Come see how you can build digital industrial IoT assets using AWS IoT Core, AWS IoT Greengrass, Amazon FreeRTOS, Amazon Sumerian, and Amazon SageMaker. AWS services help customers reduce downtime and improve operational efficiencies by lowering your mean time to repair. In this chalk talk, we highlight best practices and architecture for a conveyor belt demo, showing the art of the possible. Learn how you can use AWS services to connect assets, build digitized repair instructions in AR, and perform ML inference at the edge.

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Create intelligent industrial
equipment with AWS IoT services &
AR/VR
Chris Azer
IoT specialist solutions architect
AWS/Public Sector
S V C 3 0 1

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Agenda
Conveyor belt demo use case
Overview of AWS IoT services and Amazon Sumerian
Demo
Architecture

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We built this demo to show how AWS technologies can be combined to build a 3D
digital asset that can solve different use cases across industrial automation, fleet
management, maintenance, and technician training.

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Use cases to demo addresses
• Operation & maintenance
• Operators have a real-time view into the status and state of assets and processes
• Field technicians can access an interactive digital “manual” that reacts to the state of an asset
• Training
• Sumerian provides a platform to build “look inside” views that can be used to train operators and
technicians on the operation and maintenance of assets and processes via augmented or virtual
environments

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How can this benefit manufacturing?
• Operation & maintenance
• Reduce mean time to repair (MTTR) by giving operators and maintenance digital operating procedures
to perform repair.
• Use ML interference to predict failures and introduce stoppage events before a critical failure occurs.
• VR scenes can provide a real-time dashboard view with situational awareness, providing quick drill
downs into problem areas.
• Training
• Other common downtime situations can be attributed to high turnover of employees. Building real-time
assets with “look inside” views can be used to train operators and technicians on the operation and
maintenance of assets and processes.

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Use case: Object detection
How:IngestindustrialcameradataviaAWSIoTGreengrassanduseAmazonSageMakerMLmodelstodetectproducttypeorvisualdefects.Notify
Operations/MaintenanceviaAmazonSNS.
SNS
IoT Rule (all data)
S3 data lake
Kinesis
Data Firehose
Industrial camera
Email
SMS
Amazon S3
Glacier
Amazon
Kinesis Data
Analytics
ML
inference
AWS IoT/Greengrass/
Device Management/
Device Defender
Amazon SageMakerML models
Amazon QuickSight
Amazon Kinesis
Data Streams
Amazon
Kinesis Data
Firehose
IoT anomaly
data repository
Amazon
Athena
Amazon
Athena
IoTRule(alerts)
Realtimeand
historicalvisualization
CloudWatch
Amazon Cognito
CloudTrail
AWS Config
IoT Cert
IAM
AWS IoT Greengrass
AWS Cloud
AWS IoT Analytics

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Main parts of the demo
• An IoT-connected conveyor belt (built in our lab)
• An AWS IoT service is used to control the operation of the conveyor belt and report conveyor
operational data, such as RPM and vibrations, for analysis and reporting
• A Sumerian application that enables a 3D web view of the conveyor belt that
provides the virtual replica of the conveyor belt
• An AWS DeepLens device has been trained with a machine learning model to
detect weapons that are moving across the conveyor belt and report via the IoT
service and Sumerian application
• Beyond image analysis, ML interference can be trained to predict imminent failures
• Loud noises from motor
• Bearing failures from abnormal vibrations or high temperatures

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AWS IoT architecture

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Device
Gateway
Rules
Engine
Message
Broker
Device
Shadow
Registry
Identity
Service
AWS IoT Core
Manage authorization of
devices & provision
unique identities at scale
Fully manage connectivity
optimized for IoT workloads
Define and catalog device
for easy use by AWS
services
Understand and control
the status of your device at
any time
Reliable and fast
communication across
your IoT fleet
Ingest large amounts of IoT
data at a low cost, pre-
process it, & make it
available to 10+ services for
analytics, reporting, &
visualization

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Data and
state sync Security
Over-the-air
updatesConnectors
Operate
devices offline &
synchronize data
when reconnected
Local
actions
Simplify device
programming with
AWS Lambda
Mutual
authentication &
authorization
between cloud and
devices
Easily update AWS IoT
Greengrass Core
Machine
learning
inference
Perform ML
Inference
locally
Local
resource
access
AWS Lambda
functions can
access & use local
resources of a given
device
Extend edge devices
with connections to
external services
Local
messages
and triggers
Enable device
communication
without a cloud
connection
Secrets
Manager
Deploy secrets to
edge devices
AWS IoT Greengrass

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What is Amazon Sumerian?

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High-level architecture overview
Amazon
Sumerian
AWS IoT
Core
Amazon
FreeRTOS
AWS DeepLens
Amazon Cognito
Amazon Polly
Sync shadow
Transmit telemetry
Sumerian
publishes cross-
platform scene
Syncs with conveyor
shadow and updates
scene based on
conveyor state

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Direction arrows (state machines)
Sumerian Scene
Reported state
Desired state
IoT Shadow

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Troubleshooting walkthrough (timelines)
Digital Asset
Sumerian Scene
Reported state
IoT Shadow

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Amplify (authentication & IoT policy)
Sumerian Scene
Cognito
+
User
React Hosting on
S3
IoT Core

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IoT subscription options
Sumerian Scene
React Hosting on
S3
IoT Core
Sumerian Scene
IoT Shadow
Sumerian Scene
IoT Core
Get IoT Shadow
Subscribe to IoT
shadow and
telemetry data

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http://bit.ly/IoTConveyor

24. Thank you!
S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Chris Azer
Tim Wilson