exam 1 6 6 Preparation for final exam 1 6 6 Other (watching artwork belong to visual arts) 1 3 3 Midterm 1 1 1 Final 1 1 1 TOTAL WORKLOAD (hours) 75

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 PO.11 PO.12 PO.13 LO.1 1 3 3 3 4 5 LO.2 1 2 2 2 3 4 LO.3 1 3 3 3 4 4 LO.4 1 4 4 5 5 5 LO.5 1 3 3 5 5 5 LO.6 1 2 4 5 5 4