(upbeat music)
- Coming up we made the intelligence edge real
by showing you how you can leverage
IoT in secure intelligent ways
starting with a look at the new Azure Digital Twin service,
how to secure devices in the intelligence edge
with Azure Sphere in the new development kit,
easy ways to apply intelligence on data
from your IoT devices with Azure Cognitive Services,
new options for managing your
IoT devices with Azure IoT Central,
and how you can apply serverless
event driven automation on the Edge.
So I'm joined again today by Jeff Holland,
welcome Jeff, good to have you buddy.
- Thanks so much, it's good to be here.
- No stranger to Microsoft Mechanics.
Now we've been hearing a lot about IoT
and the work that Microsoft's been doing in this space
over the past year and I know that you, yourself,
are an early adopter of the technology
but for those among us who are waiting
for the technology to prove itself a little bit more,
how real is it today and what are
some of the applications that you're seeing?
- Yeah, so it is very real.
And you can see this kind of every day
in our lives with things like home automation
but it's really starting to take off in the industry too.
So what we've set out to build here in Azure
is an entire IoT platform that not only
allows you to take advantage of those
connected devices on the Edge
that can send data back but one that also adds
device-level security with things like Azure Sphere.
Lets you reason and analyze on the data
coming from those devices with Stream Analytics,
or Azure Data Bricks.
Applies intelligence to give predictive incites
using machine learning and cognitive services.
Letting you manage the health of those devices
with IoT Central and of course even
kicking off serverless automation or workflows
with services like Logic Apps.
- Right, so this platform approach
offers a lot of convenience for people.
You're not having to source a lot of different services
and implement and manage your own IoT ecosystem.
And I imagine this puts IoT within the reach
of organizations everywhere.
- Yeah, it really does.
Really, any smart device that's connected to the internet
can start to leverage IoT.
So let me make this real for you:
I have this example on my phone,
I'm actually running an application
from one of our partners, CBRE.
And this is built on top of the new
Azure Digital Twin Service that was announced today.
And this application enables organizations
to create a digital twin of a physical space
so that they can optimize how that space is being used.
So it's powered over here with this app.
As you'll notice I can use this to get some work done.
Whether I need to have a meeting
or find where someone's working.
Now, I want to have a meeting,
so I'm gonna select this option and I can even come down
and choose the devices that I want for my meeting.
So, in this case I say I want a service hub
and I want a Skype meeting room.
Now, once I apply this search
you'll notice here the map of my building.
Some of these rooms are lit up green,
some of them are lit up that they're occupied,
and in fact, over here, it's actually recommending
that I have my meeting in this Amber room.
I can actually click navigate here
and using GPS on my phone,
now I have turn-by-turn directions to this room.
Now this is awesome because it's not just leveraging
the scheduling information,
it's actually pulling real-time data from the physical space
which is extremely valuable for a scenario like this
where I want to find a conference room
but you can imagine this might also be nice
if I need to find where someone's working.
- Exactly, it looks incredibly useful
being able to see in real-time
your choices for finding an appropriate
and available space for your needs.
I know we've all been in similar situations,
some of us at this conference here as well,
we're visiting a new building,
struggling to find a free space to work,
so how does this actually work under the covers?
- Yeah, so the digital twin graph has been set up
and is used to model the physical space
because there is various devices that are gonna be
feeding into this real-time perspective
across the entire environment.
Now the Digital Twin Service enables us
to virtually model the relationship
between people, places, and devices
that all coexist within a physical space.
And what's great about the Azure IoT ecosystem
is that it's entirely open so you can utilize
any smart device and include it in it.
So you can imagine you might have
a simple pressure sensor on your chairs
to know if the seat has been occupied or not.
- Right, so you can basically use IoT devices
in this example to get a full real-time view
of the current work environment.
Whether I'm looking for a work space or I'm in facilities
and want to know for space-funding perspectives
or if I'm in a device in sensitive work-space areas.
How do we make sure that these are all secure
and they can't be hacked or compromised?
- So one nice thing about Azure here
is that we've actually approached security
of IoT from a few different angles.
So, first when it comes to the management of these devices,
all of these services and apps
are backed by role-based access control.
Now what that means is that only the right people
with the right permissions
can make changes to any part of the system.
Now, next it's really important
that you have secure communication to your device.
You need to make sure that your device
is who they say it are
and to prevent things like a man-in-the-middle attack,
IoT hub enabled a number of ways for you
to securely communicate with your device,
including certificates so that you can encrypt and sign
every message that's being sent and received.
Now, finally, Azure can actually provide security
even at the silicon level.
So Azure Sphere is a new solution
for creating highly secured micro-controller units, or MCUs,
and power those devices where security
now starts at the silicon level.
- [Matt] So help us understand Azure Sphere
a little bit more, is it a piece of hardware, specifically?
- Yeah, so, Azure Sphere is actually a three-part solution.
