When Sensors Act Like Teenagers

A common cornerstone of both the Internet of Things and Internet of Everything concepts is the idea of a future with billions, if not trillions, of connections to the Internet. As the Internet of Everything connects objects, data, people and processes, the future of connected things will not be traditional computers or smartphones. Rather, it may be your refrigerator, or a traffic light, or even a litter box. Basically, anything that can have a status change that will interest someone has the potential to be connected to the Internet in order to alert you to that change.

The idea of being alerted to important information automatically is appealing. After all, if your refrigerator is having a cooling issue and it can send you a text alert, you can save money by taking corrective action before your milk and other products go bad. However, not all of the data generated by the Internet of Everything will be of high value. In fact, most of it will be of little value at all.

The primary issue for you to consider isn’t the way that our things will communicate directly to us the important facts they find. Rather, it is how they will communicate to each other as they identify those important facts. The connected things may very well end up being much more like a gaggle of teenagers than anything else. By that, I mean that they may chatter on incessantly about topics that few others find remotely interesting or important. Just as we grownups filter out the giggling teens at the mall, we will also have to filter out much of the chatter generated by our things.

Let’s consider a highly connected kitchen. I have read of the vision of the refrigerator, cabinets, and even individual products monitoring themselves and letting you know when you need to buy more or when an expiration date is rapidly approaching. Realistically, there will have to be central applications that capture all of the various communications coming from the sensors in the kitchen. Those apps will consolidate the data, identify what alerts are relevant, and send a summary to you as required.

Now imagine a grocery list application that keeps tabs on what you’ve got in stock and how much is left. Periodically, it will have to take a poll to see what the current state of every item is. That will generate a lot of data. However, most of the data will simply be an item stating that nobody has used any more of it and that it is still at the correct temperature. It is clearly important for the grocery list application to receive this information and incorporate it into an updated set of actions for you at the store. However, why in the world would you want to capture and store all of these intermittent communications?

The data generated by such devices will be more massive than we can imagine. If we actually tried to store it all for the long term, we’d have a huge and expensive problem. However, when most of the data has little value to begin with and even less value as time passes, we should not worry about storing it for the long term. The paradigm of capturing and keeping all of the data that we come across will need to change. The ongoing chatter between billions of devices doesn’t need to be recorded in a permanent fashion. After all, do you record or remember every conversation you have? No. We physically record or mentally memorize important conversations or moments and the rest of our verbal communication disappears forever soon after we say it or hear it.

In order to be cost effective and avoid overwhelming ourselves with useless data, we’ll need to aggressively filter the data generated by the Internet of Everything. If we apply reasonable filters that determine what we bother to store at all, and for how long we store it when we do, we can cut down the amount of data we deal with by orders of magnitude. Masses of data may be created and transmitted. But, much of that is done in very small batches of very small messages between things. The scale of the individual messages between things isn’t an issue at all. It is only in the aggregate that it becomes problematic.

As the Internet of Everything continues to evolve, the identification of what’s actually important will be a critical step in the process of generating meaningful analytics. You probably don’t remember or record the conversation you had with your spouse about what should have been on the grocery list two months ago. Why in the world, then, would you care to keep a record of the conversation that the things in your kitchen had as they help you put a list together? We let much teenage chatter go in one ear and out the other. Plan to do the same with much of the data generated by the Internet of Everything.

Bill Franks is Chief Analytics Officer for Teradata, providing insight on trends in the analytics & big data space and helping clients understand how Teradata and its analytic partners can support their efforts.  In addition, Bill is a faculty member of the International Institute for Analytics and the author of the book Taming The Big Data Tidal Wave (John Wiley & Sons, Inc., April, 2012).  He is also an active speaker and blogger.  Bill’s focus has always been to help translate complex analytics into terms that business users can understand and to then help an organization implement the results effectively within their processes.  His work has spanned clients in a variety of industries for companies ranging in size from Fortune 100 companies to small non-profit organizations.  You can learn more about Bill at http://www.bill-franks.com.