I think the first time I heard about it there was some discussion of a European appliance

manufacturer who had a refrigerator that was connected to the network, the Internet. And

I think the scenarios that were playing out there were: "Okay, what if the refrigerator

was smart and knew enough to adjust temperatures?" Maybe it knew enough to send a request or

a message to the manufacture saying "Hey, the compressor is going bad." That was the

first time I had heard about this idea of connecting a product to the network. A product

that wasn't a traditional computer; wasn't something that we thought was supposed to

be connected to the network or interconnected. And that started to open up a lot of people's

eyes I think to this idea. It may not have been the first theoretical time that it was

discussed but it was the first time that I think popular media and culture started talking

about this idea.

But, for whatever reason that connected refrigerator didn't really take off. The idea really didn't

kind of explode. Then we started hearing about the connected washing machine in the same

kind of context. And I think that that idea of the Internet of Things then started to

refine a bit and we heard about machine-to-machine communication. The idea that instead of human

to machine, so sort of through a screen or through a webpage or through our mobile phones

or whatever, that machines would talk to one another. So the idea of a stock quote generating

a message that would be sent to another machine that might think about "Okay now I may need

to make a trade." So the automated trading world. Or a weather forecast that's reported

online triggering a message to another system that's going to adjust stock levels. So this

idea that machines might talk to one another without a human in between was sort of a refinement

I think of the Internet of Things idea.

And now over the last handful of years we're seeing more consumer facing ideas and concepts

and products coming out that I think has regenerated interest in this machine-to-machine communication.

So now we're hearing things about the connected car and the connected thermostat and the smart

home. So now that the consumer side of things is heating up, we're also asking ourselves

from a business perspective: "What is the Internet of Things for a business?" Maybe

where you don't have a consumer product or a widget that you sell. Maybe you're a services

company or a bank, what does the Internet of Things mean for a business like that, particularly

a services company?

And so for companies that aren't as consumer facing or product oriented, I think there's

more opportunity but more sort of clouds around what the Internet of Things means for business.

And I think that anything that we think about, that we estimate, that we operate in, places

we work in, people we work with, we think about the effectiveness of those things, the

effectiveness of our workplace, the effectiveness of a warehouse, the effectiveness of routes

that a truck takes or that a forklift makes. And we make guesses about the right ways to

design a workspace or design a logistics path, design a warehouse. And the question is can

we use the idea of sensors to collect data about things that we were just guessing about

before, that we were estimating, that we were sort of using our gut to design? Can we collect

real data about performance of people and places and processes that can give us more

insight into optimizing and evolving our designs for the way our business works? And that's

what I call the Internet of Business Things. It's not the consumer facing stuff, it's the

business stuff.

Most of the data we think about from an enterprise perspective is sort of modular, it's transactional,

it's a call center call or it's a web transaction or it's a sale or it's a quote or it's a piece

of data about a product. But the Internet of Things will be creating streams of data.

So one of the analogies is how social media creates streams of data. So we've got tweets

and we've got flows on our wall and such that are more streams of information. And so think

about a sensor that might be on a door in a warehouse. Every time the door opens the

sensor records a door opening, a time of day, a day of the week. Maybe it creates some other

ambient information - it records the temperature in the facility or it records how long the

door was open or whatever. So these are little bits of data that are happening every time

the door is open. And that door might be open a lot of times during an hour or a day or

a week or a month, but it's creating these streams of data. And it's not like that one

piece of data might be that interesting, but it's the trends and the patterns and things

that we're looking for in the data that may be what we're looking for.

So I want to know how often is that room used during the morning, the afternoon, certain

days of the week, weeks of the month, months of the year, to help me be more efficient

about the way I staff people in that office or the temperature or the cooling or the electricity

that I feed to that part of my facility. So that data that's created, these streams of

data are sets of data that I may not already have a technology platform to process. I don't

know how to process streams maybe. So now I have to think about a new architecture,

a new way to process a stream of data, not just a stream but maybe I have a hundred facilities

that I have these sensors in and they're creating these streams of data. So now I've got a new

challenge around data.

One of the challenges starts to feed and link into the big data topic. So as I'm collecting

these individual sensor data points over hundreds or thousands or tens of thousands of sensors

every minute or every second, I've now got these parallel streams of data I have to process.

And so it's unclear exactly how much data I would want to keep for how long, but it's

certainly a new kind of data architecture, and for some companies will be a big data

problem because there's going to be a lot of this data for large companies for a lot

of sensors and a lot of facilities or a lot of products that they want to track or whatever

it is that they want to get more insight into by putting tags or sensors on them. So, to

me this is one of the sort of subsets, subdomains of big data around sensor data, streams of

data that we're going to have to think about new architectures and new designs of and new

technologies for capturing them, storing them, processing them, abrogating them, analyzing

them and so on. So I think it's going to be a real interesting evolution to see how the

big data technologies and technologies in general are emerging to deal with streams

of sensor data.