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ADLINK teams with Intel and AWS

ADLINK Technology, a leader in edge computing, has joined forces with Intel and Amazon Web Services (AWS) to simplify artificial intelligence (AI) at the edge for machine vision.

The integrated solution offers an Amazon Sagemaker-built machine learning model optimised by and deployed with the Intel Distribution of OpenVINO toolkit, the ADLINK Edge software suite, and certification on AWS Greengrass.

The ADLINK AI at the Edge solution looks to close the loop on the full cycle of machine learning model building - from design to deployment to improvement - and does this by automating edge computing processes so that customers can focus on developing applications without needing advanced knowledge of data science and machine learning models.

The ADLINK AI at the Edge solution features:

  • Intel Distribution of OpenVINO toolkit, optimizes deep learning workloads across Intel® architecture, including accelerators, and streamline deployments from the edge to the cloud.
  • Amazon Sagemaker, a fully-managed service that covers the entire machine learning workflow.
  • AWS Greengrass, which extends AWS to edge devices so they can act locally on the data they generate, while still using the cloud for management, analytics, and durable storage.
  • The ADLINK Data River, offering translation between devices and applications to enable a vendor-neutral ecosystem to work seamlessly together.

·The ADLINK Edge software suite, which builds a set of deployable applications to communicate with end-points, devices or applications and which publish and/or subscribe to data topics on the ADLINK Data River.

“We’ve worked on multiple industrial use cases that benefit from AI at the edge, including a smart pallet solution that makes packages and pallets themselves intelligent so they can detect where they're supposed to be, when they're supposed to be there, in real-time,” said Toby McClean, VP, IoT Innovation & Technology, at ADLINK. “This enables warehouse customers to yield improved logistics and productivity, while also decreasing incorrectly shipped packages and theft. And this use case can be replicated across verticals to improve operational efficiency and productivity.”

Additional use cases include object detection modelling for object picking functions or worker safety, such as identifying product defects on conveyor systems or worker impediments in manufacturing environments, and equipment failure predictions to reduce machine downtime and increase productivity.

AI at the Edge software capabilities can be fully optimised on certified ADLINK devices, including the company's NEON industrial smart camera, EOS vision system, and deep learning accelerator card and GigE frame grabber with Intel Movidius Myriad X VPU.

Author
Neil Tyler

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