The annual Consumer Electronics Show (CES) in Las Vegas is usually a showcase of the latest electronic gadgets and gizmos with 4K, curved and 3D TVs the rage in recent years.
This year was a little different. Sure, there were a handful of eye-catching devices, but the show was a glimpse into the not too distant future when every device in the world will be connected to the Internet. This is an exciting yet daunting prospect and companies are now faced with a huge opportunity and a huge dilemma as this Internet of Everything (IoE) becomes reality.
The business challenge
The proliferation of connected devices is generating an explosion of data that has the potential to save and earn tremendous amounts of money, time and resources for companies. The problem is that most companies do not have the capability to analyse the data and respond in a timely manner. It takes too long to send the data from device to cloud for analysis and most tools are not sophisticated enough to process the mass of data in a meaningful, timely way.
Analytics processing power must be built at the “edge” of the network, not deep inside the database, so businesses can respond to the data quickly and efficiently.
“Edge” computing is all about making sure data is processed at the right place and time. It makes the best possible use of available network resources and bandwidth by using processing power both at the edge of the network and in the data centre. Each business needs a way to figure out which data needs to be processed immediately — at the edge — and which data should be moved for deeper historical analysis.
IT vendors are releasing software to figure out how to best analyse which data should exist on the Edge. For example, Cisco’s “Connected Analytics for the Internet of Everything” portfolio is designed to give businesses across industries access to near real-time information, predictions and trends that can have an immediate impact on business.
A retail example
Surveillance cameras in retail store are a simple example of Edge computing. Most footage needs to be processed in real-time to be capable of catching shoplifters or to identify shoppers who require immediate assistance. Consumption of this footage needs to happen on the Edge of the network, without delay.
Video analytics can also occur at the centre of the network once large batches of data have been captured. This can help store managers with queue management and checkout times. This type of analysis helps stores stock the right products and send expert staff to areas where customers have high interest and would benefit from extra help to make a purchase decision.
Recently a global retailer used Edge data analysis to realise a $68 million increase in revenue and $98 million reduction in labour costs.
A manufacturing example
Manufacturers constantly analyse the factory floor looking for ways to become more efficient.
The rise of the IoE means that most, if not all, robotic equipment have sensors that are used to record output and respond to events. Edge computing is used to identify the health status of mission-critical equipment to enable the workers to respond to conduct preventative maintenance before a system fails. Pre-empting a system failure requires real-time processing in (or near) the device itself.
Centralised analysis is used for collating large amounts of data and looking for trends. Manufacturing decision makers use this analysis to identify opportunities to streamline the production process.
What it all means to you
The Internet of Everything is here, and every day more and more products are becoming Internet-enabled. Your business has increasing opportunities to learn more about your customers and to respond faster to their needs. If you haven’t started thinking about IoE and its impact on your business, then now is the time.