About AR-STRIDES
Funded by National Science Foundation Award OIA #2445877, AR-STRIDES is building competitive research infrastructure and capacity to position teams of researchers and educators in Arkansas to be leaders in data-driven supply chain technologies and data analytics solutions for next generation transportation and logistics.
Research Infrastructure
Statewide Initiative
NSF EPSCoR Funded
Core Projects
Data
Provisioning
Data Provisioning for Machine Learning/Artificial Intelligence (AI) Transportation Models is developing a readily accessible data repository and provisioning service focused on representative and public transportation datasets.
Geospatial
AI
A Geospatial Foundation Model to Enable Next-Generation Transportation Analysis and Prediction addresses challenges of complex and interconnected geospatial data and will result in a research testbed for next-generation transportation tasks.
Secure Cloud
Computing
Secure and Reliable Cloud Computing System for Smart Transportation Services designs and implements a prototype secure cloud computing system tailored for smart transportation services.
Synthetic Data
Generation
Synthesis, Analysis, and Synthetic Data Generation of Supply Chain and Freight Indicators quantifies variation in supply chain activity to generate synthetic data for the research, testing, and development communities in transportation statistics.
Workforce
Development
The AR-STRIDES Workforce Development team provides students and teachers in Arkansas with data analytics and AI learning opportunities to help meet the state’s demand for data analytics talent in the transportation and logistics industry.
Research Focus Areas
Arkansas is a natural laboratory to address use-inspired research challenges for next generation transportation and logistics systems.
Artificial Intelligence for Next-Generation Transportation & Logistics
Developing artificial intelligence solutions for multimodal mobility
Harnessing Data for Next-Generation Vehicles
Creating innovative data-driven solutions in connected and autonomous vehicles
Unmanned Aerial Mobility
Data Mining
Interpreting large and complex data sets generated from unmanned aerial systems