So it includes this MCU,
which is the tiny single-chip computer,
but it also has an operating system
and a cloud security service.
So if we start with the MCU,
these are about the size of your thumbnail
and MCUs are found in everything.
Over nine billion new MCU-powered devices
are built and deployed every single year.
And more and more of these are starting
to have connectivity built in.
So we actually have an Azure Sphere dev kit up here
which we'll show you in just a second.
But this Azure Sphere was just released
and based on our over 15 years of experience
of building hardware like Xbox.
Now Azure Sphere MCUs are a new class of MCU
where security is just built in.
Now this isn't just a processor,
this has memory, connectivity, compute,
and it evens comes with secured isolation
using our Pluton subsystem
so that we can store private keys.
Now what's cool here is that on top of the hardware
is the Azure Sphere operating system.
Now this operating system was purpose-built for IoT security
and it includes isolation at the OS layer
so that your system layer is completely isolated
from your application layer.
So even if you had a malicious application code
that was on your device,
it's unable to gain access
to those secured elements of your device.
Now, the last layer is the Azure Sphere
security service itself.
Now this is a turn-key cloud service
that guards every Azure Sphere device.
And it does a few critical things.
It can broker trust so that communication
is always certificate-based and authenticated,
but it can also detect emerging threats
across the entire IoT ecosystem.
And then using that knowledge it can then improve security
through software updates to ensure that devices stay secure,
even as the IoT threat landscape might evolve.
- [Matt] Right, so who's Azure Sphere really for then?
- Any manufacturer who's working with MCUs today,
and they're interested in connecting to the internet
should think about how they can use Azure Sphere
to improve their security story.
Now what's great is that we have these dev kits
and they come with everything you need
to get started and they're available
starting today so we've actually got one here up on stage.
You can see I've got this USB cable,
it's plugged directly into my machine,
so now I can start to build applications to power this.
So, here on my screen, I actually have
a very simple Azure Sphere application.
What I want to be able to do for our office
is have a secured light switch
to turn on our light switch over here, our light bulb.
So, in my solution and visual studio
I've been able to write this code,
it's really simple, I'm just looking
to see if the button has been pressed
on our light switch using Azure Sphere.
And if I detect that that button's been pressed,
I will go ahead and encrypt and send
a secure message out to IoT hub
which will be relayed to our light switch here.
Now, I'm gonna cross our fingers that this all works out,
I've deployed this to our Azure Sphere powered light switch.
- Yeah. - So Matt, if you don't mind,
go ahead and give us a nice press.
- I will press your button.
In three,
two,
one, boop.
- 'Kay, he pushes it,
and right away, there we go!
The light switch is turned on,
that secure message sent to the cloud,
and turning on our office lights.
- The sound effects I gave was optional as well.
- It was. - Doesn't come with the kit.
I went into auto-pilot there.
- I enjoyed it.
- I hope we'll all agree, a very enlightening demo, Jeff.
(audience applauding)
- [Jeff] Come on, you've got to appreciate that.
Yes, enlightening demo.
- [Matt] Now because this was built with Azure Sphere,
we can be confident in knowing
that nothing else can turn on this light switch,
this light bulb, apart from this specific light switch.
And this is gonna remove a major blocker
for using IoT devices in the enterprise.
Now we also mentioned the Intelligent Edge a lot,
so what is that that makes these devices intelligent
and how are we able to harness it?
- So, this is where it gets very cool,
and this is actually my favorite part.
'Cause hopefully we're all aware of the massive leaps
that machine learning and artificial intelligence
have made over the last decade but this next
exciting wave that Microsoft is leading,
is around just what you talked about, the Intelligent Edge.
And the idea here is that you actually
run the analysis directly on the devices themselves.
Whether those devices are online or offline
and you're just leveraging the cloud
to help build and train those models.
- So that seems like it's gonna be able to process faster
and work with or without internet connectivity.
- Yeah, exactly right.
This is what we mean when we talk about
the Intelligent Edge and it's especially important
for scenarios where every millisecond matters.
You could think of a factory line,
you might have machinery that has sensors
and machine learning running on those machines.
Well if there's a problem with one of those machines
you need to act on it right away,
you can't deal with any extra latency
that sending a message out to the cloud might bring.
Not to mention you could be saving massively
on egress charges from having to push
all of this data over the internet.
- Right, so that all sounds great,
but what does it take to bring that
intelligence to an IoT device.
Does this mean I need some background
in machine learning or advanced mathematics?
- Yeah, so, I'm actually gonna show you
how you can build one of these today.
If you think back to our conference room scenario
what I want to build is a solution so that
if there's conference room with a camera in it
that camera is smart enough to know
if a person has just sat in the chair
or if it's just a bag or some other object.
So, we actually have up here on stage with me
this IoT camera and I need to be able to train
this camera to be smart enough to know
does this chair have a bag in it or is it a person?
