This document discusses connecting devices in motion to the cloud. It outlines some of the challenges with devices in motion like constrained resources, unreliable connections, and location data. It then describes how AWS IoT can help address these challenges through its scalable MQTT broker, device shadowing capability, security features, and integration with services like DynamoDB, RDS, and Elasticsearch that support geospatial queries and mapping. The presentation concludes with a demo of how these techniques could be applied to a connected car safety application.

1. © 2015, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Constantin Gonzalez, Jan Metzner, Ricardo DeMatos, AWS
Danny Williams, Mark Sparks, Monsanto
October 2015
From Drones to Cars
Connecting the Devices in Motion to the Cloud
MBL203

2. What to Expect from the Session
• Understand the challenges
• Architecture building blocks
• Architecture patterns
• Examples
• Demos
• Practical experience and guidelines

3. IoT in Motion at Monsanto
Danny Williams, @djwilli3
Mark Sparks, @markdsparks Monsanto IoT, @MonsantoIoT

4. IoT creates new opportunities in
precision agriculture
4
Plan
Experiment
Plant
Monitor/applyHarvest
Analyze

5. Monsanto tests products all around
the world
5
Data needs to be reliably gathered from various equipment in
remote locations where data connectivity is unreliable
Plan
Plant
MonitorHarvest
Analyze
Plan
Plant
MonitorHarvest
Analyze
Plan
Plant
MonitorHarvest
Analyze
Plan
Plant
MonitorHarvest
Analyze
Plan
Plant
MonitorHarvest
Analyze

6. The formula for reliable data transfer
and processing
6
Store and
forward on
edge
Low overhead
communication
protocol
Broker-based
processing in
cloud

7. Data ingestion and storage
Analytics Cloud code
Communication
Rest API Visualizations
HTTP

8. Demo
FIELDDRIVE

9. 9

10. Devices in motion

11. Devices in motion carry a lot of value
• Automated harvesting
• Automated transport
• Connected cars and vehicles
• Aviation
• Sports, gaming, leisure
• Medical and public service
• Tourism

12. Technical characteristics
• Mobile networks: kBit/s
• Lightweight:
Every gram, every watt counts
Low RAM, low CPU, low power
• Near real-time: Seconds count
• Location-based
• Large-impact use cases

13. Dash streams more than 1 TB of real-time data per day
Dash connects your smartphone to your car with a
simple, low-cost device which provides real-time road
safety information to drivers.
As a startup, using AWS has
allowed us to scale nicely and use
resources without spending a lot
of capital.
Brian Langel
CTO, Dash
”
“ • Real-time information for drivers
• Streams more than 1 TB of real-time
data per day over Amazon Kinesis
• Processes billions records using
Amazon DynamoDB
• Thousands of updates per second
during spikes
• Reduced operating costs by
$200,000 per year

14. Devices in motion: Challenges
• How to handle constrained resources?
• How to manage millions of things?
• How to communicate securely?
• How to deal with unreliable connections?
• How to handle geo-location?
• How to deal with map data?
?

15. Devices in motion: Challenges
• How to handle constrained resources?
• How to manage millions of things?
• How to communicate securely?
• How to deal with unreliable connections?
• How to handle Geo-Location?
• How to deal with map data?
?

16. MQTT
MQTT vs HTTPS:
• 93x faster throughput
• 11.89x less battery to send
• 170.9x less battery to receive
• 50% less power to keep connected
• 8x less network overhead
Source:
http://stephendnicholas.com/archives/1217
• OASIS standard protocol (v3.1.1)
• Lightweight, pub-sub, transport protocol
that is useful for connected devices
• MQTT is used on oil rigs, connected
trucks, and many more sensitive and
resource-sensitive scenarios
• Customers have needed to build,
maintain, and scale a broker to use
MQTT with cloud applications

17. Devices in motion: Challenges
• How to handle constrained resources?
• How to manage millions of things?
• How to communicate securely?
• How to deal with unreliable connections?
• How to handle Geo-Location?
• How to deal with map data?
?
✔

18. Highly scalable
Pub/Sub broker
MQTT
Subscribers
Publishers
Secure by default
Connect securely via X509 certs and
TLS v1.2 client mutual auth
Multi-protocol message gateway
Millions of devices and apps can connect
over MQTT or HTTP
topic
Elastic Pub/Sub broker
Go from 1 to 1 billion long-lived, bi-directional
connections with zero provisioning
AWS IoT: Securely connect devices

19. Devices
Apps
Secure
Pub/Sub
broker
AWS IoT Pub/Sub broker

20. 1. AWS services
(direct integration)
Rules Engine
Actions
AWS IoT Rules Engine
LambdaSNS SQS
S3 Amazon KinesisDDB RDS
Amazon Redshift
Amazon
Glacier
EC2
3. External endpoints
(via Lambda and SNS)
Rules Engine connects AWS
IoT to external endpoints and
AWS services.
2. Rest of AWS
(via Amazon Kinesis, Lambda,
S3, and more)

21. Devices in motion: Challenges
• How to handle constrained resources?
• How to manage millions of things?
• How to communicate securely?
• How to deal with unreliable connections?
• How to handle Geo-Location?
• How to deal with map data?
?
✔
✔

22. AWS IoT security
Authentication Authorization
MQTT/HTTP over TLS v1.2
(X.509 certs) cipher suites
TLS mutual auth:
(Client/server certificates for things)
HTTPS over sigv4 (for apps)
Amazon Cognito/IAM (for mobile apps)
Certificates are attached to policies
Policies (JSON) give granular access
to AWS IoT control and data plane
Policies allow and deny permissions on
specific resources
(rules, shadows, topics)

