AWS IoT services provide a managed cloud platform that lets connected devices interact with cloud applications and other devices easily and securely. In this session, we will discuss how constrained devices can leverage AWS IoT Core to send data to the cloud and receive commands back to the device using the protocol of their choice. AWS Greengrass is software that lets you run local compute, messaging and data caching for connected devices in a secure way. AWS IoT Device Management is a service that makes it easy to securely onboard, organize, monitor, and remotely manage IoT devices at scale. With AWS IoT Analytics, you can run sophisticated analytics on massive volumes of IoT data without having to worry about the cost and complexity typically required to build your own IoT analytics platform.
21. Easily analyze IoT data
AWS IoT Analytics
Channels DatasetsPipelines Data stores Jupyter notebooks
& templates
AWS IoT Analytics is a service that processes, enriches, stores, analyzes,
and visualizes IoT data for manufacturers and enterprises.
22. AWS IoT Architecture
Secure device
connectivity
and messaging
Endpoints
Fleet onboarding,
management, and
SW updates
Fleet
audit and
protection
IoT data
analytics and
intelligence
Things
Sense & Act
Cloud
Storage & Compute
Secure local
triggers, actions,
and data sync
AWS IoT Core
Gateway
AWS Greengrass
AWS IoT Device
Management
AWS IoT Device
Defender
Intelligence
Insights & Logic → Action
a:FreeRTOS
a:FreeRTOS
AWS IoT
Analytics
23. Sense & Act
Things
Secure device
connectivity
and messaging
AWS IoT Core
Fleet onboarding,
management, and
SW updates
Fleet
audit and
protection
IoT data
analytics and
intelligence
AWS IoT Device
Management
AWS IoT Device
Defender
GatewayEndpoints
AWS Greengrass
AWS IoT 1-Click
AWS IoT
Analytics
Amazon
FreeRTOS
Storage & Compute & Learn
Cloud
Secure local
triggers, actions,
and data sync
Intelligence
Insights & Logic → Action
AWS IoT Services Suite
24. Easily Trigger Actions in the Cloud
AWS IoT 1-Click
AWS IoT 1-Click makes it easy for simple devices to
trigger actions such as Lambda functions with one click
Acquire device Configure & deploy Extract reports
31. Problem
Nokia saw a need in industrial IoT to analyze
video streams at the edge and send the data
to remote centers only when anomalies are
detected.
Solution
Deploying AWS Greengrass on Nokia Multi-
access Edge Computing platform and
combining it with Nokia private mobile
network solutions. This joint solution makes
it possible for the oil industry to pair real-
time drilling data with production data
of nearby wells.
Impact
Due to the high cost of bandwidth being, this
solution enables Nokia to optimize the data
that is sent to other wells and to the cloud
based on rules and alerts set up on
the locally processed data.
32. Problem
Valmet produces complex equipment with
multiple dependent processes running in parallel.
Valmet customers need visibility into the state of
these processes to control quality and avoid
downtime.
Solution
Valmet is building a new digital twin capability to
allow paper mill operators to view equipment
and process data during production runs. AWS
IoT Analytics is at the core of this solution
training ML models for paper quality forecasting
and scheduling metrics generation for digital
twin view-generation.
Impact
AWS IoT Analytics allows Valmet to combine
historical models of equipment performance
with live data from current operations to glean
insights that help them learn how to make their
paper better and stronger.
33. Problem
Wärtsilä needed to accurately predict when the
marine engines they manufactured needed to
get serviced. Understanding and predicting the
service schedule is vital for Wärtsilä to increase
their service and parts revenue.
Solution
Accenture worked with AWS account SAs, AoD
SAs, and Salesforce SAs to architect an IoT
solution using Salesforce and AWS IoT Core to
collect data and build predictive models. The
solution they developed is scalable and
extensible beyond just this use case, as Wärtsilä
has 14,000 ships with 35,000 engines installed.
There are great possibilities for sensor-driven IoT
use cases.
Impact
The entire solution should result in an increase
in parts and service sales for Wärtsilä and higher
customer retention.
34. Problem
With the launch of the new X8 architecture,
the first of his kind to be connected, Kemppi
was looking at a platform that could provide
development agility and cost reduction
Solution
Kemppi chose AWS not least because of
maturity of the services such as AWS
Lambda. Adopting AWS IoT reduced the
requirement on the devices and provides a
reliable communication channel to the rest
of the platform, even from remote places
such as oil rigs.
Impact
Adopting AWS, Kemppi reduced the product
release cycle from one year to six months,
and at the same time reduced the planned
downtime. AWS IoT and other managed
services allows them to spend less time on
managing infrastructure, reducing the cost of
deliveries.
35. Problem
Rio Tinto has connectivity challenges at some
of the mine locations where large, expensive
machinery is in play. Rio was looking for a
way to still leverage the cloud to predict and
prevent equipment failures, wear and tear,
and learn about potential hazards in their
surrounding environment.
Solution
Rio is using AWS Greengrass to run locally
and collect data from its fleet of large
hauling trucks. The data is collected from
sensors on haul trucks and stored for on-site
analysis to calculate road roughness.
An online heat map of the rough roads helps
maintenance crews repair roads and reduce
premature damage of their machinery.
Impact
Greengrass allows for real-time alerts and
machine-to-machine communication even
when not connected to the cloud. Operating
locally has helped Rio manage its fleet of
trucks saving millions of dollars.