Get in touch: Speak to a Sales Rep
877-633-1102


Request a follow-up
Back to all blog posts

| Lyle Paczkowski Things on the internet and the rise of the big machine

Let’s take a completely different look at the Internet of Things (IoT). Flip it on its head. From an organizational standpoint, it’s really more about Things on the Internet (ToI?), and the reasons why they are on the Internet at all.

It’s certainly not so that any given company can collect trillions of pieces of data, most of which end up useless anyway. You may care about the temperature reading from a remote sensor in a room full of sensitive equipment right now, and you’re glad to be updated on that temperature every 10 seconds. But as long as the temperatures were where they should be and there were no anomalies, you don’t care what all the temperature readings were yesterday or the day before, so there’s essentially no value to that data beyond the now.

Thus an organization needs to ask itself why it is implementing these Things on the Internet. The answer will come down to the purpose of the organization. And when that purpose becomes the foundation, all your ToI essentially aggregate into one single Big Machine.

Let’s take a hospital as an example. Why does it exist? To diagnose illnesses and injuries and treat and heal patients. That is its Big Machine role, and all the sensors and monitors and appliances and other ToI elements aggregated together are feeding into that grand purpose.

Big Machines don’t have to be physically large. They can range from robots to cars to a manufacturing plant, a single hospital, a hospital network, even a nationwide railroad system. But what they all have in common is the need, from a machine and network perspective, to see, feel, hear, and think.

Let’s take the autonomous car, which we’ve talked about before. As an entity, it is one Big Machine whose purpose is transport, and everything it does, everything it senses, everything it communicates with, is all designed to accomplish that purpose.

Handling the Big Machine

When you conceptualize the Big Machine, then you must begin asking what technology you need to enable it to serve its purpose. What equipment, what network, and how do you control it? Who controls it?

To deal with the Big Machine and enable it to serve its purpose, you need a system that can quickly accommodate shifts in technology, not something hardened that will become obsolete and limit your abilities to adapt. Security, of course, is paramount. The administrative topology must appropriately determine user rights at all the necessary levels and make sure that the needed information is getting exactly where it needs to be, when it needs to be there.

And what about the network? The Big Machine requires a totally virtualized network that can connect with other networks both internally and externally. It calls for whatever combination of wireless and wireline is needed for the right levels of mobility and stability. Because the only way the Big Machine can function is through a network. Its rise encompasses all the equipment, all the information generated, and all that the network transports.

And that network must assure the security of the data, because information is the most important thing that any organization owns today.

Deep Thinking

We need our Big Machines to do deep learning, but more importantly, we need to them to do deep thinking. To illustrate the difference, let’s consider a machine-assisted – not autonomous – vehicle. If that vehicle can analyze all the data and its surroundings and warn me that I am going to have an accident in five seconds, that is deep thinking. I may be able to avert the accident thanks to that warning.

If no warning comes, and I have my accident, and the machine merely logs that information and reports it to a remote site, noting all the damage, location, etc., that is deep learning. It hasn’t done me nearly as much good.

Machines and networks can collect so much data today it seems almost infinite to us. What we need to do is truly take advantage of that data by teaching these machines and networks to think, to predict. Then our Big Machines will be fulfilling their grand purpose.

What do you think will be the next IoT trend?

 

Back to all blog posts

Comments

    […] In many cases, the applications may be as simple as a data analysis derivative, or as complex as a deep learning, deep thinking […]

    […] The autonomous vehicle will demand this kind of network capacity. One estimate is that the average autonomous car will be transmitting and receiving 9 petabytes of data per year. That’s 9,000 terabytes, or 9 million gigabytes. That is a machine that takes learning to a new level – and, as we have talked about previously, to the point of deep thinking. […]

Leave a comment

Our comments are screened for spam by Akismet. By submitting your comment and personal information above, you agree that this information will be available to Akismet subject to their Privacy Policy.