Archives: Tooltips
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GMU-26-4
GuardianPath AI is a predictive, human-centered AI platform that quantifies K–12 pedestrian safety by assigning every student commute a time-aware Safety Score. Unlike traditional Safe Routes to School assessments that rely…
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DT-RICH-26-7
The KNIME AI Learning Center at the NSF DT-RICH IUCRC—will serve as a national hub for rapidly building, sharing, scaling, and educating digital twin technologies using the KNIME low-code AI workflow platform.…
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DT-RICH-26-1
Natural hazards, conflict, space incidents, and public health crises have claimed thousands of lives and caused hundreds of billions of dollars in asset losses. Reducing these losses requires a clear…
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GMU-26-3
Wildfires are increasing in both frequency and intensity, posing escalating risks to lives, property, air quality, infrastructure, and public health. This project investigates how the integration of physics-based and AI-driven…
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GMU-26-1
Uncertainty Quantification (UQ) is a critical component of digital twin systems, as it enhances confidence in actionable information and builds trust among end users. Using water quality, flooding, and agriculture as representative…
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DT-RICH-26-3
The rapid proliferation of data centers has introduced localized environmental stressors—including episodic air pollutant emissions, waste heat, and intensive resource consumption—that may adversely affect community health. Current assessment approaches rely largely…
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DT-RICH-26-4
Airspace congestion is increasing rapidly, raising the risk of collisions across both aviation and space operations. Recent incidents—ranging from mid-air hazards over the Potomac River to damage of returning space capsules by…
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DT-RICH-26-8
K-12 school systems face persistent, complex challenges that demand innovative, AI-enabled solutions. This project positions high school students—those who experience these challenges most directly—as early innovators and problem-solvers. The SAIL…
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DT-RICH-26-2
Digital twin applications increasingly rely on large-scale, continuously operating computing infrastructure, yet current infrastructure operations remain largely reactive, fragmented, and manually intensive, particularly in system monitoring and issue diagnosis. We propose a…