Tag Archives: language

Looking for a quick definition of IoT?

Defining IoT (image Wikipedia)

Defining IoT
(image Wikipedia)


Tired of looking for the right words when trying to impress your boss, friends, or potential future spouse with a description of the Internet of Things, aka IoT ? Well look no further !

The 10 word version

Here’s a 10 word version. An IoT device is one that:

1. Computes
2. Is networked
3. Interacts with the environment in some way

The 20 word version

And once you’ve impressed them with this knowledge that just rolled off your tongue, feel free take it further with the 20 word version!

1. Computes
2. Is networked
3. Interacts with the environment with the intention of collecting sensory data and/or manipulating the local environment

For example:

  • A FitBit device computes, is networked, & interacts with the environment (ie you)
  • An industrial  SmartGrid meter computes, is networked, & interacts with the environment (collects power data)
  • A residential Nest meter computes, is networked, and interacts with the environment (collects temperature data)
  • Chicago’s Array of Things devices compute, are networked, and interact with the environment (collect many environmental data points)
  • Blood glucose monitors compute, are networked, and interact with the environment (ie you)
  • and much much more !!

And then, while impressing those around you, you can bring it on home with the definition of an IoT System. An IoT system:

1. Is a set of IoT devices that
2. Communicate with each other and/or communicate with
3. A central server that aggregates data and/or provides control data

Congratulations on your assured future personal, social, and professional successes now that a handy definition of IoT is at your disposal!

Talking about IoT

word cloud from 3 business magazine articles on IoT

word cloud from 3 business magazine articles on IoT

I was curious if language in articles and blog posts on IoT varied significantly with the type of magazine or blog. So my unscientific quick and dirty research was to use three semi-arbitrarily* chosen articles from three different types of blog or magazine, do word frequency counts in each of these, and then from this do a word cloud where font size varies with frequency of the word count. The three magazine/blog types were: business magazine or blog, industry trade magazine or blog, and vendor magazine or blog.  (*I say ‘semi-arbitrarily’ because I chose them all myself and I’m sure my Googling/searching habits aren’t without some bias).

The first word cloud above was made by piling the words of all three articles together and then doing a word frequency count on the combined verbiage, sorting the counts, and then creating a word cloud. I used Wordle.net to do this and it makes the last three steps pretty easy to do.

Similarly, I made sorted word frequency word clouds for articles from three industry/trade magazines/blogs and did the same again for vendor magazines/blogs:


word cloud from 3 industry/trade magazines/blogs


word cloud from 3 vendor blogs

Side by side, they look like:

side by side comparison of the same

side by side comparison of the same (click to increase size)

While there are a number of things that could be done to make the comparison more robust (higher sample count, remove ‘stop words‘, etc), I think even this little snippet of samples shares some interesting results (or at least provides direction/motivation for digging deeper with a larger sample set). Some ‘eyeball’ observations from this sample set:

  • security & privacy more prevalent in trade/industry articles/posts
  • vendor articles/posts seem to hit harder on data
  • trades & vendors heavier on sensors
  • business sample skewed some with a chunk of text from one article dedicated to talking about IoT parking systems

Language use is important because, among other things, it directly affects how we categorize, classify, and discuss risk.

Again, no smoking gun here and there’s plenty of room to make this more robust, but the use of the language used to talk about IoT it becomes more prevalent might be interesting to keep an eye on.


If you’re interested … the three articles/posts from business magazines/blogs were:
Wall Street Journal –
Forbes –
Business Insider –

The three articles/posts from industry/trade magazines and blogs were:
CIO magazine –
Dark Reading –
EE Times

And the three articles/posts from vendor articles/posts were:
Cisco –
Microsoft –
Atmel –

Choosing your language for your audience when communicating risk


Learning another language …

Communicating risk requires identifying the right language for the right audience. While your experience may be in technical systems and all of the things that can go wrong with them, trying to communicate risk in technical terms to business leaders is generally a futile endeavor. There are a couple of reasons for this:

1) Technical systems and the risk issues that go along with them typically are heavily jargon-laden and without a lot of reference points to the outside world.
2) Everybody has limited bandwidth for talking about risk. You’ve got a very narrow window in which to communicate the issues.

That second point is one of the best pieces of advice that I’ve ever received regarding communicating risk. No matter how good your message may be, there is a finite amount of tolerance that people have to discuss risk in a given discussion. Exceed that window and you’ll be able to hear the clunk as their eyes roll into the backs of their heads.

All the more reason for choosing your language carefully. So, instead of techno-speak, when talking to business leaders, speak in terms of things that are meaningful to them. Depending on your background, this preparation may require a little bit of work on your part. What information products/services (eg reports, databases, workflows, etc) do they count on to do their work? What things do they count on to look good to peers and bosses? (This one may sound childish, but it’s not. It’s got a solid foothold in Mazlow’s hierarchy of needs).

Once you’ve identified what those needs are, you can work backwards to what information systems support them and what risks are associated with those technical systems. Techno-speak with the people supporting these systems is okay, that’s their language. But when communicating risk to business people (possibly to get funding to support your risk mitigation), you’ve got to speak their language.

The Downloads page has a pdf of this graphic.

Metaphors Amuck for CyberRisk


Nagasaki, Japan 1945

PW Singer wrote a great piece for the LA Times last month, “What Americans should fear in cyberspace.” .  In the article, Singer drives home the point of the dangers and harm done of equating risks in cyberspace with historical physical and kinetic events such as Pearl Harbor and using language borrowed from the physical space — weapons of mass destruction, Cold War, etc.

By using such language, such poorly contemplated metaphors, actual risk is not communicated. Worse, misinformation (aka statements-&-proclamations-that-are-wrong) is the thread. Singer points out that instead of educating, we fear monger.

In my opinion, one reason for fear mongering with pithy armageddon-esque descriptions instead of providing education is two fold:

  • it is easier to fear monger than it is to educate
  • fear mongering titillates and sells advertising

None of this is to say that there is not a real challenge in communicating risk. There is a real challenge. As a society, we don’t have a basis for understanding this kind of risk. It’s much too new. In the shipping, financial, some health, and even sports industries, there are decades or centuries of actuarial data to work with. This industry has at most two decades, but even that is not terribly useful given the rate of change of the ecosystem and attack types.

Singer suggests studying other examples of how society has handled new (massive) ideas such as the story of the Centers for Disease Control and Prevention in public health.  This seems like a great idea. (Right now, I wish I could think of more).

“The key is to move away from silver bullets and ever higher walls … “

Singer goes on to say that cyberrisk is here to stay and needs to be viewed as a new perennial management problem. Further, we need to acknowledge that attacks and degradation will happen and we need to plan for this. Planning for this and not wishing it away is building resilience. This, I believe, is the key. And with that enduring problem come the hard decisions of dedicating resources — whether from company revenue streams or ultimately taxpayer funds.

What metaphors can we use to better educate without fear mongering? How do you think national and business resilience should be funded?

[Image:Wikimedia Commons]