Hybrid architecture for distributed operations
Edge and center deployment supports near real-time video analysis, continuous monitoring, and remote supervisory visibility.
Sinopec Case Study
Sinopec operates drilling platforms, transport lines, and LNG terminals across wide regions. Awakedata delivered a hybrid edge + center AI architecture for 24/7 safety analysis, visual monitoring, and model optimization, helping teams improve both incident response and inspection accuracy.
Deployment context: This project combined task-specific model training with deployed instrument-reading applications. The results describe the original customer project.
A practical architecture built for complex, multi-site oil and gas field environments.
Edge and center deployment supports near real-time video analysis, continuous monitoring, and remote supervisory visibility.
The delivered solution combines task-specific model training and field deployment to automate instrument reading, improving inspection consistency and data timeliness.
Operational efficiency gains from expanded AI deployment across inspection and patrol workflows.
Reduction in manual patrol input requirements.
Daily inspection time reduced for a single operating zone.
Overall operation efficiency improvement.
Patrol robot operation efficiency increase.
Hidden-risk closed-loop handling efficiency increase.
Sinopec’s project connected task-specific model development to inspection in the field. It demonstrates the importance of training for the actual task, validating the results, and fitting deployment to the operating environment.
Explore Studio for model and application development, Edge for production execution, and Hub for deployment and event management.
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