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IoT & Azure
the field of possibilities
Alex Danvy @danvy
History
Administration
-> sensor data
<- commands
<- configuration
Clients : Dash board,
Remote control
Objects : Sensors, UX,
Communication
Servers : Store data,
Configuration, Business logic,
Business Intelligence
System Center
Windows Embedded
Windows
Windows Server, SQL
Server,
Office 365
Administration
-> sensor data
<- commands
<- configuration
Clients : Dash board,
Remote control, Gateway
Objects : Sensors, UX,
Communication
Servers : Store data, Configuration,
Business logic, Business
Intelligence, Privacy
System Center
Windows Embedded,
Netduino, Quark
Windows, Windows
Phone, XBOX, wearable
Private Cloud
Public Cloud
Public Cloud :
Store data (BigData), Configuration, Business logic,
Business Intelligence, Machine learning
Windows Server, SQL Server,
Office 365, Azure, HD
Insight/Hadoop, ML, ISS
Why the cloud?
On Premises
Youscale,makeresilientandmanage
Infrastructure
(as a Service)
Managedbyvendor
Youscale,make
resilient&manage
Platform
(as a Service)
Scale,resilienceand
managementbyvendor
Youmanage
Hosting models
Software
(as a Service)
Business model
Applications
Scale,resilienceand
managementbyvendor
Why the cloud?
Why the
cloud?
 Rapidly setup environments to drive business priorities
 Scale to meet peak demands
 Increase daily activities, efficiency and reduced cost.
Azure
The Azure Cloud Platform
HybridEnterprise
Grade
Hyper-scale
AZURE REGIONS
More than AWS and
Google Cloud combined
4 more announced
34
Azure regions
available today
>120,000
New Azure customer
subscriptions/month
5Trillion
Messages per week
processed by Azure IoT
>9Million
Organizations in
Azure Active Directory
> 5Million
Developers registered with Visual
Studio Team Services
>110Billion
SQL Databases
requests/day
>40%
Revenue from
Start-ups and ISVs
Azure momentum
Compliance: aka.ms/AzureCompliance
Partners
Platform Services
Security &
Management
Infrastructure Services
Web Apps
Mobile
Apps
API
Management
API
Apps
Logic
Apps
Notification
Hubs
Content Delivery
Network (CDN)
Media
Services
HDInsight Machine
Learning
Stream
Analytics
Data
Factory
Event
Hubs
Mobile
Engagement
Active
Directory
Multi-Factor
Authentication
Automation
Portal
Key Vault
Biztalk
Services
Hybrid
Connections
Service
Bus
Storage
Queues
Store /
Marketplace
Hybrid
Operations
Backup
StorSimple
Site
Recovery
Import/Export
SQL
Database
DocumentDB
Redis
Cache Search
Tables
SQL Data
Warehouse
Azure AD
Connect Health
AD Privileged
Identity
Management
Operational
Insights
Cloud
Services
Batch Remote App
Service
Fabric Visual Studio
Application
Insights
Azure SDK
Team Project
VM Image Gallery
& VM Depot
IoT & Azure, the field of possibilities
Azure IoT
Cloud
What’s in the Cloud ?
Events
Storage
Near
Real Time
DB
SQL/noSQL
Batch
Query,
Merge &
Machine
Learning
Storage, DB
Lambda Architecture
Cloud
Azure PAAS
Events
Storage
Near
Real Time
DB
SQL/noSQL
Batch
Query,
Merge &
Machine
Learning
Storage, DB
Web App
Event Hubs
IoT Hub
Stream
Analytics
Web Jobs
Blob, Table,
Queue
Azure SQL
PowerBI,
ML
Cloud
Events
Storage
Near
Real Time
DB / NoSQL
Batch
Query,
Merge &
Machine
Learning
Storage, DB
IaaS-Open Source Software
OPC
Publisher
Device
Connectivity & Management
Analytics &
Operationalized Insights
Presentation &
Business Connectivity
IndustrialDevices
(OPCandOPCUAServers)
Hot Path Analytics
Azure Stream Analytics, Azure Storm
Presentation & Business
Connections
Websites, Mobile Services
Dynamics, BizTalk Services,
Notification Hubs
Cloud Gateway
IoT Hub
OPC UA Integration into Azure IoT Suite
Field
Gateway
OPC API & Client
Hot Path Business Logic
Service Fabric & Actor Framework
Blockchain
Microsoft Innovation
from simple ledgers, to cryptlets that
fetch trusted and agreed-upon
external data needed to execute
Smart Contracts
IoT & Azure, the field of possibilities
What is Machine Learning?
