Moving to the Edge

Internet of Things (IoT)-enabled “smart” gadgets are now so ubiquitous that we often forget that our everyday coffee machines, TVs, lights, cars and virtual assistantsare now capable of “talking” to each other — working behind the scenes to make our personal lives easier. 

Even on the business front, these webs of interconnected devices generating massive volumes of data, combined with the power of Artificial Intelligence (AI), are ushering in the fourth industrial revolution. 

We’ve witnessed the migration of computing power and storage from physical servers to the cloud. And now, with billions of devices collecting and processing data in real-time, we’re moving towards edge computing or the “Edge”. This is where the “local” work happens, like a half-way house for data where information is sorted and relayed back to the device before moving to its permanent home. According to Gartner, by 2022, a staggering 75 percent global enterprise-generated data will move to the Edge. 

Cloud — the problem child?

Moving data to the cloud and back to derive actionable insights takes time, and even a few seconds latency can prove costly — take the case of a driverless car that needs to stop the instant it identifies a pedestrian crossing the road.

With smart cities no longer mere aspirations shared by world leaders, the need to reduce latency time to derive actionable insights will only be further multiplied by the increase in data produced from an entire city's worth of autonomous vehicles, and other IoT infrastructure covering health, energy, and security. 

As entire nations start shifting to smart architecture fuelling a boom in data and devices, the Cloud may no longer be able to cope.

Moving to the Edge

Coupled with the need to protect massive amounts of citizen data and deliver quicker response times, edge computing will become an absolute necessity.

By relocating data processing closer to the end device, actions can be instantaneous without the need for data to move to a central cloud for analysis. And to make sense of it all, AI will come to the fore — and only improve the process further as a technology that matures when fed with more data.

Preparing for the avalanche

This all sounds great — but how do we go about implementing an IoT and Edge computing strategy? In a nutshell, at least right now, a lot of graft.

First, you’ll need a new kind of server — smaller, lighter and more rugged — so that it can withstand being deployed in the field where your connected devices are located and subjected to often harsh environments. You'll need to choose from hundreds of IoT platforms that currently exist, and build and deploy a new infrastructure that creates a network between all these various devices. 

That takes skilled and expensive talent, and it might seem daunting but it can start small. Look at how smart cities start with implementing IoT in street lighting to be more efficient. This generates cost savings in electricity, which in turn enables them to purchase additional equipment and eventually scale. 

As the IoT industry matures and adoption becomes widespread, accessibility to the technology will improve. Start with just one aspect of your business or operations and see what efficiencies can be gained. Smart IoT is coming, so don’t bury your head in the sand. It doesn’t have to be perfect to begin with —the important thing is just to start somewhere.