Speaker: Tim Cruse, Specialist Solutions Architect - IoT, APAC, AWS Customer Speakers: Andreas Ruland, CTO, smove Gary Han, GM Product Marketing, Murata Machine learning enables fantastic business opportunities. Whether through implementing smarter data driven decision making or more precise recommendations. In many cases, machine learning needs to leave the cloud and be applied closer to the end customer, closer to the data being generated. In this session, we will cover how AWS IoT suite of services enables bridging that gap between cloud and edge. We will show how AWS IoT technology enable machine learning at the edge in a scalable manner, and how customers are leveraging AWS IoT to bring their business solutions to life.

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ML in the physical world with IoT
Timothée Cruse
APAC IoT Specialist SA
AWS
Andreas Ruland
CTO
smove
Gary Han
General Manager
Product Marketing
ASEAN, India, Oceania
Murata

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1951
Telecaster
1951
Precision
bass
1954
Stratocaster

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Wood matching–Quality assurance

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Wood matching

6. If you knew the state of every thing and could
reason on top of that data…
what problems would you solve?

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Device fleet
maintenance
Energy efficiency
monitoring
Safeguard
manufacturing facilities
Payment, insurance and
connected commerce
Predictive
maintenance
Wellness and
health solutions
Connected buildings
and city systems
Productivity and
process optimization
What customers are doing with AWS IoT

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AWS IoT customers solve problems in all sectors

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Revenue growth
IoT data drives business growth
Operational efficiency
IoT data decreases OpEx
New services &
business models
Products that get better
with time
Better relationship
with customers
Increased
efficiency
Intelligent decision
making
Data driven
discipline
Business outcomes with IoT

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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

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IoT virtuous cycle

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AWS IoT Events
IoT virtuous cycle
AWS IoT Analytics
AWS IoT SiteWise
AWS IoT Device
Management
AWS IoT
Things Graph
AWS IoT Core
AWS IoT
Device Defender
AWS IoT
Device SDK
Amazon FreeRTOS
AWS IoT
Device Tester
AWS IoT
Greengrass

14. Smove Singapore
www.smove.sg
AWS IoT at Smove
Andy Ruland, CTO
Smove Systems

15. Smove Singapore
www.smove.sg
First in Asia to provide A
to B car sharing trips
Drive for Grab
(Private Hire Vehicle)
either part-time or
full time
Personal use for
meetings, after work
trips, errands or longer
term rentals

16. Smove Singapore
www.smove.sg
Four rental options
from 15 minutes to
15 months & beyond
Fleet size of over
400+ in 5 different
vehicle categories
Over 15,000
bookings per month
with a user base of
96,000+ users
110+ pick up/drop
off locations
islandwide

17. Smove Singapore
www.smove.sg
AWS IoT at Smove
Device Shadow
Status Config Cmd
Rules
ForwardStatuses
Desired
config /
command
Reported
status /
config /
command
Desired
status /
config /
command
MQTT
Back-End

18. Smove Singapore
www.smove.sg
AWS IoT at Smove

19. Smove Singapore
www.smove.sg
Greengrass
IoT
Kinesis
Machine
Learning
The Future of
AWS IoT at
Smove

20. Smove Singapore
www.smove.sg
Machine Learning at Smove
● Event Detection
● Driver Profiling
● CV on Images/Videos
● Vehicle health
● Rekognition - License Validation
● ...

21. Smove Singapore
www.smove.sg

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What happens when
you combine AI and
IoT?

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–

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The Edge…….

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“AIoT” (AI and IoT) — ML at the Edge
Train in the cloud, infer at the edge
Amazon SageMaker
AWS IoT
Greengrass
Amazon
FreeRTOS
AWS IoT Core
AWS IoT Analytics

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How can I
extend AWS
cloud capabilities
to the edge with ML
capabilities?

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IoT virtuous cycle
AWS IoT
Device SDK
Amazon FreeRTOS
AWS IoT
Device Tester
AWS IoT
Greengrass

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Edge Cloud
Law of Economics
Law of Physics
Law of the Land
AWS IoT Greengrass
AWS IoT Greengrass extends AWS IoT onto your devices, so that they can act
locally on the data they generate, while still taking advantage of the cloud.