Methods and Systems that …
Adapt
based on
recorded
data
Predict new
data based
on recorded
data
Optimize
an action
given a
utility
function
Extract
hidden
structure
from the
data
Summarize
data into
concise
descriptions
The United States Postal Service
processed over 150 billion pieces of
mail in 2013—far too much for
efficient human sorting.
But as recently as 1997, only 10% of
hand-addressed mail was
successfully sorted automatically.
The challenge in automation is
enabling computers to interpret
endless variation in handwriting.
By providing feedback, the Postal
Service was able to train computers
to accurately read human
handwriting.
Today, with the help of machine
learning, over 98% of all mail is
successfully processed by machines.
SQL Server
enables data
mining of
databases
Computers
work on users
behalf, filtering
junk email
Microsoft
Kinect can
watch users
gestures
Microsoft
launches Azure
Machine
Learning,
making years
of innovation
available
Microsoft
search engine
built with
machine
learning
Bing Maps
ships with ML
traffic-
prediction
service
Successful,
real-time,
speech-to-
speech
translation
Microsoft & Machine Learning
20 years of realizing innovation
John Platt,
Distinguished scientist at
Microsoft Research
1999 201220082004 201420102005
Machine learning is pervasive throughout
Microsoft products.“ ”
Azure Machine Learning
1. Pick & drop
models. No need to
write scripts.
2. Uploaded data tables
4. Pre-built
commands to
transform or
manipulate data
6. Evaluate models,
Visualize result or
export data
5. Specific settings to fine
tune the models
Easily turn data into intelligent action
Action
People
Automated
Systems
Apps
Web
Mobile
Bots
Intelligence
Dashboards &
Visualizations
Cortana
Bot
Framework
Cognitive
Services
Power BI
Information
Management
Event Hubs
Data Catalog
Data Factory
Machine Learning
and Analytics
HDInsight
(Hadoop and
Spark)
Stream Analytics
Intelligence
Data Lake
Analytics
Machine
Learning
Big Data Stores
SQL Data
Warehouse
Data Lake Store
Data
Sources
Apps
Sensors
and
devices
Data
Cognitive
Services
Give your solutions
a human side
IoT & Azure, the field of possibilities
www.botframework.com
IoT & Azure, the field of possibilities
IoT & Azure, the field of possibilities
Windows 10 IoT Enterprise
Desktop Shell, Win32 apps, Universal Windows Apps and Drivers
1 GB RAM, 16 GB Storage
X86
Windows 10 IoT Mobile Enterprise
Modern Shell, Universal Windows Apps and Drivers
512 MB RAM, 4 GB storage
ARM
Windows 10 IoT Core
No Shell, Universal Windows Apps and Drivers
256MB RAM, 2GB storage
X86 or ARM
Premium
Entry
$
Device Capabilities
Windows for Industry Devices
IoT & Azure, the field of possibilities
IoT & Azure, the field of possibilities
IoT & Azure, the field of possibilities
IoT & Azure, the field of possibilities
Consumer (client)
Producer (server)
HoloLens
Microsoft HoloLens Microsoft Confidential
Gaze
Gesture
Ink
Speech
Identity
Text
Holograms
Audio
Tangible
Emotional
input output
Virtual Reality
A computer’s simulated version of reality
Massive, immersive FOV
Occlusion limits mobility, usefulness
Gaming and focused uses
Augmented Reality
Data notifications tied to the real world
Lightweight, mobile
Overlays data, doesn’t integrate
Navigation, light communication
Holograms
Your real and digital worlds integrated, enhanced with holograms
Integrates your real and digital worlds seamlessly
Not constrained by size of 2D, rectangular displays
Intuitive, natural interactions
Digital content is wherever you need it
Complete Windows 10 computer
A new way to see your world
IoT & Azure
the field of possibilities
Alex Danvy @danvy

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IoT & Azure, the field of possibilities

  • 1. IoT & Azure the field of possibilities Alex Danvy @danvy
  • 3. Administration -> sensor data <- commands <- configuration Clients : Dash board, Remote control Objects : Sensors, UX, Communication Servers : Store data, Configuration, Business logic, Business Intelligence System Center Windows Embedded Windows Windows Server, SQL Server, Office 365
