August 8, 2014
dig•it•al spa•ghet•ti– the art of creating new words that describe something technical to educate your friends and co-workers; helpful when playing buzzword bingo in your next emerging technology discussion. Digital spaghetti terms share a characteristic of being relatively new and lack a universally agreed upon definition.
With the evolution of anything – especially technology because it changes so fast – the vocabulary needed to describe the latest concepts is continuously evolving. Think about the last meeting you attended where emerging technology concepts were mentioned. Did everyone have the exact same definition of what those terms really defined? In some cases, these concepts are being used incorrectly and/or interchangeably when it’s important to understand the nuances of how each technology is an enabler of the others.
Axiom: When there’s a lack of reality coupled with a lot of talking, there tends to be mass misinformation.
In an attempt to untangle a bowl of digital spaghetti, let’s describe 3 terms that are peaking in today’s marketing hype cycle: The Internet of Things, Wearable Computing, and Context-Aware Computing.
The Internet of Things
The Internet of Things (IoT) describes technologies that allow wired and wireless systems to talk to each other, and usually over a common protocol like IPv6. But if you go back a few years, machine-to-machine (M2M) was used to describe the exact same thing. M2M provides the basics of connectivity and infrastructure via sensor/actuator, connectivity, data and management elements. IoT extends this concept by adding new elements including people, location and dynamic services.
In other words, M2M is about machines communicating with each other, whereas IoT extends and builds on this concept by enabling just about anything to communicate with the rest of the world. Based on these concepts, M2M is a subset of IoT.
Wearable computing (wearables)
Modern wearables include sensors – typically embedded in clothing, accessories or your body – which measure things like movement, temperature, light and location, to name just a few of the data points collected. Fitness armbands are great examples of wearables.
However, wearables are nothing new. Arguably, 19th century pocket watches or wristwatches are wearables in the sense that they can be worn and provide a service (compute time). Much as wristwatch wearers developed a heightened sense of time, modern wearables enable a heightened sense of “what’s going on”—news of the day, invisible details of our health, the thoughts of a loved one. The watch allowed new feats of time coordination; modern wearables enable increased personal and social awareness.
Though really just a pile of sensors with access to an Internet connection, wearables will continue to find novel applications in our work and home lives; more importantly, they serve as a primary source of data that enables something even bigger: context-aware computing.
Context-aware computing tries to predict what you do (or do not) want to happen next. A present-day example is when your vehicle proactively calls for emergency services after detecting a crash, or when your cell phone automatically silences itself knowing that you are in a meeting. It works by continuously acquiring information about a user and his or her environment; modeling the current circumstance or intention of a user; reasoning what the next best action should be; and notifying a user or other apps/services of an action.
Instead of being a singular technology, context-aware computing exists as a result of combining four other emerging technologies that are reaching critical mass: smartphones, embedded sensors, Big Data analytics, and cloud computing. At the core of this is an intelligence engine, context computer or “brain” which uses predictive modeling to generate contextual intelligence – i.e. context-aware computing.
And the winner is?
It is understandable if your brain feels a bit like mush after reading about these concepts. IoT, wearables, and context-aware computing all describe systems that are loosely coupled yet require high cohesion.
Understanding the relationships and differences among concepts is important; what’s more important is that they do not bog down you and your team. Think of definitions as placeholders that describe something. Because everyone’s organization is different, successfully navigating these concepts, as well as future ones, means agreeing on how you want to use them. A successful emerging technology team must agree how they should be defined for their organization—and then normalize around the concepts.
If you are not successful defining emerging technology terms, you still may win buzzword bingo – but you won’t win your audience, and you may end up with digital indigestion.