NSF invests in AI-ready test beds to accelerate U.S. leadership
The U.S. National Science Foundation announced over $2 million in planning grants to support the development of artificial intelligence-ready test beds — real-world environments that will accelerate the design, evaluation and deployment of AI technologies across sectors critical to America's economy and prosperity.
The initiative is a joint effort led by the NSF directorates for Computer and Information Science and Engineering (NSF CISE) and Technology, Innovation and Partnerships (NSF TIP), implementing a priority issued in the White House’s recent AI Action Plan to invest in secure, real-world settings that allow researchers to prototype new AI systems and translate them to the market.
"The AI-ready test beds program is uniquely NSF," said Ellen Zegura, NSF acting assistant director for CISE. "It leverages critical, existing test environments to drive AI progress. This initiative not only builds the foundation for new breakthroughs in AI research but also helps bridge the gap between research and applications by connecting researchers with real-world challenges and enabling them to explore how AI can be most effectively applied in practice."
As AI systems become increasingly integrated into areas ranging from emergency response to wireless networks, evaluating their reliability and performance beyond controlled settings is essential to developing long-term, impactful solutions that benefit the nation. NSF's test bed investments ensure that AI breakthroughs are tested for impact, scalability and built to serve the public good.
"It's clear that AI holds transformative potential to reshape how our world functions," said Erwin Gianchandani, NSF assistant director for TIP. "The AI-ready test beds program is designed to help researchers across academia and industry accelerate that transformation by simulating the dynamic, real-world conditions that AI systems and technologies will encounter as they scale and deploy. By catalyzing living labs focused on critical sectors and use-cases, this program lays the foundation for what could become essential infrastructure for a promising AI-enabled future."
The awarded projects explore the application of AI across a diverse range of areas, including wireless and radio communications, smart transportation, disaster planning and precision agriculture, among others.
The following provides a summary of some awarded projects:
STAIRWAI to COSMOS: Sensor-enabled Test Bed for Advancing Innovative Research in Wireless+AI. Led by Rutgers University–New Brunswick, this new test bed combines wireless technology with AI to improve the performance and reliability of next-generation networks. Built on the NSF-funded COSMOS project, a city-scale programmable test bed in West Harlem, STAIRWAI will focus on using AI to enhance wireless network performance and management while also optimizing wireless infrastructure to support the effective deployment of AI systems. This combined approach could lead to solutions for challenges in advanced manufacturing, smart cities, transportation and beyond.
Artificial Intelligence for Agriculture (AI4Ag) test bed. Led by Cornell University, AI4Ag will build an AI-ready living lab at the Cornell Agricultural Systems test bed, aimed at advancing AI innovations for agricultural and food systems. By developing and safely testing new AI technologies in real-world farming conditions, this test bed will help farmers grow crops more efficiently, reduce resources such as water and fertilizer, and adapt to changing climate and market conditions, delivering tangible benefits to farmers, consumers and the broader food supply chain.
TRACE: Test Bed for Disaster Resilience Auditing and Crisis Evaluation. Led by the University of Maryland, Baltimore County, the Test Bed for Disaster Resilience Auditing and Crisis Evaluation (TRACE) will use AI, robotics, sensors and real-time data to enable faster, smarter responses to emergencies like wildfires, earthquakes, snowstorms and hurricanes. TRACE could transform how cities prepare for, respond to and recover from natural disasters, helping search and rescue teams make more informed decisions in emergencies.
SmartSenseAI Lab: Holistic Evaluation of ML Research for AV-enabled Transportation Services. The University of Michigan, Ann Arbor, will enhance the NSF-funded Mcity 2.0 test bed — an integrated automated test bed for autonomous transportation research — to support safer and more realistic testing of self-driving cars, drones and the machine learning systems that power them. The upgrades will allow researchers to test algorithms in end-to-end driving scenarios, including interactions between vehicles, people and infrastructure. It will also explore how to support new services such as delivery drones, robotaxis and automated charging or cleaning, with the potential to accelerate the deployment of safer, more reliable autonomous transportation technologies.