November 3, 2022, Filed Under: Digital twin, ProjectsActive Fire Incident Map This project provides active fire incidents of every major city on an interactive map. The tracker is updated in almost real-time from all over the nation. This live tracker updates with the latest smoke runoff from each fire, keeping you well informed and out of danger, as well as keeps… read more
September 3, 2022, Filed Under: Artificial Intelligence, ProjectsConvergent, Responsible, and Ethical AI Training Experience (CREATE Roboticists) CREATE Roboticists will train future roboticists who: (i) understand the ethical implications of service robots and can develop new theories, methods, and techniques to satisfy ethical requirements; (ii) design human-centered ethical service robots that respect human autonomy and ethical values; and (iii) develop robotics policy informed by cutting edge convergent… read more
May 1, 2022, Filed Under: ProjectsShort to Medium Range Autonomous Delivery Systems (SMADS) An interdisciplinary team spanning across four UT labs is developing a building-to-building delivery system for the UT Austin campus using robots that will improve contactless deliveries and save people time. These robots will cross complex terrain, navigating around people, cars, and other obstacles typical to campus roadways. Team Members: Junfeng… read more
February 10, 2022, Filed Under: Deserts, ProjectsTransit Desert Research This website was developed using research methods created in the Urban Information Lab at the University of Texas at Austin. Each block group is classified as either a transit oasis, properly served area, or a transit desert. A transit oasis is an area with more transit service than normal for… read more
January 13, 2022, Filed Under: Health, ProjectsOptimize EMS Responses During Extreme Events Optimizing ambulance allocation and routing is one of the most efficient ways for EMS to save more lives at virtually no cost. However, current EMS software was developed under models that assume normal demands. They are unable to adapt to disasters such as the COVID-19 pandemic, where traffic patterns change,… read more
November 1, 2021, Filed Under: Health, ProjectsUrban Health Risk Mapping This project developed an AI system that can measure the health effects of neighborhood environments in ten major US cities using citizen crowd-sourced data. The research team mapped the computed health risk scores at the census tract-level for all selected municipalities and also built an interactive website that allows users… read more
October 3, 2021, Filed Under: ProjectsCountering Misinformation and Disinformation Older adults are especially vulnerable to believing and circulating disinformation online, and we want to enable this population to use social media more responsibly. We aim to do that in three ways. First, our research will investigate what kinds of disinformation is most widely believed by older adults – what… read more
July 3, 2021, Filed Under: ProjectsCameras, AI, and Public Values in Smart Cities This project investigates comparative policies around the creation and use of video data in the public sector. As more cities deploy monitoring and sensing technologies, cameras are in the front lines of data-gathering in traffic, policing, and health and safety. However, there are no commonly accepted standards for using the… read more
June 7, 2021, Filed Under: Deserts, ProjectsAustin AI Housing Analysis – Open Data Repository-Interactive Website We have created a website for Austin AI Housing Analysis. All the maps are interactive on this website. Team Members: Junfeng Jiao (Principal Investigator, Architecture), Weijia Xu (Texas Advanced Computing Center), Michelle Addington (Architecture), Ming Zhang (Architecture), Jake Wegmann (Architecture), Katie Pierce Meyer (University of Texas Libraries), Hao Zhu (Electrical… read more
March 3, 2021, Filed Under: Digital twin, ProjectsImproving Pedestrian Safety with Traffic Monitoring Camera and AI In collaboration with the Austin Transportation Department, we study pedestrian road use and identify potential safety concerns by analyzing existing traffic camera videos. Our approach automatically analyzes the content of video data from existing traffic cameras using a semi-automated processing pipeline powered by the state-of-art computing hardware and algorithms. Transportation… read more