  • 4. Administration -> sensor data <- commands <- configuration Clients : Dash board, Remote control, Gateway Objects : Sensors, UX, Communication Servers : Store data, Configuration, Business logic, Business Intelligence, Privacy System Center Windows Embedded, Netduino, Quark Windows, Windows Phone, XBOX, wearable Private Cloud Public Cloud Public Cloud : Store data (BigData), Configuration, Business logic, Business Intelligence, Machine learning Windows Server, SQL Server, Office 365, Azure, HD Insight/Hadoop, ML, ISS
  • 6. On Premises Youscale,makeresilientandmanage Infrastructure (as a Service) Managedbyvendor Youscale,make resilient&manage Platform (as a Service) Scale,resilienceand managementbyvendor Youmanage Hosting models Software (as a Service) Business model Applications Scale,resilienceand managementbyvendor Why the cloud?
  • 7. Why the cloud?  Rapidly setup environments to drive business priorities  Scale to meet peak demands  Increase daily activities, efficiency and reduced cost.
  • 9. The Azure Cloud Platform HybridEnterprise Grade Hyper-scale
  • 10. AZURE REGIONS More than AWS and Google Cloud combined 4 more announced 34 Azure regions available today
  • 11. >120,000 New Azure customer subscriptions/month 5Trillion Messages per week processed by Azure IoT >9Million Organizations in Azure Active Directory > 5Million Developers registered with Visual Studio Team Services >110Billion SQL Databases requests/day >40% Revenue from Start-ups and ISVs Azure momentum
  • 14. Platform Services Security & Management Infrastructure Services Web Apps Mobile Apps API Management API Apps Logic Apps Notification Hubs Content Delivery Network (CDN) Media Services HDInsight Machine Learning Stream Analytics Data Factory Event Hubs Mobile Engagement Active Directory Multi-Factor Authentication Automation Portal Key Vault Biztalk Services Hybrid Connections Service Bus Storage Queues Store / Marketplace Hybrid Operations Backup StorSimple Site Recovery Import/Export SQL Database DocumentDB Redis Cache Search Tables SQL Data Warehouse Azure AD Connect Health AD Privileged Identity Management Operational Insights Cloud Services Batch Remote App Service Fabric Visual Studio Application Insights Azure SDK Team Project VM Image Gallery & VM Depot
  • 17. Cloud What’s in the Cloud ? Events Storage Near Real Time DB SQL/noSQL Batch Query, Merge & Machine Learning Storage, DB Lambda Architecture
  • 18. Cloud Azure PAAS Events Storage Near Real Time DB SQL/noSQL Batch Query, Merge & Machine Learning Storage, DB Web App Event Hubs IoT Hub Stream Analytics Web Jobs Blob, Table, Queue Azure SQL PowerBI, ML
  • 19. Cloud Events Storage Near Real Time DB / NoSQL Batch Query, Merge & Machine Learning Storage, DB IaaS-Open Source Software
  • 20. OPC Publisher Device Connectivity & Management Analytics & Operationalized Insights Presentation & Business Connectivity IndustrialDevices (OPCandOPCUAServers) Hot Path Analytics Azure Stream Analytics, Azure Storm Presentation & Business Connections Websites, Mobile Services Dynamics, BizTalk Services, Notification Hubs Cloud Gateway IoT Hub OPC UA Integration into Azure IoT Suite Field Gateway OPC API & Client Hot Path Business Logic Service Fabric & Actor Framework
  • 21. Blockchain Microsoft Innovation from simple ledgers, to cryptlets that fetch trusted and agreed-upon external data needed to execute Smart Contracts
  • 23. What is Machine Learning? Methods and Systems that … Adapt based on recorded data Predict new data based on recorded data Optimize an action given a utility function Extract hidden structure from the data Summarize data into concise descriptions
  • 24. The United States Postal Service processed over 150 billion pieces of mail in 2013—far too much for efficient human sorting. But as recently as 1997, only 10% of hand-addressed mail was successfully sorted automatically.
