Core of FLOW eye is an advanced AI image recognition algorithm that continuously tracks conveyed items and thereby detects, predicts, and prevents anomalies in the physical material flow.
It is able to precisely localize anomalies such as blockages, doubles, damages, theft, manual errors, and others in real-time, recognize patterns, identify triggers and make predictions. By interacting with the conveyors’ control system, it can generate commands to re-route or re-align items, or trigger emergency stops of the system.
FLOW eye’s knowledge is not only site specific, it also learns from other detections within the deployed network.
All of the performance data can be analyzed in a real-time KPI dashboard that also allows for customizable reports. Based on these insights, the occurrence and location of frequent anomalies are automatically evaluated as the basis for system enhancements.
The mobile app alerts operators of all incidents, including exact locations, so they no longer have to search for them themselves.
FLOW eye gathers its data via robust detection units that are suitable for assisted self-installation. Their installation is completely non-disruptive and works conveyor OEM agnostic.
Existing CCTV streams may also be integrated if their coverage is beneficial.