Intel® Edge Software Hub

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.

Predict performance issues with manufacturing equipment. Perform local or cloud analytics on any issues found and predict when failures might arise.

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

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

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

Deploy industrial AI application for product quality checks using OpenNESS platform. Includes support for two types of defect detection.

Consolidate visual intelligence and wireless workloads at traffic intersections. This container is hosted in an Open Network Edge Services Software (OpenNESS) edge node.

Use battery-operated, smart wireless sensor devices at the edge that communicate to mobile or stationary gateways with cloud connectivity.

Use classification models and computer vision algorithms, optimized by Intel® Distribution of OpenVINO™ toolkit, to identify defects in a textile manufacturing or printing facility.

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.

Optimize the deployment of deep learning models and network capabilities for digital images by applying cloud native architectures for on-premise health care applications.

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.