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IoT Edge

Presented byMadhuri PeriBuilder and IoT Edge practice leaderAWS Professional services

AWS IoT customers solve problems in all sectors

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Device fleet maintenance

Energy efficiency monitoring

Safeguard manufacturing facilities

Payment, insurance and connected commerce

Predictive maintenance

Wellness andhealth solutions

Connected buildings and city systems

Productivity and process optimization

What customers are doing with AWS IoT

Connect, communicate,

secure

Onboard,

provision, manage

Devices & sensors

Connectivity & infrastructure

Analyze,

visualize, act

Analytics & insights

Engage, empower,

delight

Applications & services

Transform, shift culture

Change management

IoT solutions are complex & multidimensional

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AWS IoT architecture

IoT virtuous cycle

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Why Edge

• Laws of Physics• Network connectivity

• Latency

• Laws of regulation• Data privacy

• Government entities

• Laws of Economics• Transmission / bandwidth costs

• Data volume

How can I extend AWS cloud capabilities to the edge?

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?

How can I securely connect constrained, microcontroller-based devices?

Will it work on my chip? Does it have the

functionality I need?How do I start?Where do I get it?

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Amazon FreeRTOS is a microcontroller operating system that makes small, low

powered edge devices easy to program, deploy, secure, connect, and maintain.

Amazon FreeRTOS

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Will it work on my chip? Does it have the

functionality I need?

How do I start?Where do I get it?

EMBEDDED APPS

FreeRTOS

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Amazon FreeRTOS is a microcontroller operating system that extends the popular FreeRTOS kernel to

enable devices to securely connect to AWS, while making them easy to manage, deploy, and update.

Amazon FreeRTOS

Local Connectivity Libraries

Cloud Connectivity Libraries

Security ConnectivityLibraries

OTA &Code Signing

Amazon FreeRTOS

Communicate with AWS IoT

Greengrass devices without

a cloud connection

Easily collect data and take

actions on microcontroller-

based devices

Secure device data and

connectionsDeploy security updates, bug

fixes, and firmware updates to

devices in the field

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Data and State Sync Security

Over the Air UpdatesConnectors

Operate devices offline & synchronize data

when reconnected

LocalActions

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

LocalMessages

and Triggers

Enable device communication without a cloud

connection

Secrets Manager

Deploy secrets to edge devices

AWS IoT Greengrass

AWS Greengrass – Group Concept

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Sagemaker NEO

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How can I liberate data that was once locked in industrial facilities?

Structure your data and specify performance metrics for your assets

and processes

Easily browse equipment and process data, build data views to identify inefficiencies,

diagnose issues, and improve cross-facility processes

AWS IoT SiteWise collects data from the plant floor with a local gateway, structures & labels that data, and generates real time KPIs & metrics to make better data-driven decisions.

See your data flowing in minutes without writing code, just connect and configure

your gateway

AWS IoT SiteWise

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Customizable

Views

Data Management and Modeling Tools

Remotely ManageableEdge Gateway

Access data from

local databases on

the factory floor

Collect data

consistently from

different sources

Visually identify

equipment or process

issues

AWS IoT SiteWise

Recent Feature Launches

• Amazon FreeRTOS 201906.00 Major• BLE GA , AWS IoT Device Tester integration

• OpenWRT support for ARMV7l and ARMV8 architectures

• Device IoT device management• Connectivity indexing, lifecycle events

• Dynamic Thing Groups

• IoT Device defender • Auditing at scale, audit device configurations, monitor device defender,

generate alerts, investigate and mitigate security issues

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Problem

Nokia desired to analyze video streams at the edge and send data to remote centers only when anomalies are detected.

Solution

The solution is the deployment of 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 cost of bandwidth, this allows Nokia to optimize data sent to other wells and to the cloud based on rules and alerts set up on the locally-processed data.

Problem

Enel was looking to manage network distribution at the edge. They were seeking to collect sensor and meter data over 500,000 cabins distributed across the territory to measure energy consumption, monitor network behavior in real time, and track effects of seismic waves and earthquakes.

Solution

Enel implemented AWS Greengrass to collect, convey, and process the largest amount of data to trigger actions, govern activities, respond to anomalies, and promote new services.

ImpactThe project is the widest so far in Europe and provides Enel an opportunity to leverage data to design a better future.

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Modjoul is a data invention company for wearable technology that is focused on keeping employees safe. Modjoul is using AWS IoT Analytics to help keep industrial workers safe, whether they’re working in or out of a vehicle. In an eight-hour shift, they collect data 28,800 times per day from their connected activity tracker worn by each of their employees that includes 40 metrics including heart rate and activity level. With AWS IoT Analytics, they not only analyze all that health data, but also enrich it with location and environmental data, such as outdoor temperature, to get accurate analytics that prevent injuries and save lives.

Problem

Healthcare poses a number of challenges when connecting devices including patient privacy, industry standards and protocols, and the management of personal and population data.

Solution

The Philips HealthSuite digital platform (HSDP) is built to face the challenges of connecting and supporting healthcare devices. HSDP Connect Services leverage AWS IoT services to manage, update, & remotely monitor data from smart devices.

Impact

HSDP Connect Services currently enable over 11 million device connectivity solutions. By using AWS IoT services, HSDP Connect is reducing connectivity costs by 46%.

Problem

Pentair provides water filtration systems equipped with sensors to fish farms and large industrial brewing customers. Most of their industrial customers are located in geographies with unreliable internet connectivity. They need to send data from sensors and devices to the cloud while continuously maintaining connection which is challenging in remote areas.

Solution

From Pentair’s water filtration systems, data is sent to AWS IoT Core. When connectivity is limited, AWS Greengrassprovides Pentair with a local connection so data is never lost.

Impact

Pentair can make decisions in near real-time that impact the health of its devices but also the health of the fish which in turn, results in better yields, prevents the spread of disease and lowers cost of operations.

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Problem

Stanley Black and Decker finds it unsustainable to ingest, transmit, store, query and analyze all data generated at the edge and more specifically on construction sites or rural areas with constrained network resources.

Solution

AWS Greengrass enables Stanley Black and Decker to monitor and filter data at the edge of the network enabling applications to send asset health and predict any mechanical failures before they occur. Edge-based applications built on Greengrass will help detect and compare vibrations emitted by high value tools to historical signatures that indicate everything from normal operations to imminent failure.

Impact

Instead of trying to use all the data Stanley Black and Decker will utilize Greengrass to focus on the right data. Applications include remote troubleshooting of hydraulic assets by technicians, maintenance interval tracking, fuel savings, and alerts.

Problem

Recife needed to improve its urban cleaning program by monitoring 26 cleaning services. it required thousands of vehicles and employees and consumed close to 10 percent of the city’s operating budget.

Solution

Recife implemented RasSystem's RasCol solution to track cleaning operations.

Impact

Enables greater efficiency in urban cleaning

Improved cleaning service reliability by 15%

Reduced monthly cleaning costs by $250,000

Recife models being a smart city

Can focus on operational improvements

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Thank you!