Abstract
This US-Japan joint research project aims to apply and expand the concept of ?digital twins? into disaster science and build a ?Disaster Digital Twin? (DDT) which utilizes human-centered data to improve community resilience. The DDT will capture the evolution of a disaster and its impacts to humans, creating an approximate replica in the cyberworld through sensing, computing, and communication.
Performance Period: 04/01/2024 - 03/31/2027
Award Number: 2420847
Collaborative Research: CPS: NSF-JST: Enabling Human-Centered Digital Twins for Community Resilience
Lead PI:
Nalini Venkatasubramanian
Abstract
This US-Japan joint research project aims to apply and expand the concept of ?digital twins? into disaster science and build a ?Disaster Digital Twin? (DDT) which utilizes human-centered data to improve community resilience. The DDT will capture the evolution of a disaster and its impacts to humans, creating an approximate replica in the cyberworld through sensing, computing, and communication.
Performance Period: 04/01/2024 - 03/31/2027
Award Number: 2420846
Abstract
Critically ill patients receive multiple treatments, which can be automated for clinicians to enable focus on high-level decision-making tasks, while reducing effort on tedious monitoring and titration tasks. However, automation of multiple critical care treatments presents unique challenges. Each treatment given to a patient elicits multiple physiological changes. Thus, when multiple isolated automated treatments are given to a patient, they can conflict and drive the patient to unsafe physiological states. Regardless, most previous work has neglected such conflicts.
Performance Period: 04/15/2024 - 03/31/2027
Award Number: 2322534
Collaborative Research: CPS: Medium: Automating Complex Therapeutic Loops with Conflicts in Medical Cyber-Physical Systems
Lead PI:
Jin-Oh Hahn
Abstract
Critically ill patients receive multiple treatments, which can be automated for clinicians to enable focus on high-level decision-making tasks, while reducing effort on tedious monitoring and titration tasks. However, automation of multiple critical care treatments presents unique challenges. Each treatment given to a patient elicits multiple physiological changes. Thus, when multiple isolated automated treatments are given to a patient, they can conflict and drive the patient to unsafe physiological states. Regardless, most previous work has neglected such conflicts.
Performance Period: 04/15/2024 - 03/31/2027
Award Number: 2322533
Abstract
This research project focuses on using uncrewed aerial systems (UAS) to monitor and track natural disaster events like wildland fires and flooding rivers and lakes. As the intensities of these events continue to increase worldwide due to climate change, the need for their early monitoring and tracking has also increased. A UAS, consisting of a team of uncrewed aerial vehicles (UAVs) and one or more ground stations, can provide real-time monitoring and tracking of unfolding disaster events, as well as help with relief operations to avoid large scale losses of lives and property.
Performance Period: 03/01/2024 - 02/28/2027
Award Number: 2343062
Abstract
This NSF Civil Infrastructure Systems project will create the world?s first fully automated augmented-reality test facility for autonomous transportation research. Connected and automated vehicle (CAV) technologies have the potential to significantly improve safety, mobility, and sustainability, but also pose great challenges in technical and social dimensions including control, sensing, communication, human-in-the-loop, etc.
Performance Period: 10/01/2022 - 09/30/2026
Award Number: 2223517
EAGER: IMPRESS-U Adaptive Infrastructure Recovery from Repeated Shocks through Resilience Stress Testing in Ukraine
Lead PI:
Rafael Munoz-Carpena
Abstract
This IMPRESS-U project is jointly funded by NSF, Estonian Research Council (ETAG), Research Council of Lithuania (LMT), National Science Center of Poland (NCN), US National Academy of Sciences, and Office of Naval Research Global (DoD). The research will be performed in a multilateral international partnership that unites the University of Florida (US), G.E. Pukhov Institute for Modelling in Energy Engineering of the NAS of Ukraine (PIMEE), Kiyv (Ukraine), National Technical University of Ukraine ?Igor Sikorsky Kyiv Polytechnic Institute?
Rafael Munoz-Carpena
Dr. Rafael Muñoz-Carpena is a Distinguished Professor in the Department of Agricultural and Biological Engineering, focused on hydrological modeling and monitoring of complex integrated environmental systems. He earned MSc. and BSc. Agricultural Engineering degrees from the Polytechnic University of Madrid (Spain), and a Ph.D. in Biological and Agricultural Engineering at North Carolina State University (USA) as Fulbright scholar. Two distinct features of his research and teaching program are the innovative integration of physical, biological, and engineering design principles applied to a wide range of critical issues, such as water pollution, environmental health, and systems resilience, along with the internationalization and active professional development and placement of graduate and postdoctoral water engineers and scientists. He actively participates in interdisciplinary expert groups and panels worldwide. The model he developed, the Vegetative Filter Strips Modeling System (VFSMOD), has been accepted as a reference tool for study and design of vegetative filter strips and is used regularly to control runoff pollution by state and federal agencies, and by research institutes in more than 20 countries. He has authored or co-authored more than 400 peer-reviewed journal articles and technical publications, 2 books, and eleven book chapters. He has received numerous international and national recognitions like elected Fellow of AAAS (American Association for the Advancement of Science) and ASABE (American Society of Agricultural and Biological Engineers), Elected Foreign Member of the Royal Society of Engineering of Spain, ASABE’s John Deer Gold Medal and ADS/Hancor Soil Water national awards, National Postdoctoral Association Mentoring Award, and the UF “International Educator”, “Dissertation Mentoring”, and “High Impact Research” awards."
Performance Period: 05/01/2024 - 04/30/2026
Award Number: 2402580
Abstract
Digital representations that replicate 3D physical objects at low latency and high accuracy, known as ?live 3D digital twins,? are the next advance in cyber-physics systems. In the transportation domain where vehicles are highly instrumented with 3D sensors that, e.g., include LiDAR and stereo cameras, their data will be continuously streamed and fused into a digital representation that provides accurate real-time situational awareness for the driver and the transportation infrastructure itself, promoting greater safety and efficiencies.
Performance Period: 05/01/2024 - 04/30/2026
Award Number: 2348461
Abstract
This EArly-concept Grant for Exploratory Research (EAGER) award supports research to expand the effectiveness, range of application and affordability of artificial intelligence (AI) in the design and manufacturing of products. The focus of the project is on the use of AI to identify geometrical similarities between new part designs and the designs of parts that have already been successfully manufactured.
Performance Period: 05/15/2024 - 04/30/2026
Award Number: 2415752
CRII: CPS: FAICYS: Model-Based Verification for AI-Enabled Cyber-Physical Systems Through Guided Falsification of Temporal Logic Properties
Lead PI:
khouloud Gaaloul
Abstract
In the world of smart systems, a captivating real-time fusion occurs where digital technology meets the physical world. This synergy has been significantly transformed by the integration of artificial intelligence (AI), a move that, while dramatically enhancing system capabilities, also introduces a layer of complexity, presenting new challenges in ensuring their safety, reliability, and accuracy.
Performance Period: 03/01/2024 - 02/28/2026
Award Number: 2347294