>> Scott: I've actually got a couple of devices plugged into me.

Right now I've got this band. This is real. It's monitoring

my heart rate. But I'm also a Type I diabetic. And I've been

diabetic for 20 years. One of the things that every diabetic

does when they become diabetic is they try to solve this problem

usually with Microsoft Excel; but at some point they try to figure

out, well, I'm a diabetic and I'm an engineer, let's plug some

wires together and see what we can do. So when we say the Internet

of Things, I think it's great that you, the normal sugared people,

you know, you have your FitBits, and we think that's adorable,

but I have an insulin pump and that insulin pump is plugged in.

There's the insulin pump. And it's plugged into my arm.

It's 24 hours a day.

And that talks to a system. Here is a CGM. That is my actual

live blood sugar right now.

You see how it's kicking up there a bit?

That's because of stress.

That's actually plugged in down here

in an implant in my side. Sorry to show you my chubbiness.

And this is real. When you hear Internet of Things, you think

Fitbit and you think Raspberry Pi, but I think this.

And we've plugged this into some cloud systems that I want to

share with you. While the Internet of Things is fun, things like

Raspberry Pi, this is great, this is a Raspberry Pi, this is

an Internet of Things enabled one. We've actually got C code

on this talking to this temperature sensor. So what does that

temperature sensor look like? Let me switch over to some code

here and show you.

This is some C code inside of Visual Studio. This is the low

level stuff. C code makes your eyes blur a little bit sometimes.

What you need to know, people who are wearing suits, is you've

got IoT Hub and you have Azure devices. So the takeaway there

is that that's cloud enabled. But for the developers that think

this is crazy, I want you to notice that we've actually got a

Visual Studio plug in to do remote debugging of things like Raspberry

Pis in Visual Studio. So whether it be high level, updating hundreds

of thousands of objects, or whether it's low level and doing

remote GDB debugging to a Raspberry Pi, we can do that.

Now let's talk about my system. Let me bring back to the slides

here for a moment. This is overwhelming. This is Azure, and

all these icons,

all these people doing all these things. Let's talk about me

and the system that I'm building.

That's me in my shirt.

I've got my bands. The band goes to Microsoft Health. That goes

ultimately into storage.

My glucose system actually goes up into an API, and I pull that

data in as well, because that's personal to me. I've got my

heart rate over years. I've got my blood sugar over years.

What can I do with that? I'm going to show you some visualizations,

some graphs and I'm going to plug some things into Office and

see if Azure machine learning can answer some really interesting

questions about me and my health. And this is all live and this

is all real.

So let's come back over to this machine here.

This is a system called Nightscout. This is an open source node

application that is running in Azure, and this talks to my CGM,

my Continuous Glucose Meter. And I want you to point out a couple

of things here.

This is the first presentation today.

And this is now.

That is a realtime system that is showing my blood sugar.

And one of the things that happens is not just that I drink orange

juice, which, by the way, I have in case I pass out, but also stress.

Stress dumps glucose into the system. And this is just one of

the things that I have to deal with when I'm managing my blood sugar.

And actually I'm not sure if the guy can get a tight shot of that.

But this just popped up and it will appear in the cloud.

It's warning me that I'm now going high. So in a second the

website is also going to announce, and I'll get a notification

on my band and on my watch, and people are going to start calling

me and it will be scary.

So there we go. Notification just showed up. So let's talk about

how that notification did in fact show up. I've got a band.

And this is some data in the cloud. How do I see that?

Well, turns out the band can talk some JavaScript. I can take

JavaScript out of the band. This is at developer.microsoft.band.com.

You may have a band. You may not be a developer, but you may

have a URL that points to JavaScript or a blog or some XML and

you want to create a tile. I made one for my blood sugar.

So now I've got Nightscout on my system, and I can see my blood

sugar right there.

What's interesting about this is that I can use this Visual Designer,

but I can also

look at the manifest directly and look at this.

That's the code there. Sugar is high. If it's over 150, notification.

And then I'll get a notification on my band. This could be done

with a build server, whether you want to water your plants, whatever.

That is the personal Internet of Things. And that's what makes

me happy. But let's think about this. Once my blood sugar is

in the cloud, what else can I do with it? I can send notifications.

My wife can be concerned. She's probably going to be calling

in a moment to make sure that I'm okay. But this is part of

the process. Remember how I said I want to analyze this stuff

in Excel.

Well, it turns out that I'm not very good at VBA, Visual Basic

for Applications. Remember that 80 percent of the world's business

logic runs in Excel. I think that's a fact. And in fact there's

an Excel JS API, JavaScript API for Excel. I can write an add

in for Excel in JavaScript using the Web technologies that I

know how to make. So we went and we made the

HanselSugarsProject, and I'm going to actually show you

some of the code here in just a second.

There we go.

Where we're going to populate a table in Excel using JavaScript,

using Web technologies. And what's exciting for this, exciting

for me about this, is that I didn't know how to do this before.

