Edge Insights for Vision

Combine data from point-of-sale systems, scales, cameras, and RFID readers to prevent loss at checkout.

Monitor traffic intersections via IP cameras to optimize traffic flow. Detect vehicles and pedestrians, record vehicle types and counts, calculate velocity and acceleration, and more.

Use computer vision, deep learning, and edge networking to develop a solution for managing driver behavior and alertness.

Use computer vision and sensors to detect products removed from a cooler or cabinet, count inventory, identify the need for maintenance, and more.

Create an end-to-end pipeline to detect social distancing, a COVID-19 preventive measure. Apply deep learning models from the Intel® Distribution of OpenVINO™ toolkit.

Use a video source to generate a visual heat or motion map to count the number of people that enter and exit a smart venue, store, factory, or warehouse aisle.

Use computer vision inference in the Intel® Distribution of OpenVINO™ toolkit to provide analytics on customer engagement, store traffic, and shelf inventory, optimizing retail operations.

Single-click deployment of a ready-to-use cloud to edge inferencing pipeline.​ You are responsible for payment of all third-party charges, including payment for use of Amazon Web Services (AWS).

Install web-based application to securely connect devices to Azure IoT*. You are responsible for payment of all third-party charges, including payment for use of Microsoft Azure* services.

Integrate video streams from a variety of edge devices into computer vision applications.

Gain insight into consumer behavior by using computer vision models to identify patterns in customer volume and flow.