Introduction to Smart Infrastructure Systems

Course Description

The course will include lectures that provide historical background of smart infrastructure systems, fundamental concepts of decision-making, data representation, sensing and actuation networks, and associated challenges specific to smart cities applications. Basics concepts of probability and statistics, optimization, and uncertainty and risk will be introduced to help students build a solid foundation for machine learning and engineering system modeling. The course includes assignments that will provide hands-on experience on applying what they have learned from lectures. The students will conduct a comprehensive independent research project on topics related to smart infrastructure systems to enhance their understanding of a specific topic of their interest. This course will cover topics including sensing systems, data visualization, probabilistic modeling, Bayesian updating, convex optimization, uncertainty and risks, as well as open-ended topics related to policy, economics, and information security challenges in infrastructure monitoring and decision-making. 3 credits Grading Letter graded (A, A-, B+, etc.)

Code

CIV 550

Credits

3

Subject

CIV