AWS, Intel, Adlink Team for AI at the Edge
December 2, 2019
ADLINK
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.
|