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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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Fender’s Wood matching architecture
AWS Cloud
Lambda
Factory
Camera
Workers
Dashboard
Raspberry Pi
Lambda
Lambda

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AWS IoT Events
IoT virtuous cycle
AWS IoT Analytics
AWS IoT SiteWise

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From raw
sensor data to
sophisticated
IoT analytics
How can I analyze and make sense of IoT data?

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Collect AnalyzeProcess Store Visualize
AWS IoT Analytics
AWS IoT Analytics is a service that processes, enriches, stores, analyzes,
and visualizes IoT data for manufacturers and enterprises.
Collect only the data
you want to store &
analyze
Convert raw data to
meaningful
information
Store device data in
time-series data
store for analysis
Get deeper insight
into the health &
performance of assets
Quickly visualize
your IoT data sets

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AWS IoT Events
IoT virtuous cycle
AWS IoT Analytics
AWS IoT SiteWise
AWS IoT Device
Management
AWS IoT
Things Graph
AWS IoT Core
AWS IoT
Device Defender
AWS IoT
Device SDK
Amazon FreeRTOS
AWS IoT
Device Tester
AWS IoT
Greengrass

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MOTOR HEALTH MONITORING
101

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• Capacitors
• Inductors (Coils)
• Noise / EMI Suppression Products and Filters
• Ultra Low Power Short Range RF-IC
• Resistors
• Thermistors
• Sensors
• Timing Devices
• Sound Components
• Power Devices
• Micromechatronics
• RFID
• Matching Devices
• RF Components
• RF Modules
• Batteries
• Filters
• Substrates
• Ionizers/ Ozonizers
• Front-end Modules

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A total of 43
manufacturing
facilities
around the
world *as of 31 March 2018
No. of Employees:
Americas
United States
Brazil
Canada
Mexico
EMEA
The Netherlands
Finland
France
Germany
Hungary
Italy
Spain
Switzerland
United Kingdom
Asean and India
Singapore
India Malaysia
Philippines Thailand
Vietnam
Greater China
Japan
Korea

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HUGE FINANCIAL LOSS!
- Estimated loss: USD 100K/ day per production line
CRITICAL PROCESS BREAKDOWN!
- Unexpected motor failure
LONG DOWNTIME!
- Production line stopped for days
S U M M I T

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Murata
Vibration
Sensor NodeEase of
Implementation
and Installation
§ Easy to Start
§ Easy to Use
§ Easy to Expand

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How AWS helps us make it “easy”?
AWS Lambda
AWS S3
ML Models
AWS SNS
AWS Greengrass
AWS QuickSight
Local Lambda
and models
Murata: Machine’s stethoscope
AWS: Machine’s doctor

42. Sensor Nodes
MACHINE
User Interface (UI)
END CUSTOMER
Cloud
Back End
ML Model Insights
ML Model Development
Cloud Front End
Data Collection
Pre-Processing

43. Delivered by Murata
Facilitated by AWS & Murata
Value for Customer: Specific Solution addressing to exact customer requirements & Customized Solution
Customer
Internal SW Teams
(IP owned by Customer)
Option 2
Customer
engaged SIer
(IP owned by Sier)
Option 3
PHASE1
• Murata introduces SIer
• AWS introduces SIer (*many options)
• AWS Professional Services
(IP owned by Developing Party)
Option 1
• Murata introduces ML partner
• AWS introduces ML partner
(*many options)
• AWS Professional Services
(IP owned by Developing Party)
MOVING AHEAD …
Sensor
Nodes
Dataset
Collection
ML Model
Insights
ML Model
Development
Cloud
Front End
Pre-
Processing
Cloud
Back End
PHASE2

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AWS
Solutions
to Start
to Use
to Expand

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Now that you know the state of
every thing, and can reason on
top of that data, what problems
would you solve?
aws.amazon.com/IoT

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Thank you!
S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Timothée Cruse
tcruse@amazon.com