Smart Cities Courses

  • This course is intended to introduce students to different technologies used in Smart Mobility. Special emphasis is given to how these relate to traffic operations, active mobility and road safety. We will explore issues related to impact of technologies on mobility and transportation infrastructure. The course is self contained with preliminary concepts explained in advance during the lectures. Students will learn basic Python Programming skills as they will interact, collaborate and work on topics relevant to the smart mobility and infrastructure. They will be exposed to the latest relevant research through papers readings, projects and presentations. Guest lecturers will be invited to present expert related materials, to bring practical experience to the classroom, and to promote interactive discussions on the subject. [ CEE 9412 Course Outline ]
  • This course is designed to provide a comprehensive overview of data management techniques and technologies relevant to Smart Cities and focusing on Civil and Environmental Engineering applications such as transportation and urban infrastructure. Students will explore the role of data in enhancing urban planning and decision-making processes, learning essential coding and data analysis skills. Through hands-on projects, collaborative learning, and interactive discussions, they will engage with real-world scenarios demonstrating the importance of data-driven solutions in urban environments. The course activities include relevant smart cities data management projects and readings of the latest research papers on data management and its applications in smart cities. By the end of the course, students will have a solid understanding of the core concepts related to data management in smart city contexts, reinforced by case studies, expert seminars, group projects, and course assignments.  [ CEE 9414 Course Outline ]
  • Application of Data Analytics/Machine Learning in urban water including drinking water, wastewater and stormwater infrastructure design, operation and maintenance to achieve resilient, sustainable and cost-effective water management. [ CEE 9415 Course Outline ]
  • Introduction to the concepts of structural health monitoring (SHM) and smart infrastructure management systems. Topics include data acquisition systems and testing methods such as vibration testing, acoustic emission and image-based methods of structures using smart sensors; data mining using AI; structural condition assessment using operational modal analysis; damage identification and localization using timeseries methods, time-frequency. [ CEE 9516 Course Outline ]
  • The objective of this course is to provide essential knowledge required to manage and implement BIM technologies in construction process, provide professionals with relevant skills to use BIM in the design and construction of facilities, with an emphasis on structural and civil roles, and Use of BIM software in the process of preparing the models, analysis and documentation. [ CEE 9518 Course Outline ]
  • Probability, statistics and reliability with special application to engineering; data analysis, probability distributions, sampling theory, probability of failure and elementary decision theory. [ CEE 9520 Course Outline ]
  • This course offers a comprehensive introduction to smart mobility in smart cities. It addresses the nature and characteristics of smart cities and smart mobility, providing a focus on smart mobility services within urban areas and the opportunities and challenges associated with the application of advanced technologies. The definition of mobility adopted for the course is the ease of movement or travel within an urban area. The course places an emphasis on decarbonization possibilities and the potential for smart city mobility services to reduce emissions and fuel consumption while optimizing modal use, along with risk identification and management using a structured approach. A focus is also placed on the need for end-to-end decision support for smart city mobility services. Overall, the course provides a framework for effective smart mobility planning, design, operations and performance management.  [ CEE 9695 Course Outline ]
  • A gentle introduction to the field of data science and machine learning with applications in civil engineering. Topics include unsupervised and supervised learning, feature engineering, decision trees, support vector machines, and deep neural networks. [ CEE 9730 Course Outline ]