Aviva Launches Aviva Insight OMI App
IIoT app with built-in AI for real-time decision-making
Real-time operation through integration with Aviva System Platform


The amount of real-time operational and manufacturing data collected by Industrial Internet of Things (IIoT) apps is growing by the day. However, as the number of notifications and warnings increases, it becomes more difficult to distinguish between critical warnings and false notifications.

Accordingly, on the 10th, AVEVA launched the 'AVEVA™ Insight OMI' app, which improves operational agility by intervening in decision-making in real time with AI.

“Failure to respond to alerts from IIoT apps can result in lost operational time and resources,” said Rashesh Mody, head of AVEVA’s Monitoring and Control business unit. “By leveraging the AI capabilities and cloud analytics built into AVEVA Insight OMI, users can take preventative action before problems occur.”

The Aviva Insight OMI app implements AI in the control room or plant field to identify anomalies detected in real time on a situation-aware OMI visualization display.

It can be utilized by engineers, managers, and others in various industrial fields such as water and sewage, energy, and food and beverage.

The AVEVA Insight OMI app brings AI capabilities to the AVEVA System Platform, enhancing its ability to proactively alert equipment before problems occur and automatically detect abnormal operating patterns.

Users can be notified of business issues such as unplanned downtime or production loss before they become serious through advance warnings. It can be resolved quickly.

The AVEVA System Platform is a responsive and scalable solution that integrates enterprise processes with management and supervision, SCADA, HMI, and Industrial Internet of Things (IIoT) apps.

It provides a collaborative foundation for integrating equipment assets across all facilities to support continuous operational improvement and real-time decision-making. This enables the establishment of standardized systems for processes, each team, and field operations.

Additionally, AI-based notifications can be optimized with a simple mouse click, without any programming or data knowledge. As user feedback data accumulates, the AI prediction engine's accuracy improves, enabling it to send users appropriate notifications based on their importance.

When abnormal patterns are detected, apps within the HMI/SCADA solution capture them, allowing users to apply analytics where needed.