Hydra: Computer Vision for Online Data Quality Monitoring

Conference · Mon May 06 00:00:00 EDT 2024 · EPJ Web of Conferences

DOI:https://doi.org/10.1051/epjconf/202429502008· OSTI ID:2406488

Jeske, Torri ^[1]; Britton, Thomas ^[1]; Lawrence, David ^[1]; Rajput, Kishansingh ^[1]

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1. Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States)

Hydra is a system utilizing computer vision for near real-time data quality monitoring. Currently operational across all of Jefferson Lab’s experimental halls, it reduces the workload of shift takers by autonomously monitoring diagnostic plots during experiments. Hydra uses "off-the-shelf" supervised learning technologies and is supported by a comprehensive MySQL database. To simplify access, web apps have been developed to facilitate both labeling and monitoring of Hydra’s inferences. Hydra can connect with the alarm system and incorporates complete historical tracking, enabling it to identify issues that shift takers could miss. When issues are detected, a natural first question is: "Why does Hydra think there is a problem?" To answer, Hydra employs Gradient-weighted Class Activation Maps (GradCAM) to identify regions of the image that are important for the specific classification. This interpretive layer enhances transparency and trustworthiness, which is essential for integration with experiment workflows and operation. The Hydra system, results, and sociological considerations for deployment will be discussed.

• Research Organization: Thomas Jefferson National Accelerator Facility, Newport News, VA (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Nuclear Physics (NP)
• DOE Contract Number: AC05-06OR23177
• OSTI ID: 2406488
• Report Number(s): JLAB-CST-23-3929; DOE/OR/23177-7155
• Journal Information: EPJ Web of Conferences, Journal Name: EPJ Web of Conferences Vol. 295; ISSN 2100-014X
• Country of Publication: United States
• Language: English