The University of North Dakota (UND) is spearheading a new initiative to develop an AI-powered system aimed at improving operations in the Arctic. This project involves creating a Kubernetes cluster, named after the Ancient Greek term for “helmsman,” which will drive the Arctic Knowledge-Based System (A-KBS). The system is designed to support decision-making in cold weather environments through real-time data analytics and long-term forecasting.
The initiative, supported by a research contract from the US Army Corps of Engineers Research and Development Center, marks the first deployment of a Kubernetes cluster with supercomputing capabilities at UND. Principal Investigator Timothy Pasch emphasized the importance of advanced situational awareness and predictive analytics in tackling challenges in the Arctic.
Naima Kaabouch and Aaron Bergstrom are co-leading this project alongside Pasch. They aim to handle vast amounts of data, including satellite imagery and LiDAR scans, using AI-driven decision support tools. A Science Gateway developed with NCEAS will deploy Globus Compute to transmit data securely for processing at the San Diego Supercomputing Center.
Aaron Bergstrom highlighted that this cyberinfrastructure enables geospatial forecasting critical for Arctic infrastructure investment and national preparedness. The initiative also includes collaborative research with SUNY Stony Brook on sustainable materials development and Virginia Tech on engineering resilient infrastructure.
At UND, several graduate students and faculty members are collaborating closely on various aspects of this project under Pasch’s leadership.
