A Good System for Smart Cities

 

AI technologies can build safer and smarter cities and help us monitor and evaluate how new and critical infrastructure will affect access to housing, jobs, and public services, but city datasets are fragmented across domains and practically inaccessible to the general public. This project seeks to build an AI system that will link city datasets – extracting useful information, identifying data bias, making better and safer decisions within complex and dynamic environments, and ensuring responsible data use. Building on these different datasets, this research will also develop digital twin models for different critical infrastructures (e.g. fire, transportation, water, energy) to monitor the status, visualize different scenarios, and mitigate emerging challenges in critical infrastructures.

Team Members


Arya Farahi
Statistics and Data Science
Geological Sciences and Civil, Architectural, and Environmental Engineering
Catherine Cubbin
Steve Hicks School of Social Work
Devrim Ikizler
Economics
Jun-Whan Lee
Civil, Architectural and Environmental Engineering
Paul Navratil
Texas Advanced Computing Center
Desmond Ong
Psychology
Kijin Seong
Texas Advanced Computing Center
Electrical and Computer Engineering
Project Co-Lead
Junmin Wang
Mechanical Engineering

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