Summary
This conference paper describes DAQ Expert, an automated expert system developed for the CMS experiment at CERN's Large Hadron Collider to enhance data acquisition efficiency and operational reliability. The system employs real-time monitoring and automated fault recovery protocols to minimise downtime, reduce human error, and decrease on-call expert requirements, achieving fully automatic recovery capability by the end of Run 2. The authors present operational experience, design principles for encoding expert knowledge, and web-based interfaces facilitating human–machine cooperation in particle physics data-taking operations.
UK applicability
This work has limited direct applicability to UK farming systems, soil health, or nutrition research, as it concerns particle physics instrumentation and data systems rather than agricultural or food systems science.
Key measures
CMS downtime reduction in 2018 run; frequency and effectiveness of automated recovery events; operator workload and on-call expert demand; system availability metrics
Outcomes reported
The study reports on the design, implementation, and operational performance of DAQ Expert, an automated expert system deployed in 2017 to improve data-taking efficiency of the CMS experiment. It measured improvements in downtime recovery, reduction in human operator burden, and the capability of fully automatic fault recovery without human intervention by the end of Run 2.
Topic tags
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