The Internet of Missing-Some-Things, Part 2: Semantics

I got a little side-tracked with other good topics over the past month, but the 2011 tech predictions podcast by Minnov8 reminded me that there's still much to talk about with regards to the "Internet of Missing-Some-Things." In the podcast, Steve Borsch puts the Internet of Things as his #1 item for 2011, but a discussion follows which asks the question, "why hasn't it already taken off?" I firmly believe one of the reasons is that there is a lot of hidden complexity in the problem area. Hence my "...Missing-Some-Things" series of posts.

Even before I started building TelemetryWeb, I knew there were a lot of very hard problems to solve when trying to combine the semantic web with the M2M market ("Machine-to-Machine"...the term for the market that existed before IoT became the buzz-word).

The Minnov8 gang really hit on a number of great points, but one of the best is that humans get frustrated with the rigid structure of taxonomies/ontologies. They can figure out how to manage semantic information with tags.

Google, Facebook, and other companies have done pretty amazing things with semi-structured information, to be sure. Search engines are getting really good at finding relevant websites or potential connections between people. But these systems still rely on a human to look at the list of results and determine which of them are valid.

But machines require much more structure in order to produce reliable results. And reliability is what you expect when you are creating a closed-loop system between, say, industrial controls and monitoring sensors.

Despite the significant evolution of computers, humans still make computers look pretty dumb by comparison. We can combine and correlate lots of semi-structured information, all in real-time, all in our heads. But someone has to tell the machine that "C", "Celsius", "Centigrade", "Deg-C", etc. all mean the same thing before the computer can effectively correlate temperature data of the same type, or do the necessary conversions to "F", "Fahrenheit", "Kelvin", and so on. What? You mean this particular "C" is the unit of measure of amperage capacity for a lithium-polymer battery? Uh-oh!

The greatest potential in the Internet of Things is the ability to utilize the data in ways that were not previously anticipated. Once the data is freed from the physical constraints of the device, it can provide tremendous benefit (if utilized correctly/responsibly, of course).

But without these sorts of semantics in place, the data in the cloud is locked into purpose-specific software. That software is traditionally written with one goal in mind and makes use of a lot of assumptions regarding the devices and the data they send. The only way you correlate disparate data across systems like these is through difficult, expensive, point-to-point system integrations. That model simply doesn't scale effectively enough to provide the kind of value people are envisioning.

There are potential solutions for these sorts of problems. I happen to think I have a few in the works. But until someone figures out how to merge the semantic web within the context of machine-to-machine communication, we're going to be limited to single-purpose, non-integrated, hardware-plus-software solutions.