In this presentation I do a review of the architecture of an AI application for IoT environments. Since specific modeling and training aspects also have an impact on the final implementation of an enterprise ready solution, such solutions become very complex pretty soon. The complexity of AI system for IoT is a big challenge – thus, I want to break this complexity down into particular views, which emphasize the individual but still interconnected aspects more clearly.

1. IoT meets AI in the Clouds
Dr. Mirko Kämpf | Sr. Solution Architect | CEMEA team

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AGENDA
• Introduction: What drives IoT and Cloud AI?
• Classification of Systems
• What is an IoT Solution (incl. AI)?
• How do we do IoT?
• What are others doing?
• Generalization
• Functional decomposition
• Dataflows and Processes
• Roles and Team-Setup
• How to go to Market?

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INTRODUCTION: WHAT DRIVES IOT AND CLOUD AI?

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DRIVERS FOR AUTOMATIC DECISIONS:
Available information is source for learning and triggers decisions / responses.
Event or Message Driven
People and systems communicate
with each other.
Data Driven
Existing data has huge impact on
functionality, e.g. because models or
Unknown structures can be derived
from data .
Amazon Dash Button
Source: https://techcrunch.com/2018/05/14/aws-introduces-1-click-lambda-functions-app-for-iot/?guccounter=1

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CONSUMER MARKET: COOL APPS

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INDUSTRY AUTOMATION SOLUTIONS: ENTERPRISE IT

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WHY DO WE CARE ABOUT AI?
Cloudera offers expertise / components / platform for automated decisions.
• Big Data
• Variety of data types
• Evolving schemas
• Cloud based and Hybrid
systems
Automation @ Scale:
Highly interconnected
systems
like:
autonomous cars
within smart cities
using smart energy.
• Machine Learning
• World class tools:
- for learning
- deployment
• Support on top hardware:
- GPU
- Customized processors
Where we come from
...
Where we try to be ... The Future ...

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CLASSIFICATION OF IT SYSTESMS / PRODUCTS:
From the shelf DIY
Customizable, open, flexible solutions
Open SourceClosed Source
Enterprise ready: secure, robust, adaptive

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MATURITY LEVELS:
Yust another way to classify systems ...
• Funtionality matters!
• PoC
• Working Tool
• Enterprise Context is cruicial ...
• Secure
• Robust/maintainable
• @Scale – because the business needs growth
• Massive data
• Huge # of users / devices
• Dynamic requirements due to unknown growth direction and speed

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HOW CAN THIS BE DONE?

13. Sensors,
Actuators, Data
Sources
Advanced Analytics &
Machine Learning
Cloud IoT Platform
Edge Processing &
Analytics
Enterprise IT
& Apps
Telemetry Data
IOT
Gateways
Centralized Data Platform
IOT
Integration Hub
Real-Time
Analytics
Data Ingest
Real-Time
Processing
Data
Storage
Machine
Learning
Data
Security
App Data
Enterprise ApplicationsConnected
“Things”
Management
App
Integration
Telemetry
Data
Integrating IOT Operating Technology, Data Management, Analytics, and Applications
Open End-to-End IoTArchitecture
(CDH)

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AWS:
A variety of IoT offerings ...
• Process & act upon device data
• Connect and manage device data
• Secure device connections and data
• Read and set device state

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GENERALIZATION

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SIMPLIFICATION: LOOK @ ONE FACET AT A TIME ...

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DATA ASSETS AND PROCESSES (WHICH NEED TO SCALE OUT)

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MULTIDISCIPLINARY APPROACH IS KEY TO SUCCESS:

20. Sensors,
Actuators, Data
Sources
Advanced Analytics &
Machine Learning
Cloud IoT Platform
Edge Processing &
Analytics
Enterprise IT
& Apps
IOT
Gateways
CDH /Altus: Data Platform
IOT
Integration Hub
Real-Time
Analytics
Data Ingest
Real-Time
Processing
Data
Storage
Machine
Learning
Data
Security
CDSW: ML & AI ApplicationsConnected
“Things”
Integrating IOT Operating Technology, Data Management, Machine Learning & AI-Applications
Finally: IoT meets AI in the Clouds ....
(CDH)

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WHY USING CLOUDERA OPEN SOURCE IOT ARCHITECTURE?
• Works on premise & in the clouds!
• Open source device management
(powered by Eclipse Foundation)
• Open source ML and AI platform for the cloud
(powered by ASF components)

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CLOUDERA OFFERINGS ARE NOT LIMITED
TO ONE SPECIFIC IOT PLATFORM ...

23. Sensors,
Actuators, Data
Sources
Advanced Analytics &
Machine Learning
Cloud IoT Platform
Edge Processing &
Analytics
Enterprise IT
& Apps
IOT
Gateways
CDH /Altus: Data Platform
IOT
Integration Hub
Real-Time
Analytics
Data Ingest
Real-Time
Processing
Data
Storage
Machine
Learning
Data
Security
CDSW: ML & AI ApplicationsConnected
“Things”
Integrating IOT Operating Technology, Data Management, Machine Learning & AI-Applications
Cloudera ML meets Google IoT in the Cloud ....
(CDH)

24. Sensors,
Actuators, Data
Sources
Advanced Analytics &
Machine Learning
Cloud IoT Platform
Edge Processing &
Analytics
Enterprise IT
& Apps
IOT
Gateways
CDH /Altus: Data Platform
IOT
Integration Hub
Real-Time
Analytics
Data Ingest
Real-Time
Processing
Data
Storage
Machine
Learning
Data
Security
CDSW: ML & AI ApplicationsConnected
“Things”
Integrating IOT Operating Technology, Data Management, Machine Learning & AI-Applications
Cloudera ML meets AWS IoT in the Cloud ....
(CDH)

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HOW AND WHAT DO WE FINALLY DELIVER?
Partners offer “from the
shelf solutions” to end
users.
Open Source
Community
Cloudera:
Open End-2-end
IoT Architecture
We continue to
contribute to a
sustainable open
source culture.
Enterprise ready: secure, robust, adaptive
We serve our customers &
partners and enable them
to deliver high quality ML
enabled IoT solutions.
We deliver top class systems by
integrating the relevant components
for the enterprise.