Program Overview

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Civil Engineering (MS) Smart Cities

The Master of Science in Civil Engineering with a focus on Smart Cities is a unique program designed to equip students with the knowledge and skills necessary to design, manage, and maintain the cities of the future. This program emphasizes smart transportation, resilient infrastructure, and technological applications in environmental engineering and water resources.

Program Overview

The Smart Cities track is part of the Master of Science in Civil Engineering program, offered by the College of Engineering and Computer Science at the University of Central Florida. This track is designed for students with a background in science or engineering who wish to pursue a career in civil engineering with a focus on smart cities.

Program Requirements

• Total Credit Hours Required: 30 credit hours minimum beyond the Bachelor's degree.
• Thesis/Nonthesis Option: Students can choose between a thesis and a non-thesis option. The thesis option requires 6 credit hours of thesis work, while the non-thesis option requires an additional 6 credit hours of elective courses and the submission of an end-of-program portfolio.

Required Course

• CGN5341 - Interdisciplinary Introduction to Smart Cities' Applications (3 credit hours): This course provides an interdisciplinary introduction to the applications of smart cities, covering topics such as smart transportation, resilient infrastructure, and technological advancements in environmental engineering and water resources.

Core Courses

Students must complete at least 3 of the following core courses:

• CCE5220 - Sustainable Infrastructure Systems (3 credit hours)
• CEG6610 - Smart Underground Structures: Tunnels and Shafts (3 credit hours)
• CES6876 - Smart City Built Infrastructure (3 credit hours)
• CGN5617 - Infrastructure Systems Optimization and Identification (3 credit hours)
• CGN6342 - Modeling Human Behavior with Emerging Data (3 credit hours)
• CGN6343 - Cyber-Physical Systems and Smart Cities (3 credit hours)
• ENV5128 - Smart Air Quality Monitoring and Air Pollution Control (3 credit hours)
• ENV6533 - Smart Water and Wastewater Management (3 credit hours)
• STA5703 - Data Mining Methodology I (3 credit hours)
• TTE5531 - Active Mobility and Technologies: Synergy and Challenges (3 credit hours)
• TTE5532 - Policy Aspects of Smart City Transportation (3 credit hours)
• TTE6533 - Mobility in Smart Cities: Technologies and Application Areas (3 credit hours)
• TTE6275 - Connected and Autonomous Vehicles (3 credit hours)
• TTE6608 - Algorithms and Models for Smart Cities (3 credit hours)
• CGN5340 - Internet of Things: Applications in Smart Cities (3 credit hours)

Elective Courses

Students must complete at least 4 of the following elective courses:

• CAP5415 - Computer Vision (3 credit hours)
• CAP5610 - Machine Learning (3 credit hours)
• CAP5738 - Visualization Techniques for Data Analysis (3 credit hours)
• CEN5016 - Software Engineering (3 credit hours)
• CGN6655 - Regional Planning, Design, and Development (3 credit hours)
• EEL5825 - Machine Learning and Pattern Recognition (3 credit hours)
• EEL6026 - Optimization of Engineering Systems (3 credit hours)
• EEL6671 - Modern and Optimal Control Systems (3 credit hours)
• EEL6683 - Cooperative Control of Networked Autonomous Systems (3 credit hours)
• EMA5104 - Intermediate Structure and Properties of Materials (3 credit hours)
• EMA5504 - Modern Characterization of Materials (3 credit hours)
• EMA6626 - Mechanical Behavior of Materials (3 credit hours)
• HMG6449 - Smart Travel and Tourism (3 credit hours)
• PAD5337 - Urban Design (3 credit hours)
• PAD5930 - Global Cities (3 credit hours)
• PAD5356 - Managing Community and Economic Development (3 credit hours)
• PAD6339 - Housing Development and Planning (3 credit hours)
• PAD6387 - Transportation Policy (3 credit hours)
• PAD6716 - Information Systems for Public Managers and Planners (3 credit hours)
• STA5104 - Advanced Computer Processing of Statistical Data (3 credit hours)
• STA5206 - Statistical Analysis (3 credit hours)
• STA5825 - Stochastic Processes and Applied Probability Theory (3 credit hours)
• STA6704 - Data Mining Methodology II (3 credit hours)
• STA6707 - Multivariate Statistical Methods (3 credit hours)
• STA6709 - Spatial Statistics (3 credit hours)
• TTE6270 - Intelligent Transportation Systems (3 credit hours)
• TTE6667 - Discrete Choice Modeling in Transportation (3 credit hours)
• URP6711 - Sustainable Transportation Planning (3 credit hours)

Track Prerequisites

A Bachelor of Science degree in civil engineering or another closely related engineering degree is required. Applicants without a directly related undergraduate degree may need to complete additional undergraduate courses.

Degree Requirements

The program requires a minimum of 30 credit hours beyond the Bachelor's degree, including required courses, core courses, elective courses, and either a thesis or a non-thesis option.

Financial Information

Graduate students may receive financial assistance through fellowships, assistantships, tuition support, or loans. For more information, see the College of Graduate Studies Funding website.

Fellowship Information

Fellowships are awarded based on academic merit to highly qualified students. They are paid to students through the Office of Student Financial Assistance, based on instructions provided by the College of Graduate Studies.

Equipment Fee

Students in the Civil Engineering MS program pay a $16 equipment fee each semester that they are enrolled. Part-time students pay $8 per semester.

Independent Learning

A research or design project serves as the independent learning experience for thesis students. Non-thesis students are required to take at least one of the courses marked with an asterisk (*), denoting an independent learning experience, and submission of an end-of-program portfolio.