This Guidance helps you reduce the time required to set up an in-plant computer vision (CV) quality detection system. It provides workflows and interfaces that enable quality subject matter experts to train CV models so that you don’t have to procure expensive data scientists. The architecture includes a series of interfaces for one-touch gateway onboarding, which eliminates the need for specialized personnel to set up, deploy, and manage the gateways and CV models. The architecture also uses edge technology, machine learning (ML), and user interfaces to initiate quality inference, orchestrate gateway deployments, calculate key performance indicators (KPIs), and visualize data through dashboards.