  • 25. The challenge in automation is enabling computers to interpret endless variation in handwriting.
  • 26. By providing feedback, the Postal Service was able to train computers to accurately read human handwriting. Today, with the help of machine learning, over 98% of all mail is successfully processed by machines.
  • 27. SQL Server enables data mining of databases Computers work on users behalf, filtering junk email Microsoft Kinect can watch users gestures Microsoft launches Azure Machine Learning, making years of innovation available Microsoft search engine built with machine learning Bing Maps ships with ML traffic- prediction service Successful, real-time, speech-to- speech translation Microsoft & Machine Learning 20 years of realizing innovation John Platt, Distinguished scientist at Microsoft Research 1999 201220082004 201420102005 Machine learning is pervasive throughout Microsoft products.“ ”
  • 28. Azure Machine Learning 1. Pick & drop models. No need to write scripts. 2. Uploaded data tables 4. Pre-built commands to transform or manipulate data 6. Evaluate models, Visualize result or export data 5. Specific settings to fine tune the models
  • 29. Easily turn data into intelligent action Action People Automated Systems Apps Web Mobile Bots Intelligence Dashboards & Visualizations Cortana Bot Framework Cognitive Services Power BI Information Management Event Hubs Data Catalog Data Factory Machine Learning and Analytics HDInsight (Hadoop and Spark) Stream Analytics Intelligence Data Lake Analytics Machine Learning Big Data Stores SQL Data Warehouse Data Lake Store Data Sources Apps Sensors and devices Data
  • 35. Windows 10 IoT Enterprise Desktop Shell, Win32 apps, Universal Windows Apps and Drivers 1 GB RAM, 16 GB Storage X86 Windows 10 IoT Mobile Enterprise Modern Shell, Universal Windows Apps and Drivers 512 MB RAM, 4 GB storage ARM Windows 10 IoT Core No Shell, Universal Windows Apps and Drivers 256MB RAM, 2GB storage X86 or ARM Premium Entry $ Device Capabilities Windows for Industry Devices
  • 42. Microsoft HoloLens Microsoft Confidential Gaze Gesture Ink Speech Identity Text Holograms Audio Tangible Emotional input output
  • 43. Virtual Reality A computer’s simulated version of reality Massive, immersive FOV Occlusion limits mobility, usefulness Gaming and focused uses Augmented Reality Data notifications tied to the real world Lightweight, mobile Overlays data, doesn’t integrate Navigation, light communication Holograms Your real and digital worlds integrated, enhanced with holograms Integrates your real and digital worlds seamlessly Not constrained by size of 2D, rectangular displays Intuitive, natural interactions Digital content is wherever you need it Complete Windows 10 computer
  • 44. A new way to see your world
  • 45. IoT & Azure the field of possibilities Alex Danvy @danvy

Editor's Notes

  • #4: This is how things are running for the last two decades and it’s not close to an end.
  • #5: Consumer Devices + best OS for IoT + apps Windows has been though with information consumption in mind. Modern design focus on content. Live tiles give a overview of your things. Business From the prototype to the Cloud Microsoft is an IoT player for decades now. A lot of ATM, gaz stations, etc. are running on Windows Embedded. We embraced the modern IoT challenges with Azure, our Cloud solution, simplifying how to store and deal with huge volume of data (Storage, SQL, HDInsight/Hadoop), extract information (BI) and bring intelligence to the story (Machine Learning). Azure has solutions for small set of devices (Azure Mobiles Services) to the most demanding scenarios of thousands devices (EventHub, Devices and apps create the link to the business
  • #14: Speaker notes: Azure meets a broad set of international and industry-specific compliance standards, such as ISO 27001, HIPAA, FedRAMP, SOC 1 and SOC 2, as well as country-specific standards including Australia IRAP, UK G-Cloud, and Singapore MTCS. Azure cloud services, with independently verified compliance, give you the foundation to achieve compliance for the infrastructure and applications you run in Azure. Azure is subjected to rigorous audits by independent organizations and the results are available to you as a part of Microsoft's commitment to transparency. Microsoft was also the first to adopt the uniform international code of practice for cloud privacy, ISO/IEC 27018, which governs the processing of personal information by cloud service providers.
