COURSE UNIT TITLE

: SMART CITIES AND URBAN TECHNOLOGIES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
PLN 3482 SMART CITIES AND URBAN TECHNOLOGIES ELECTIVE 2 0 0 3

Offered By

City and Regional Planning

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR HAYAT ZENGIN ÇELIK

Offered to

City and Regional Planning

Course Objective

The main aim of the course is to explain the concept of smart city to students and to introduce the technologies used to make cities sustainable, efficient, safe and livable. This course emphasizes the use of information and communication technologies
in urban areas, as well as exploring solutions to make cities smarter and more innovative. It aims to introduce tools that can be used to produce studies that enable urban systems such as infrastructure, transportation, energy, water management, waste management, security and services to function more effectively using advanced technologies and data analytics. In addition to the perspective expected to be gained through theoretical explanations, it is aimed to design virtual cities with computer games. In addition, it is expected that students will gain the techniques and perspective that they can integrate into project courses,
competitions and various applications.

Learning Outcomes of the Course Unit

1   To have knowledge about the concept of smart cities and its components
2   Learn about data science, artificial intelligence, digital twin cities concepts
3   Having the ability to follow new technologies and integrate them into urban research areas
4   To have knowledge about the use of technologies in city planning and city information systems
5   Gaining a perspective on solving problems related to the cities of the future, exploring potentials and simulating citie

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to urban technologies and its importance
2 Smart cities concept and application examples
3 Smart cities of the future and innovative technologies
4 Digital twin cities and city simulation
5 Virtual city applications
6 Virtual city applications
7 Midterm
8 Augmented reality technology and potential applications in the city
9 Project idea development and application areas
10 Project idea development and application areas
11 Project idea development and application areas
12 Project critique
13 Project critique
14 General evaluation and discussion
15 Final delivery notification
16 Final submission

Recomended or Required Reading

References:
- Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, 2013, Anthony M. Townsend

- Smart Cities: Governing, Modelling and Analysing the Transition, 2014, Mark Deakin ve Husam Al Waer

Planned Learning Activities and Teaching Methods

Lectures on the content of the course will be made through interactive presentations. In addition to presentations, an understanding of student participation will be adopted with practice examples in the course. Modular teaching technique will be used.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FINS FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + ASG * 0.30 + FINS * 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + ASG * 0.30 + RST * 0.40


Further Notes About Assessment Methods

None

Assessment Criteria

Learning outcomes of defining concepts and describing them with examples will be evaluated in the midterm exam. Relating the subjects, criticizing the examples and proposing alternative solutions will be evaluated in the assignment and the final exam.

Language of Instruction

Turkish

Course Policies and Rules

Optional, if the instructor needs to add some explanation or further note, this column can be selected from the DEBIS menu.

Contact Details for the Lecturer(s)

hayat.zengin@deu.edu.tr

Office Hours

Will be announced

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 2 24
Student Presentations 1 2 2
Preparations before/after weekly lectures 12 1 12
Preparation for midterm exam 1 9 9
Preparation for final exam 1 24 24
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 75

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14PO.15PO.16PO.17
LO.111
LO.211
LO.311
LO.41
LO.51