When is a cow not a cow? When it’s a Thing.
Since the beginning of the Internet of Things movement, one question has always followed it around: “what exactly is IoT?” It’s not actually IoT that people are struggling to understand, but the concept of a Thing and its relevance to the Internet.
Many experts will define a Thing as a physical object that can collect data. Some will even go further and say that there must be a measure of actuation i.e. it does something.
However it still doesn’t help us understand what a Thing is, simply because it lacks context, in the same way IoT needs value to help its understanding.
Shades of origins
Consider the first instance of “The Internet of Things” being applied by Kevin Ashton in 1999 – the lack of in-store stock of a particular shade of lipstick made by Proctor & Gamble.
The context of the Thing is cosmetics in retail, and the value of IoT is in optimising the supply chain so that sales aren’t missed.
Breaking ground with context
So how do we add context to a Thing? Cisco’s concept of the Internet of Everything (IoE), which was first published in 2011, was ground-breaking as it included:
It recognised that to achieve value we had to consider more than just a sensor that could collect data.
For me, a Thing broadly falls into these four categories:
- It’s what you have
- It’s what you are
- It’s what you create
- It’s what you learn
It’s not just an industry. Really.
Now these four categories clearly put me at odds with much of the IoT industry, because something you create (e.g. data) isn’t limited to an IoT company.
But that’s the point.
IoT shouldn’t be solely an industry, but a theme
Thanks goes to Kelsey Skinner for putting it so succinctly during a recent conference we both spoke at.
In fact, a Thing and IoT is just part of a bigger digital landscape that becomes clear when we look at the intersecting circles of the diagram above:
- What you have and are is now commonly called “quantified self”
- What you are and create is what we at Innovate UK define as “personal data”
- What you create and learn can be classed as “big data and analytics”
- What you learn and have is “machine learning & insights”, leading to “artificial intelligence”
Of course there are even more intersecting circles that we could begin to explore and the descriptions above are neither comprehensive nor definitive.
The digital ocean
IoT and its many Things form part of a much larger digital ecosystem that can have a transformative effect on industries and sectors; cities and societies.
It lets us provide context to technology that, in turn, allows us to demonstrate real-world value, encouraging us to dive further deeper into the ocean that is the digital economy.
Follow me on Twitter: @JonnyVoon
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