  • #16: Why this Slide: You need some reference to come back to after the IaaS demo because now you are transitioning to PaaS. You want to focus the attention to the building blocks that you will show in the next demo – a web app, SQLDB, Storage and CDN. Key Points: We already said that your mental model of this picture is IT Lego – building blocks you provision and use. Your job is to work out what you need and to glue them together. Illustrate on the slide the 4 parts of the app you will use. Reinforce PaaS – the SERVICE looks after everything for you. The responsibility to keep these services working is now Azure’s – NOT yours (as it is with software you run in a VM). DON’T SPEND TOO MUCH TIME HERE – it’s a brief transition slide to the DEMO… Transition to NEXT Slide: Let’s see PaaS in action
  • #17: Let’s dive a little deeper in to what makes Azure Machine Learning unique—it’s easy to manage and monitor solutions right from the Azure portal. If you’re not already using Azure, your IT team can set up an Azure subscription in seconds with the help of a set-up wizard Then they can quickly enable data scientists by creating ML Studio workspaces. All you need is a Windows Live ID, and you can provision a Studio account. The data scientist then doesn’t need to mess with the Azure portal, she receives an email saying she’s ready to get started. Then right from the Azure Portal, your Azure ops team can predict expenses by monitoring storage and CPU usage of workspaces and web services with a near real-time view And when your data scientists are ready to deploy a model to production, or update an existing model, the team will receive alerts
  • #23: Smart Contracts are unable to access external data or events based on time or market conditions. Calling code or data outside of a Smart Contract or blockchain breaks the general trust barrier and authenticity of transactions. Cryptlets will allow the blockchain to access external data securely, while maintaining the integrity of the blockchain.
  • #26: Last year the United States Postal Service processed 150 Billion pieces of mail – far to much for efficient human sorting, but as recently as 1997, only 10% of all the hand-addressed mail was sorted automatically. Why? https://about.usps.com/who-we-are/postal-facts/size-scope.htm http://en.wikipedia.org/wiki/Handwritten_Address_Interpretation
  • #27: Because this is a tough problem – the type of problem machine learning is designed to solve. It has taken so many years to automate the sorting of the mail because reading handwriting is hard due to all the variables involved. Even humans have trouble reading other humans’ handwriting, if you can imagine the thousands of ways someone can write a name or address, this is a huge machine learning problem to solve. How can we teach the machine to read the mail and how can the machine learn and get better over time?
  • #28: The answer is by providing feedback both in terms of humans training the machine learning models and the machine learning from the patterns in the data over time. By providing feedback, the Postal Service was able to train computers to accurately read human handwriting. This is where the “learning” part of machine learning comes in. Data scientists created a model based on all the data they had on how people can write addresses. Then they train the model as more data comes in, correcting attempts at reading handwriting when they’re off, until the model has enough of a history to draw from that it can accurately read handwriting. Today, with the help of machine learning, over 98% of all mail is successfully processed by machines. https://about.usps.com/who-we-are/postal-facts/size-scope.htm http://en.wikipedia.org/wiki/Handwritten_Address_Interpretation
  • #29: Back in the 90s when the post office was wrestling with this issue, we were also working on Machine Learning, starting in 1991 when Microsoft Research was formed. As early as 1999 they were using it to help create email filters by predicting which emails were junk, and which were relevant. And as John Platt mentions—it’s a key technology that Microsoft uses to develop its own software. In 2004. Machine learning was part of Microsoft’s search engine It is also used in Bing Maps as part of the traffic prediction service. And many people know about how it was a key technology to make Kinect a reality, letting computers track people’s gestures and sort through what’s relevant and what’s not. Like filtering out a dog in the background to see a player’s movements. And today, this technology that has been developed over decades is becoming available commercially as part of Azure It’s this depth of experience with machine learning, testing and refining over years, using it to develop pretty much all Microsoft products, that makes Microsoft’s solution so robust.