So to build this I'll show you my screen quickly.
I'm starting here in the Azure Cognitive Services.
And this is the Azure Custom Vision Service.
Now, I've been able to use this service to power
IoT camera, you can see here I've actually
uploaded a few sample images already.
Some of these are tagged that a person
is present in the conference room
and other ones are tagged that it's empty.
And what's powerful here is that
without having to write a single line of code
I can click this train button and train this model
so now when it sees new images
that it might have never seen before,
it can accurately predict is this a person or not.
Now bringing this back to IoT,
I don't want to have to send the video feed
from my devices constantly up into the internet.
So what I can actually do here back on my screen
is in Azure Cognitive Services,
I can click this export button.
And export this model to run directly
on the IoT device itself.
So now all of that processing can happen there.
So that's exactly what we've done,
we'll test this out, I've deployed this
working model to our IoT camera
that's up here on the stage and Matt,
you can notice that it's not yet registered
there's a person there, there's nothing happening.
But if you'll go ahead and take a seat.
- And I noticed that, before I go,
that you had, it was a dockerfile,
so that's a docker container running on that device.
- That's right, yeah so it's all powered through containers.
- [Matt] Okay, there we go.
- So he goes ahead, he takes a seat.
And you'll notice right away, as soon as he
sits down this device has detected that there's
a person, the lights have flashed,
and it lets us know this is not just a bag,
it's not a wet blanket, this is a person.
- Thanks, I'm not just a bag.
Thanks very much, also very cool, what do you think?
(audience applauding)
So this analysis was able to happen
even though you weren't connected to the internet,
or that camera wasn't specifically.
It all happened locally on the device
and it seemed like it was pretty easy
to train the model as you showed.
So it becomes accessible for developers
of all skill levels just to get started with.
Now, once we've got all these intelligent devices
powering different solutions, how do we manage it?
Because the operations person in me
is a little bit worried it's a nightmare
to manage all of these connected devices
and keep them up to date.
- Honestly, traditionally IoT management has been a struggle
because you're adding all of these new devices
into your business, how do you keep it from
just becoming a tangled mess?
So, the last thing that I want to show you here
is another solution in the Azure IoT platform
and this is Azure IoT Central.
It became generally available today,
and this is a fully managed SaaS solution that allows you
to connect, monitor, and manage your IoT assets at scale.
So in our offices we want to provide snacks
for our employees so we've got a few
refrigerated vending machines around on different floors.
And what's awesome is here in IoT Central,
I can actually get a single view
into all of the different devices
that I have configured to my business.
And if I wanted to get more specifics on a specific device,
like I want to know what's happening on floor two,
I just simply click into that device,
and now here I have real-time insights
into the health and temperature of this device.
- [Matt] That's awesome, cool stuff.
Lots of useful information for people
to glean from those specific devices.
Now, that's a great example of managing
and monitoring device health,
but what happens if a device has an issue?
Can we automatically take action?
- Absolutely, so IoT Central has this cool functionality
called Rules and I can specify Rules for my IoT devices.
So for our refrigerated vending machines
I want to know if the temperature ever gets too high.
So I can come in here and go ahead and set a rule
and I can specify a high temperature alert.
Now I can choose if I want this alert to run
on all devices of this class
or just on this specific device.
I can even define the condition here,
so you'll notice I've set a condition already
that says if the temperature goes
above 60 degrees Fahrenheit, I need to fire an alert.
The food is getting too warm,
I might food poison all of my employees.
And the last element here in my rule
is the action that I want to take.
Now I actually have a few different options
for actions here.
I can do something as simple as write an email
or I can execute server-less workflows
or run server-less code,
and respond to any of these rules firing.
So that's actually what I've wired up here,
this is a server-less work flow
that will run whenever a vending machine gets too hot.
It's gonna automatically post a message
to our operations team
and let them know that a device needs to be serviced.
I can then create an incident in Dynamics 365
and then I also have some logic here to continue to track
that incident to make sure if it doesn't get resolved
I can escalate it to make sure everything's taken care of.
So this means now that my device health and management
can trigger automatically without any human intervention
so hopefully you can see that from the silicon,
to the cloud, to IT management,
Azure has really provided a fully-featured solution
that allows me to work with IoT and AI
in a productive and secure way.
- Well, awesome, thanks Jeff.
Thanks for joining us today on the show and making IoT real.
It's always a pleasure to have you.
Now, how can people go and learn more?
- So that Azure Digital Twin service
that I showed you earlier is available now in preview.
You can get a dev kit for Azure Sphere,
also in preview today, and you can try out
any of the technologies that I showed you
at any of these links shown behind me.
- Awesome, and of course, keep watching Microsoft Mechanics
for the latest tech updates.
Subscribe to us on Twitter,
thank you so much for watching, bye for now.
(audience applauding) (upbeat music)