You see? I'm a Web developer. But now I can go in here put in

my target range, hit refresh, and now we're going to go and talk

to the backend system and then dynamically populate a chart in

Excel of my blood sugar that I could then send to a doctor or

my wife. You have to think about the sense of power and enthusiasm

I had suddenly have for Excel that I did not have before.

I'm a Web developer. That's a Web application in the pane there.

And it works in Excel Online.

And one day it will work in Excel on an iPad.

It's like pft. Once you learn how to use one Lego piece, you

can then plug them into other stuff. It's extremely heartening

for me to do this. Again, if my blood sugar isn't interesting

to you, and it shouldn't be, maybe some hobby of yours or some

thing at work or some inspiration will come into your mind and

you'll think about how you can plug these things in together.

That's what's so exciting about this. So I've got all my blood

sugar in real time. I can collect it into the cloud. What else

can I do with it? Let's switch over to another machine here.

I'm going to switch over to a Mac.

This is a Mac running VS Code. And this particular Mac has got

the code to collect my data from the whoops from the health API.

So we're going to go and make RESTful API calls, standard API

calls off to Microsoft Health, which is where the Band Aid is

stored, because this is the thing that's so important. It's my data.

It's my heartbeat data. My blood sugar is my data. Once I have

that ownership of that data, what can I do with it? I can plug

in that data and do different stuff. Let me see if I can jump

out of here. This has gone full screen.

Full screen can be a little confusing. There we go. I'm going

to take that data, and I'm going to pull it out of the Microsoft

Health API. And this is a storage explorer. The reason I wanted

to show you this on a Mac is because this is the Azure Storage

Explorer that we've released. That's cross platform. We're looking

at the CSV files of my blood sugar data as it's sitting in the cloud.

Excuse me. My heart rate data, pardon me. I'm going to hit download.

I'm going to throw that on a desktop. Watch the right side.

Now I have power. Now I have control. Now I've got a hold of

that and I can run analysis on it. And now in this case I just

brought it down to the desktop. I can do some test

notifications on my blood sugar.

I've got I can do some analysis here, but maybe I want to do

that analysis in a more sophisticated way. When you start thinking

about the Internet of Things, you start thinking about huge amounts

of data.

I said it has my heart rate. Like how much is that?

Is it an average over a minute, over five minutes, over hours?

This is a huge amount of data. My blood sugar is doing three

or 400 datasets every single day. Over the course of a year,

this adds up to huge amounts of information. This is where simply

putting it into Excel and sorting going looks like a pattern

isn't going to be enough for me. I'm going to need to do some

machine learning. I want to find out about why does my blood

sugar go up when I'm stressed out. What does Thanksgiving dinner

look like? Maybe I can answer those questions with machine learning.

So I'm going to switch back over to

this system here. And what I'm going to do,

I'm going to jump into here. This is a machine learning kind

of algorithm that I've put together, experiment, if you will,

to pull in data from the heart rate on the right there from Azure

Storage and the glucose data and I'm going to come up with a

stress index. I'm inventing a number the Hanselman Stress Index.

And we're going to load that data up. And what we're going to

do is clean it up, do a little bit of normalization, do a couple

of analysis, run some statistics, and then come up with a dataset

that the result is going to be a time based dataset of my stress.

Okay. So that's kind of interesting.

It's pretty powerful, though, that but I need to see it over time.

So how would I express this over time? And what value is there

in it?

Well, there is this API in Office 365 and all of Microsoft called

the Graph API, the Microsoft Graph, graph.Microsoft.com, and

this allows me to pull my information. I keep stressing, it's

my blood sugar, my heart rate, and my calendar and my e mail.

I want a unified API to go and get those things and the graph

API, you can see there at graph.Microsoft.com allows me to make

those requests. So what if we looked at my blood sugar and my

stress and my heart rate over time, overlaid on an Office 365

calendar, that could give us some insights. And again I don't

know anything about this stuff. This is what's so important and

why as a developer this is so exciting. I know JavaScript.

I know the Web. I know C#.

Now I'm feeling comfortable about the cloud. But when I see,

hey, this is an API and it uses JavaScript and I can access all

the graph data in Microsoft, that's amazing. That's a playground

of excitement. So I can go build this, get a start date and end date.

This is all standard

parsing of JSON, parsing of JavaScript, all using the graph API

and let's see what kind of question that could potentially answer.

So here is my calendar;

the stress index as it applies to calendar data. Let's click

on one. This is all real.

So here's glucose is updating.

I can see the different rehearsals and I can see heart rate and

sugar and stress changing. I can actually run queries and see

the result of that machine learning and ask the really burning

question, the question that we all have, which is what is the

most stressful person in my life that is causing these problems

and raising my blood sugar.

[Laughter] [Applause]

Darn it.

It is a really, really great time to be a developer.

I can put stuff like this together now. It is an extremely personal time.

It's an extremely empowering time. You know how we keep telling