The Internet of Things is transforming how companies do business.
With devices collecting real-time information about products and assets, it's never been
easier to benefit from IoT, and those benefits include: Eliminating downtime, reducing environmental
impact, and delivering breakthrough products innovations.
Today, Rockwell Automation is delivering industrial automation solutions across infrastructure,
manufacturing, power generation, and so much more.
They've been using Azure IoT already to connect to the equipment that powers these industries,
and using Azure Services to predict the maintenance needs and eliminate downtime for them.
So let's look into the future at some of Azure's new intelligent edge capabilities that Rockwell
Automation will be using to detect visual defects and anomalies automatically.
Now, for context, as devices and sensors generate more and more data, such as video data, it's
more practical to deliver compute and AI right down to the devices themselves.
Now, this is where Azure IoT Edge comes in.
Azure IoT Edge enables Azure Services as well as your own code to escape the cloud and be
deployed directly down onto devices and managed remotely -- all on devices smaller than a
Raspberry Pi, or as large and capable as the solution calls for.
To see this in action, let's take a look at Rockwell Automation's operational dashboard.
Now, in this dashboard, I have two alerts.
One is inside the building, and the other is up on the roof.
Let's take a look at the one inside the building first.
And when I click on it, I see the image of an anomaly that was captured.
Now, this anomaly was detected by a camera produced by Qualcomm in partnership with Microsoft.
It has rich compute and AI capabilities, and it runs Azure IoT Edge.
Now, to power this, we've used Azure Machine Learning to build an AI model, and packaged
it up in a Docker container, and then deployed it to this camera.
Because we're using this technique, we can deploy it to millions of these in minutes.
Through various talks this week, you're going to see us show you exactly how easy it is
for you to do the same thing.
Now, with Azure IoT Edge and our AI models running locally on this camera, it means Rockwell
doesn't have to send all of that video to the cloud.
Instead, they can simply send alerts.
It also means they don't have to manually inspect all those pipes.
Now, our AI model detected a stress fracture, and if left untreated, it can be very dangerous.
So I'm going to create a ticket in Dynamics 365 to dispatch a technician.
Great.
So back on our dashboard, the second alert is a pressure drop in a pipe up on the roof.
Now, environments like this can be dangerous to technicians, and very costly to organizations
to deploy them.
So this really calls for a solution with a new perspective.
DJI is the world's leader in drone technology.
From ready-to-fly consumer products to highly configurable industrial platforms capable
of doing jobs that are dull, dirty, or just dangerous.
And, like us, they give people the tools they need to bring their innovations to life.
Microsoft is partnering with DJI to bring Azure IoT Edge right to their drones.
And this is significant because it means any Azure developer using Azure Machine Learning
can develop AI models and deploy them to their drones.
It also means I can take that same AI model that went to the Qualcomm camera and deliver
it to the DJI drone.
Now, this incredible drone is a DJI M210 RTK and it's capable of running Azure IoT Edge
right on board.
This smaller drone is a DJI Mavic Air, and it's perfect for learning the principles of
flight and for developing and testing your AI models.
Now, it's all well and go to talk about drones, but I bet you'd like to see me fly one, and
I would love to, but unfortunately, in a room like this, you need a commercial drone pilot
license to do that, and they're incredibly hard to get.
So for that, we're going to welcome Francisco from DJI out to the stage to fly for us.
Come on out.
(Applause.)
Now, Francisco is going to be flying the DJI Mavic Air over the pipes that you see here,
which represent the ones 150 feet up on the roof.
And the Mavic Air is going to be streaming video back to the laptop here, which is running
Azure IoT Edge as well as our AI model, all packaged up in a great UWP app.
And when it sees the anomaly, it'll draw that same yellow bounding box that you saw with
the Qualcomm camera.
All right, let's check it out.
Now, as you can see, we're detecting that anomaly in real time.
But for the first time ever, we're able to stream video back from that drone to this
laptop running IoT Edge and our AI model, which was developed in the cloud.
And as I mentioned, the M200 will be running that right on board.
Great, thank you, Francisco.
(Applause.)
Now, that anomaly was pretty easy to see, but in the real world, there's hundreds of
pipes over thousands of miles, so solutions like this will save Rockwell significant time
and expense.
Now, if you're eager to try this out, DJI is offering an early release of the Windows
SDK exclusively to Build attendees.
Stop by their booth, check it out, and try it for yourself.
You've just seen two instances of the intelligent edge in action, deploying the same AI model
to both the Qualcomm camera as well as the DJI drone.
And the best part is, as I find new defects in my model and retrain it, I can deploy that
out in minutes to millions of devices, immediately making the intelligent edge even more intelligent.
Thank you.