[video]
Presenter: Sanjeev Heda
Manufacturers are constantly looking for new ways to improve their production processes. Using cameras and computer vision is a new way to provide coverage for potential issues that is more cost effective than traditional sensing techniques. But just having a computer vision model is not enough to generate insights that drive action. Organizations need a complete analytic pipeline that has all the necessary components to transform input data sets into actionable insights. This analytic pipeline must have sufficient accuracy to have confidence in predictions, minimal latency to provide these decisions in a timely manner, and have the ability to deploy and scale to multiple cameras and facilities. See how this analytic pipeline for a manufacturing use case can be built and operationalized with SAS Viya using SAS Visual Data Mining and Machine Learning and SAS Event Stream Processing. We will show how the analytic pipeline consumes multiple data sources, contains multiple post-processing analytic techniques to interpret and generate actionable information from the computer vision model outputs, leveraging technology optimized for compute, and the intermixing of both SAS and open source technology in the same analytic pipeline.
