- Build a data ingestion pipeline for easy aggregation and contextualization.
- Integrate external and internal databases (weather, GIS, etc.)
- Automate the digital inspection process and check for defects on valuable equipment such as pipes, boilers, tanks, and flare stacks with pre-built ML models.
- Train pre-built ML models with incremental learning as you review and validate defects on a dedicated user interface.
- Generate reports automatically.
- Integrate collaborative tools fully.
- Link work orders to specific teams and equipment IDs.
- Elaborate on predictive models by cross analyzing with industrial and IoT data.
Published by olivier@jill © Alteia 2024
