COURSE UNIT TITLE

: SMART CITY INFORMATION SYSTEMS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CSC 5035 SMART CITY INFORMATION SYSTEMS ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

Offered to

Computer Science
Ph.D. in Computer Science

Course Objective

This course aims to provide an integrated framework approach for the information system and data analytics applications, which are used extensively in modern urban environments through information and communications technologies.

Learning Outcomes of the Course Unit

1   Analyze the digital infrastructure of a city and develop new conceptual data models
2   Analyze and design information flow architectures for urban systems
3   Plan and design data exchange applications between legacy and new information systems for an effective data-driven city management
4   Determine key performance indicators for smart city information systems and strategies
5   Design and implement functional designs for smart city integration projects

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Information systems
2 Smart city concept, Urban informatics Homework 1
3 Urban systems, Smart city models
4 ICT standardisation requirements, Information flow
5 Ubiquitous computing in the city
6 Data exchange interoperability between information systems Homework 2
7 Smart systems, Society, Government, Housing, Economy, Mobility and Safety in the city
8 Project progress report presentations
9 Data & information policies, Open, Big, Cloud, IoT (Internet of Things)
10 Sustainability of the smart city systems Homework 3
11 Key performance indicators for smart cities
12 Case Study presentations
13 City analytics, Prescriptive and predictive approaches
14 Systems integration, Information management
15 Project presentations

Recomended or Required Reading

Textbook(s): Frequently cited articles from the recent literature.
Supplementary Book(s): ISO/IEC JTC 1, Smart cities: Preliminary report, International Organization for Standardization & International Electrotechnical Commission, 2014.
N. Marz, and J. Warren, Big Data: Principles and best practices of scalable real-time data systems, Manning, 2015.

Planned Learning Activities and Teaching Methods

The course is taught in a lecture, class presentation and discussion format. Besides the taught lecture, group presentations are to be prepared by the groups assigned and presented in a discussion session. In some weeks of the course, results of the homework given previously are discussed.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG ASSIGNMENT
2 PRS PRESENTATION
3 FCG FINAL COURSE GRADE ASG * 0.50 + PRS * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

ugur.eliiyi@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 13 4 52
Preparing assignments 3 15 45
Preparing presentations 2 10 20
Project Preparation 1 40 40
Project Assignment 3 2 6
TOTAL WORKLOAD (hours) 205

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.1444
LO.2444
LO.3444
LO.4555
LO.5555