ADLINK Technology, a global
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
optimized 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 closes the loop on the full cycle of machine learning model
building-from design to deployment to improvement-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 modeling 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 optimized on certified ADLINK devices, including our NEON
industrial smart camera, EOS
vision system, and deep
learning accelerator card and GigE
frame grabber with Intel Movidius Myriad X VPU.