  • #30: The beauty of simulation is that we can evaluate algorism or models without any engineering resource. Matchbox is an algorithm-based recommender developed by Microsoft Research in Cambridge, UK. Matchbox is offered as an out-of-the-box machine learning algorithm in Microsoft Azure Machine Learning Platform, which makes it easy to do predictive analytics of big data. Go to Demo.
  • #34: Animation set to loop (replace /Build walk in ?), Add session id to top Bot Framework provides everything you need to build and connect intelligent bots that interact naturally wherever your users are talking, from text/sms to Skype, Slack, Office 365 mail and other popular services. Bot Framework consists of three main components: Bot Connector, Bot Builder, and Bot Directory
  • #44: Microsoft is delivering the technologies for MPC as a platform for the first time in Windows 10   The MPC technologies for developers are identity, holograms, speech, touch, and ink   These technologies are part of the Windows core, and will be available in the full landscape of Windows 10 device, including HoloLens Example script: “Do you remember your first real computer? Mine was Tandy TRS 80. It was monochrome and had two floppy drives. I only started using a mouse after my sister gave me an IBM PC clone that ran Windows 3.1.   In just over forty years we’ve gone from punch cards and dip switches to playing games with the Kinect and using our fingerprints to unlock our phones. We’re starting to use the natural interactions that we’ve had since birth to engage our computers.   The idea behind HoloLens was to create a computer that would bridge our digital and real worlds using holograms. We call this new experience mixed-reality.   We wanted mixed reality to feel completely natural, so we used the same natural interactions that we use in the real world. On the left you see the natural inputs, on the right the natural outputs. This is why the human technologies of more personal computing are at the core of Windows 10. We created the most natural and intuitive interactions possible, available to the whole landscape of Windows 10 devices.”
  • #45: Audience understands: VR and MR exist at the opposite ends of a continuum VR and MR offer something unique, both are more valuable than AR, which sits between them on the continuum  Microsoft believes MR offers the most benefits across the most scenarios Example script: “To understand why mixed reality has such potential to transform the way we work, let’s talk about what makes it different from virtual reality and augmented reality.   VR delivers immersive experiences. These can be really exciting, especially when playing games. But VR’s immersiveness is also limiting, because it takes over all your senses and isolates you from the world around you. VR completely obscures your vision, so you can’t move around in the real world. And because you can’t see, you can’t use your hands to interact with things in the real world. One way to think about immersive VR is that it’s similar to 3D movies or TV. It’s powerful and can use useful, but infrequently so due to its limitations.   Augmented reality places digital information, usually visual, over your perception of the world around you. Whether you experience AR using apps on your smartphone or a device like Google Glass, AR is limited because it has no ability to comprehend the world around it, which means it can’t integrate the real and digital worlds. AR has no holographic capabilities, so you can’t directly engage with any of the overlays it puts over your world.   We wanted mixed reality with HoloLens to be more useful. We needed to be able to explore the world and use our hands to do stuff. To do that, we didn’t isolate you from the real world, we integrated digital experiences into the real world.   With HoloLens you move freely, so you can explore mixed reality in your spaces. And because you retain full use of your hands and vision, it is possible to do some amazing things. With mixed reality we can deliver spatial context and insight that you can’t get from either VR or AR.
  • #46: Holograms are the next evolution in computing. With this vision in mind, hardware, software, and user design engineers came together to create a new canvas for creators and developers. Microsoft HoloLens, together with Windows 10, introduces a powerful new holographic platform. The era of holographic computing is here. Microsoft HoloLens is truly something revolutionary. By blending holograms with reality it opens up entirely new ways to create, learn, collaborate, and visualize.   You see your creations come to life in the world around you. And, it is powered by Windows 10.