Hydra: computer vision for data quality monitoring

被引：0

作者：

Britton, Thomas ^{[1
]}

Jeske, Torri ^{[1
]}

Lawrence, David ^{[1
]}

Rajput, Kishansingh ^{[1
]}

机构：

[1] Thomas Jefferson National Accelerator Facility, VA, Newport News, United States

来源：

Journal of Instrumentation | 2024年 / 19卷 / 12期

关键词：

Data assimilation - Data transfer - Gluing - Metadata - Network security;

D O I：

10.1088/1748-0221/19/12/C12005

中图分类号：

学科分类号：

摘要：

Hydra, initially developed for Hall-D in 2019, is a system that utilizes computer vision to perform near real time data quality monitoring. Since then, it has been deployed across all experimental halls at Jefferson Lab, with the CLAS12 collaboration in Hall-B being the first outside of GlueX to fully utilize Hydra. The system comprises back end processes that manage the models, their inferences, and the data flow. The front-end components, accessible via web pages, allow detector experts and shift crews to view and interact with the system. © 2024 IOP Publishing Ltd and Sissa Medialab. All rights, including for text and data mining, AI training, and similar technologies, are reserved.

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