Publications

1 Result

Search results

Jump to search filters

Machine learning at the edge to improve in-field safeguards inspections

Annals of Nuclear Energy

Shoman, Nathan; Williams, Kyle A.; Balsara, Burzin; Ramakrishnan, Adithya; Kakish, Zahi K.; Coram, Jamie L.; Honnold, Philip H.; Rivas, Tania; Smartt, Heidi A.

Artificial intelligence (AI) and machine learning (ML) are near-ubiquitous in day-to-day life; from cars with automated driver-assistance, recommender systems, generative content platforms, and large language chatbots. Implementing AI as a tool for international safeguards could significantly decrease the burden on safeguards inspectors and nuclear facility operators. The use of AI would allow inspectors to complete their in-field activities quicker, while identifying patterns and anomalies and freeing inspectors to focus on the uniquely human component of inspections. Sandia National Laboratories has spent the past two and a half years developing on-device machine learning to develop both a digital and robotic assistant. This combined platform, which we term INSPECTA, has numerous on-device machine learning capabilities that have been demonstrated at the laboratory scale. This work describes early successes implementing AI/ML capabilities to reduce the burden of tedious inspector tasks such as seal examination, information recall, note taking, and more.

More Details
1 Result
1 Result