23. Devices
Apps
Secure
Pub/Sub
broker
AWS IoT Pub/Sub broker
MQTT/TLS
MQTT/TLS

24. Devices in motion: Challenges
• How to handle constrained resources?
• How to manage millions of things?
• How to communicate securely?
• How to deal with unreliable connections?
• How to handle Geo-Location?
• How to deal with map data?
?
✔
✔
✔

25. AppsShadow
Secure
Pub/Sub
broker
Thing SDK
AWS IoT Device Shadows

26. AWS IoT Device Shadows flow
Shadow
Thing
SDK
1. Device publishes current state
2. Persist JSON data store
3. App requests device’s current state
4. App requests change the state
5. Device Shadow syncs
updated state
6. Device publishes current state
7. Device Shadow confirms state change

27. Devices in motion: Challenges
• How to handle constrained resources?
• How to manage millions of things?
• How to communicate securely?
• How to deal with unreliable connections?
• How to handle geo-location?
• How to deal with map data?
?
✔
✔
✔
✔

28. Geo-location and mapping use cases
• Tracking
• Geo-fencing
• Find nearby objects
• Alert nearby things
• Map matching
• Routing

29. Geohashing
• Easy to compute
• Arbitrary precision
• Similar positions yield
similar prefixes
• Removing characters reduces
precision
• Simple way to look up and manage
geo objects
Picture: https://github.com/stephenlb/geohash-chat-by-proximity

30. Distribute messages to geo-located things with
topic tiles
• One topic per geohash
• Things subscribe to their
current geohash tile’s topic
as they move
• Send messages to tile topics
• Use geohash lengths to
change area impact of
message

31. Geo library for Amazon DynamoDB
• Ready-to-use Java JAR
• Library and sample apps
available on GitHub
• Supports GeoJSON
• Uses geohashes for
DynamoDB local
secondary indexes
• Simplifies box and radius
queries

32. AWS IoT Service and DynamoDB with
Geohashing Architecture
Rules Engine
Send
lat/lon AWS Lambda +
Geo library for
Amazon DynamoDB
Look up
geohash
Moving
thing
Amazon
DynamoDB
Return
matches
1 2
34
5

33. Amazon RDS for PostgreSQL with PostGIS
• Powerful support for:
• Geo data formats
• Geometric projections
• Transform operations
• Query functions
• Well understood, easy
to use
• Supported on Amazon
RDS for PostgreSQL

34. AWS IoT and Amazon RDS for PostgreSQL
Rules Engine
Send
lat/lon AWS Lambda
Geo-
queries
Moving
thing
Amazon RDS
for PostgreSQL
Return
matches
1 2
34
5

35. Processing map graphs with TitanDB
• Scalable graph database
• Import maps as graphs
• Supports routing and
other complex map
queries
• Amazon DynamoDB
storage back end for
TitanDB available

36. AWS IoT and
Amazon DynamoDB for TitanDB
Rules Engine
Send
lat/lon AWS Lambda
Map
queries
Moving
thing
Amazon
DynamoDB
Return
matches
1 2
34
5
TitanDB +
Amazon DynamoDB
back end

37. Amazon Elasticsearch Service
• Powerful, real-time, distributed, open-source
• Supports geolocation searches:
• Geo-points, geohashes, geo-aggregations, geoshapes
Amazon Elasticsearch Service
• Managed service
• Easy to set up, scale, operate

38. AWS IoT and Amazon Elasticsearch Service
architecture
Rules Engine
Send
lat/lon AWS Lambda
Run
queries
Moving
thing
Amazon
Elasticsearch
Service
Return
matches
1 2
34
5

39. Devices in motion: Challenges
• How to handle constrained resources?
• How to manage millions of things?
• How to communicate securely?
• How to deal with unreliable connections?
• How to handle geo-location?
• How to deal with map data?
✔
✔
✔
✔
✔
✔

40. Summary
• Use AWS IoT to manage and communicate with your
things
• Scalable, easy to use MQTT pub/sub message broker
• Powerful AWS IoT Rules Engine
• Use AWS IoT Device Shadows for unreliable connections
• Take advantage of AWS Lambda to connect to geo-aware
services:
• Amazon DynamoDB with geohash and/or TitanDB support
• Amazon RDS for PostgreSQL with PostGIS
• Amazon Elasticsearch Service

41. Demo: Connected car safety
Ricardo DeMatos, AWS

42. http://www.iteris.com/cvria/html/applications/app74.html#tab-3

43. https://github.com/smartdevicelink

44. OBE
Vehicle
RSE
Notification
function
DMS
Vehicle
GIS
Rules engineRules engine
Notification
topic
Traffic information center
Partner notification
Shadow
Reported
state
Reported
state
Desired
state
Environment
situation
stream
Traffic incident
service
OBE
Prediction API
Reported
state
Desired
state
Desired
state

45. Don’t Miss These Other AWS IoT Deep Dive Talks!
• MBL203 State of the Union – San Polo 3501B 11:00 AM
• MBL203 Everything about AWS IoT – Venetian H 12:15 PM
• MBL311 AWS IoT Security – Palazzo A 1:30 PM
• MBL312 Rules and Shadow – Palazzo A 2:45 PM
• MBL313 Devices SDK and Kits – Palazzo A 4:15 PM
• MBL303 Mobile Devices and IoT – Delfino 4005 4:15 PM
• MBL305 IoT Data and Analytics – Delfino 4005 11:30 AM

46. Remember to complete
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47. Thank you!